id	sid	tid	token	lemma	pos
iajs-2710	1	1	130	130	NUM
iajs-2710	1	2	fully	fully	ADV
iajs-2710	1	3	automated	automate	VERB
iajs-2710	1	4	magnetic	magnetic	ADJ
iajs-2710	1	5	resonance	resonance	NOUN
iajs-2710	1	6	detection	detection	NOUN
iajs-2710	1	7	and	and	CCONJ
iajs-2710	1	8	segmentation	segmentation	NOUN
iajs-2710	1	9	of	of	ADP
iajs-2710	1	10	brain	brain	NOUN
iajs-2710	1	11	using	use	VERB
iajs-2710	1	12	convolutional	convolutional	ADJ
iajs-2710	1	13	neural	neural	ADJ
iajs-2710	1	14	network	network	NOUN
iajs-2710	1	15	atheel	atheel	PROPN
iajs-2710	1	16	sabih	sabih	PROPN
iajs-2710	1	17	shaker	shaker	NOUN
iajs-2710	1	18	computer	computer	NOUN
iajs-2710	1	19	engineering	engineering	NOUN
iajs-2710	1	20	techniques	technique	NOUN
iajs-2710	1	21	,	,	PUNCT
iajs-2710	1	22	baghdad	baghdad	PROPN
iajs-2710	1	23	college	college	PROPN
iajs-2710	1	24	of	of	ADP
iajs-2710	1	25	economic	economic	PROPN
iajs-2710	1	26	sciences	sciences	PROPN
iajs-2710	1	27	university	university	PROPN
iajs-2710	1	28	baghdad	baghdad	PROPN
iajs-2710	1	29	,	,	PUNCT
iajs-2710	1	30	iraq	iraq	PROPN
iajs-2710	1	31	.	.	PUNCT
iajs-2710	2	1	atheel.sabih@baghdadcollege.edu.iq	atheel.sabih@baghdadcollege.edu.iq	PROPN
iajs-2710	2	2	abstract	abstract	ADJ
iajs-2710	2	3	the	the	DET
iajs-2710	2	4	brain	brain	NOUN
iajs-2710	2	5	's	's	PART
iajs-2710	2	6	magnetic	magnetic	ADJ
iajs-2710	2	7	resonance	resonance	NOUN
iajs-2710	2	8	imaging	imaging	NOUN
iajs-2710	2	9	(	(	PUNCT
iajs-2710	2	10	mri	mri	NOUN
iajs-2710	2	11	)	)	PUNCT
iajs-2710	2	12	is	be	AUX
iajs-2710	2	13	tasked	task	VERB
iajs-2710	2	14	with	with	ADP
iajs-2710	2	15	finding	find	VERB
iajs-2710	2	16	the	the	DET
iajs-2710	2	17	pixels	pixel	NOUN
iajs-2710	2	18	or	or	CCONJ
iajs-2710	2	19	voxels	voxel	NOUN
iajs-2710	2	20	that	that	PRON
iajs-2710	2	21	establish	establish	VERB
iajs-2710	2	22	where	where	SCONJ
iajs-2710	2	23	the	the	DET
iajs-2710	2	24	brain	brain	NOUN
iajs-2710	2	25	is	be	AUX
iajs-2710	2	26	in	in	ADP
iajs-2710	2	27	a	a	DET
iajs-2710	2	28	medical	medical	ADJ
iajs-2710	2	29	image	image	NOUN
iajs-2710	2	30	the	the	DET
iajs-2710	2	31	convolutional	convolutional	ADJ
iajs-2710	2	32	neural	neural	ADJ
iajs-2710	2	33	network	network	NOUN
iajs-2710	2	34	(	(	PUNCT
iajs-2710	2	35	cnn	cnn	PROPN
iajs-2710	2	36	)	)	PUNCT
iajs-2710	2	37	can	can	AUX
iajs-2710	2	38	process	process	VERB
iajs-2710	2	39	curved	curved	ADJ
iajs-2710	2	40	baselines	baseline	NOUN
iajs-2710	2	41	that	that	PRON
iajs-2710	2	42	frequently	frequently	ADV
iajs-2710	2	43	occur	occur	VERB
iajs-2710	2	44	in	in	ADP
iajs-2710	2	45	scanned	scan	VERB
iajs-2710	2	46	documents	document	NOUN
iajs-2710	2	47	.	.	PUNCT
iajs-2710	3	1	next	next	ADV
iajs-2710	3	2	,	,	PUNCT
iajs-2710	3	3	the	the	DET
iajs-2710	3	4	lines	line	NOUN
iajs-2710	3	5	are	be	AUX
iajs-2710	3	6	separated	separate	VERB
iajs-2710	3	7	into	into	ADP
iajs-2710	3	8	characters	character	NOUN
iajs-2710	3	9	.	.	PUNCT
iajs-2710	4	1	the	the	DET
iajs-2710	4	2	convolutional	convolutional	ADJ
iajs-2710	4	3	neural	neural	ADJ
iajs-2710	4	4	network	network	NOUN
iajs-2710	4	5	(	(	PUNCT
iajs-2710	4	6	cnn	cnn	PROPN
iajs-2710	4	7	)	)	PUNCT
iajs-2710	4	8	can	can	AUX
iajs-2710	4	9	process	process	VERB
iajs-2710	4	10	curved	curved	ADJ
iajs-2710	4	11	baselines	baseline	NOUN
iajs-2710	4	12	that	that	PRON
iajs-2710	4	13	frequently	frequently	ADV
iajs-2710	4	14	occur	occur	VERB
iajs-2710	4	15	in	in	ADP
iajs-2710	4	16	scanned	scan	VERB
iajs-2710	4	17	documents	document	NOUN
iajs-2710	4	18	case	case	NOUN
iajs-2710	4	19	of	of	ADP
iajs-2710	4	20	fonts	font	NOUN
iajs-2710	4	21	with	with	ADP
iajs-2710	4	22	a	a	DET
iajs-2710	4	23	fixed	fix	VERB
iajs-2710	4	24	mri	mri	NOUN
iajs-2710	4	25	width	width	NOUN
iajs-2710	4	26	,	,	PUNCT
iajs-2710	4	27	the	the	DET
iajs-2710	4	28	gaps	gap	NOUN
iajs-2710	4	29	are	be	AUX
iajs-2710	4	30	analyzed	analyze	VERB
iajs-2710	4	31	and	and	CCONJ
iajs-2710	4	32	split	split	VERB
iajs-2710	4	33	.	.	PUNCT
iajs-2710	5	1	otherwise	otherwise	ADV
iajs-2710	5	2	,	,	PUNCT
iajs-2710	5	3	a	a	DET
iajs-2710	5	4	limited	limited	ADJ
iajs-2710	5	5	region	region	NOUN
iajs-2710	5	6	above	above	ADP
iajs-2710	5	7	the	the	DET
iajs-2710	5	8	baseline	baseline	NOUN
iajs-2710	5	9	is	be	AUX
iajs-2710	5	10	analyzed	analyze	VERB
iajs-2710	5	11	,	,	PUNCT
iajs-2710	5	12	separated	separate	VERB
iajs-2710	5	13	,	,	PUNCT
iajs-2710	5	14	and	and	CCONJ
iajs-2710	5	15	classified	classified	ADJ
iajs-2710	5	16	.	.	PUNCT
iajs-2710	6	1	the	the	DET
iajs-2710	6	2	words	word	NOUN
iajs-2710	6	3	with	with	ADP
iajs-2710	6	4	the	the	DET
iajs-2710	6	5	lowest	low	ADJ
iajs-2710	6	6	recognition	recognition	NOUN
iajs-2710	6	7	score	score	NOUN
iajs-2710	6	8	are	be	AUX
iajs-2710	6	9	split	split	VERB
iajs-2710	6	10	into	into	ADP
iajs-2710	6	11	further	further	ADJ
iajs-2710	6	12	characters	character	NOUN
iajs-2710	6	13	x	x	PUNCT
iajs-2710	6	14	until	until	SCONJ
iajs-2710	6	15	the	the	DET
iajs-2710	6	16	result	result	NOUN
iajs-2710	6	17	improves	improve	VERB
iajs-2710	6	18	.	.	PUNCT
iajs-2710	7	1	if	if	SCONJ
iajs-2710	7	2	this	this	PRON
iajs-2710	7	3	does	do	AUX
iajs-2710	7	4	not	not	PART
iajs-2710	7	5	improve	improve	VERB
iajs-2710	7	6	the	the	DET
iajs-2710	7	7	recognition	recognition	NOUN
iajs-2710	7	8	score	score	NOUN
iajs-2710	7	9	,	,	PUNCT
iajs-2710	7	10	contours	contours	PROPN
iajs-2710	7	11	are	be	AUX
iajs-2710	7	12	merged	merge	VERB
iajs-2710	7	13	and	and	CCONJ
iajs-2710	7	14	classified	classify	VERB
iajs-2710	7	15	again	again	ADV
iajs-2710	7	16	to	to	PART
iajs-2710	7	17	check	check	VERB
iajs-2710	7	18	the	the	DET
iajs-2710	7	19	change	change	NOUN
iajs-2710	7	20	in	in	ADP
iajs-2710	7	21	the	the	DET
iajs-2710	7	22	recognition	recognition	NOUN
iajs-2710	7	23	score	score	NOUN
iajs-2710	7	24	.	.	PUNCT
iajs-2710	8	1	the	the	DET
iajs-2710	8	2	features	feature	NOUN
iajs-2710	8	3	for	for	ADP
iajs-2710	8	4	classification	classification	NOUN
iajs-2710	8	5	are	be	AUX
iajs-2710	8	6	extracted	extract	VERB
iajs-2710	8	7	from	from	ADP
iajs-2710	8	8	small	small	ADJ
iajs-2710	8	9	fixed	fix	VERB
iajs-2710	8	10	-	-	PUNCT
iajs-2710	8	11	size	size	NOUN
iajs-2710	8	12	patches	patch	NOUN
iajs-2710	8	13	over	over	ADP
iajs-2710	8	14	neighboring	neighboring	NOUN
iajs-2710	8	15	contours	contours	NOUN
iajs-2710	8	16	and	and	CCONJ
iajs-2710	8	17	matched	match	VERB
iajs-2710	8	18	against	against	ADP
iajs-2710	8	19	the	the	DET
iajs-2710	8	20	trained	train	VERB
iajs-2710	8	21	deep	deep	ADJ
iajs-2710	8	22	learning	learning	NOUN
iajs-2710	8	23	representations	representation	NOUN
iajs-2710	8	24	this	this	DET
iajs-2710	8	25	approach	approach	NOUN
iajs-2710	8	26	enables	enable	VERB
iajs-2710	8	27	tesseract	tesseract	ADJ
iajs-2710	8	28	to	to	PART
iajs-2710	8	29	easily	easily	ADV
iajs-2710	8	30	handle	handle	VERB
iajs-2710	8	31	mri	mri	NOUN
iajs-2710	8	32	sample	sample	NOUN
iajs-2710	8	33	results	result	NOUN
iajs-2710	8	34	broken	break	VERB
iajs-2710	8	35	into	into	ADP
iajs-2710	8	36	multiple	multiple	ADJ
iajs-2710	8	37	parts	part	NOUN
iajs-2710	8	38	,	,	PUNCT
iajs-2710	8	39	which	which	PRON
iajs-2710	8	40	is	be	AUX
iajs-2710	8	41	impossible	impossible	ADJ
iajs-2710	8	42	if	if	SCONJ
iajs-2710	8	43	each	each	DET
iajs-2710	8	44	contour	contour	NOUN
iajs-2710	8	45	is	be	AUX
iajs-2710	8	46	processed	process	VERB
iajs-2710	8	47	separately	separately	ADV
iajs-2710	8	48	hard	hard	ADJ
iajs-2710	8	49	to	to	PART
iajs-2710	8	50	read	read	VERB
iajs-2710	8	51	!	!	PUNCT
iajs-2710	9	1	try	try	VERB
iajs-2710	9	2	to	to	PART
iajs-2710	9	3	split	split	VERB
iajs-2710	9	4	sentences	sentence	NOUN
iajs-2710	9	5	.	.	PUNCT
iajs-2710	10	1	the	the	DET
iajs-2710	10	2	cnn	cnn	PROPN
iajs-2710	10	3	inception	inception	PROPN
iajs-2710	10	4	network	network	PROPN
iajs-2710	10	5	seems	seem	VERB
iajs-2710	10	6	to	to	PART
iajs-2710	10	7	be	be	AUX
iajs-2710	10	8	a	a	DET
iajs-2710	10	9	suitable	suitable	ADJ
iajs-2710	10	10	choice	choice	NOUN
iajs-2710	10	11	for	for	ADP
iajs-2710	10	12	the	the	DET
iajs-2710	10	13	evaluation	evaluation	NOUN
iajs-2710	10	14	of	of	ADP
iajs-2710	10	15	the	the	DET
iajs-2710	10	16	synthetic	synthetic	ADJ
iajs-2710	10	17	mri	mri	NOUN
iajs-2710	10	18	samples	sample	NOUN
iajs-2710	10	19	with	with	ADP
iajs-2710	10	20	3000	3000	NUM
iajs-2710	10	21	features	feature	NOUN
iajs-2710	10	22	,	,	PUNCT
iajs-2710	10	23	and	and	CCONJ
iajs-2710	10	24	12000	12000	NUM
iajs-2710	10	25	samples	sample	NOUN
iajs-2710	10	26	of	of	ADP
iajs-2710	10	27	images	image	NOUN
iajs-2710	10	28	as	as	SCONJ
iajs-2710	10	29	data	data	NOUN
iajs-2710	10	30	augmentation	augmentation	NOUN
iajs-2710	10	31	capacities	capacity	NOUN
iajs-2710	10	32	favors	favor	VERB
iajs-2710	10	33	data	datum	NOUN
iajs-2710	10	34	that	that	PRON
iajs-2710	10	35	is	be	AUX
iajs-2710	10	36	similar	similar	ADJ
iajs-2710	10	37	to	to	ADP
iajs-2710	10	38	the	the	DET
iajs-2710	10	39	original	original	ADJ
iajs-2710	10	40	training	training	NOUN
iajs-2710	10	41	set	set	NOUN
iajs-2710	10	42	and	and	CCONJ
iajs-2710	10	43	thus	thus	ADV
iajs-2710	10	44	unlikely	unlikely	ADJ
iajs-2710	10	45	to	to	PART
iajs-2710	10	46	contain	contain	VERB
iajs-2710	10	47	new	new	ADJ
iajs-2710	10	48	information	information	NOUN
iajs-2710	10	49	content	content	NOUN
iajs-2710	10	50	with	with	ADP
iajs-2710	10	51	an	an	DET
iajs-2710	10	52	accuracy	accuracy	NOUN
iajs-2710	10	53	of	of	ADP
iajs-2710	10	54	98.68	98.68	NUM
iajs-2710	10	55	%	%	NOUN
iajs-2710	10	56	.	.	PUNCT
iajs-2710	11	1	the	the	DET
iajs-2710	11	2	error	error	NOUN
iajs-2710	11	3	is	be	AUX
iajs-2710	11	4	only	only	ADV
iajs-2710	11	5	1.32	1.32	NUM
iajs-2710	11	6	%	%	NOUN
iajs-2710	11	7	with	with	ADP
iajs-2710	11	8	the	the	DET
iajs-2710	11	9	increasing	increase	VERB
iajs-2710	11	10	the	the	DET
iajs-2710	11	11	number	number	NOUN
iajs-2710	11	12	of	of	ADP
iajs-2710	11	13	training	training	NOUN
iajs-2710	11	14	samples	sample	NOUN
iajs-2710	11	15	,	,	PUNCT
iajs-2710	11	16	but	but	CCONJ
iajs-2710	11	17	the	the	DET
iajs-2710	11	18	most	most	ADV
iajs-2710	11	19	significant	significant	ADJ
iajs-2710	11	20	impact	impact	NOUN
iajs-2710	11	21	in	in	ADP
iajs-2710	11	22	reducing	reduce	VERB
iajs-2710	11	23	the	the	DET
iajs-2710	11	24	error	error	NOUN
iajs-2710	11	25	can	can	AUX
iajs-2710	11	26	be	be	AUX
iajs-2710	11	27	made	make	VERB
iajs-2710	11	28	by	by	ADP
iajs-2710	11	29	increasing	increase	VERB
iajs-2710	11	30	the	the	DET
iajs-2710	11	31	number	number	NOUN
iajs-2710	11	32	of	of	ADP
iajs-2710	11	33	samples	sample	NOUN
iajs-2710	11	34	.	.	PUNCT
iajs-2710	12	1	keywords	keyword	NOUN
iajs-2710	12	2	:	:	PUNCT
iajs-2710	12	3	technological	technological	ADJ
iajs-2710	12	4	treatment	treatment	NOUN
iajs-2710	12	5	,	,	PUNCT
iajs-2710	12	6	deep	deep	ADJ
iajs-2710	12	7	learning	learning	NOUN
iajs-2710	12	8	,	,	PUNCT
iajs-2710	12	9	machine	machine	NOUN
iajs-2710	12	10	learning	learning	NOUN
iajs-2710	12	11	,	,	PUNCT
iajs-2710	12	12	convolutional	convolutional	ADJ
iajs-2710	12	13	neural	neural	ADJ
iajs-2710	12	14	networks	network	NOUN
iajs-2710	12	15	,	,	PUNCT
iajs-2710	12	16	magnetic	magnetic	ADJ
iajs-2710	12	17	resonance	resonance	NOUN
iajs-2710	12	18	,	,	PUNCT
iajs-2710	12	19	brain	brain	NOUN
iajs-2710	12	20	.	.	PUNCT
iajs-2710	13	1	ibn	ibn	PROPN
iajs-2710	13	2	al	al	PROPN
iajs-2710	13	3	haitham	haitham	PROPN
iajs-2710	13	4	journal	journal	PROPN
iajs-2710	13	5	for	for	ADP
iajs-2710	13	6	pure	pure	ADJ
iajs-2710	13	7	and	and	CCONJ
iajs-2710	13	8	applied	apply	VERB
iajs-2710	13	9	science	science	NOUN
iajs-2710	13	10	journal	journal	PROPN
iajs-2710	13	11	homepage	homepage	NOUN
iajs-2710	13	12	:	:	PUNCT
iajs-2710	13	13	http://jih.uobaghdad.edu.iq/index.php/j/index	http://jih.uobaghdad.edu.iq/index.php/j/index	NOUN
iajs-2710	13	14	doi	doi	NOUN
iajs-2710	13	15	:	:	PUNCT
iajs-2710	13	16	10.30526/34.4.2710	10.30526/34.4.2710	PROPN
iajs-2710	13	17	article	article	NOUN
iajs-2710	13	18	history	history	NOUN
iajs-2710	13	19	:	:	PUNCT
iajs-2710	13	20	received	receive	VERB
iajs-2710	13	21	1	1	NUM
iajs-2710	13	22	,	,	PUNCT
iajs-2710	13	23	august	august	PROPN
iajs-2710	13	24	,	,	PUNCT
iajs-2710	13	25	2021	2021	NUM
iajs-2710	13	26	,	,	PUNCT
iajs-2710	13	27	accepted	accept	VERB
iajs-2710	13	28	26	26	NUM
iajs-2710	13	29	,	,	PUNCT
iajs-2710	13	30	september	september	PROPN
iajs-2710	13	31	,	,	PUNCT
iajs-2710	13	32	2021	2021	NUM
iajs-2710	13	33	,	,	PUNCT
iajs-2710	13	34	published	publish	VERB
iajs-2710	13	35	in	in	ADP
iajs-2710	13	36	october	october	PROPN
iajs-2710	13	37	2021	2021	NUM
iajs-2710	13	38	.	.	PUNCT
iajs-2710	14	1	mailto:atheel.sabih@baghdadcollege.edu.iq	mailto:atheel.sabih@baghdadcollege.edu.iq	PROPN
iajs-2710	14	2	ibn	ibn	PROPN
iajs-2710	14	3	al	al	PROPN
iajs-2710	14	4	-	-	PUNCT
iajs-2710	14	5	haitham	haitham	PROPN
iajs-2710	14	6	jour	jour	X
iajs-2710	14	7	.	.	PROPN
iajs-2710	14	8	for	for	ADP
iajs-2710	14	9	pure	pure	ADJ
iajs-2710	14	10	&	&	CCONJ
iajs-2710	14	11	appl	appl	PROPN
iajs-2710	14	12	.	.	PUNCT
iajs-2710	15	1	sci	sci	PROPN
iajs-2710	15	2	.	.	PROPN
iajs-2710	16	1	34(4)2021	34(4)2021	NUM
iajs-2710	16	2	131	131	NUM
iajs-2710	16	3	1	1	NUM
iajs-2710	16	4	.	.	PUNCT
iajs-2710	16	5	introduction	introduction	NOUN
iajs-2710	16	6	it	it	PRON
iajs-2710	16	7	provides	provide	VERB
iajs-2710	16	8	us	we	PRON
iajs-2710	16	9	with	with	ADP
iajs-2710	16	10	an	an	DET
iajs-2710	16	11	overview	overview	NOUN
iajs-2710	16	12	of	of	ADP
iajs-2710	16	13	several	several	ADJ
iajs-2710	16	14	related	related	ADJ
iajs-2710	16	15	areas	area	NOUN
iajs-2710	16	16	of	of	ADP
iajs-2710	16	17	research	research	NOUN
iajs-2710	16	18	.	.	PUNCT
iajs-2710	17	1	since	since	SCONJ
iajs-2710	17	2	no	no	DET
iajs-2710	17	3	other	other	ADJ
iajs-2710	17	4	algorithms	algorithm	NOUN
iajs-2710	17	5	have	have	AUX
iajs-2710	17	6	been	be	AUX
iajs-2710	17	7	proposed	propose	VERB
iajs-2710	17	8	that	that	SCONJ
iajs-2710	17	9	exactly	exactly	ADV
iajs-2710	17	10	match	match	VERB
iajs-2710	17	11	our	our	PRON
iajs-2710	17	12	goal	goal	NOUN
iajs-2710	17	13	,	,	PUNCT
iajs-2710	17	14	many	many	ADJ
iajs-2710	17	15	similar	similar	ADJ
iajs-2710	17	16	tasks	task	NOUN
iajs-2710	17	17	are	be	AUX
iajs-2710	17	18	examined	examine	VERB
iajs-2710	17	19	,	,	PUNCT
iajs-2710	17	20	especially	especially	ADV
iajs-2710	17	21	the	the	DET
iajs-2710	17	22	detection	detection	NOUN
iajs-2710	17	23	and	and	CCONJ
iajs-2710	17	24	text	text	NOUN
iajs-2710	17	25	extraction	extraction	NOUN
iajs-2710	17	26	from	from	ADP
iajs-2710	17	27	brains	brain	NOUN
iajs-2710	17	28	,	,	PUNCT
iajs-2710	17	29	and	and	CCONJ
iajs-2710	17	30	the	the	DET
iajs-2710	17	31	detection	detection	NOUN
iajs-2710	17	32	of	of	ADP
iajs-2710	17	33	objects	object	NOUN
iajs-2710	17	34	in	in	ADP
iajs-2710	17	35	scanned	scan	VERB
iajs-2710	17	36	images	image	NOUN
iajs-2710	17	37	and	and	CCONJ
iajs-2710	17	38	the	the	DET
iajs-2710	17	39	classification	classification	NOUN
iajs-2710	17	40	of	of	ADP
iajs-2710	17	41	forms	form	NOUN
iajs-2710	17	42	.	.	PUNCT
iajs-2710	18	1	in	in	ADP
iajs-2710	18	2	general	general	ADJ
iajs-2710	18	3	,	,	PUNCT
iajs-2710	18	4	these	these	DET
iajs-2710	18	5	algorithms	algorithm	NOUN
iajs-2710	18	6	consist	consist	VERB
iajs-2710	18	7	of	of	ADP
iajs-2710	18	8	detecting	detect	VERB
iajs-2710	18	9	brain	brain	NOUN
iajs-2710	18	10	-	-	PUNCT
iajs-2710	18	11	like	like	ADJ
iajs-2710	18	12	objects	object	NOUN
iajs-2710	18	13	,	,	PUNCT
iajs-2710	18	14	followed	follow	VERB
iajs-2710	18	15	by	by	ADP
iajs-2710	18	16	the	the	DET
iajs-2710	18	17	extraction	extraction	NOUN
iajs-2710	18	18	of	of	ADP
iajs-2710	18	19	information	information	NOUN
iajs-2710	18	20	in	in	ADP
iajs-2710	18	21	the	the	DET
iajs-2710	18	22	form	form	NOUN
iajs-2710	18	23	of	of	ADP
iajs-2710	18	24	human	human	ADJ
iajs-2710	18	25	-	-	PUNCT
iajs-2710	18	26	readable	readable	ADJ
iajs-2710	18	27	text	text	NOUN
iajs-2710	18	28	,	,	PUNCT
iajs-2710	18	29	similar	similar	ADJ
iajs-2710	18	30	to	to	ADP
iajs-2710	18	31	what	what	PRON
iajs-2710	18	32	we	we	PRON
iajs-2710	18	33	aim	aim	VERB
iajs-2710	18	34	to	to	PART
iajs-2710	18	35	do	do	VERB
iajs-2710	18	36	the	the	DET
iajs-2710	18	37	new	new	ADJ
iajs-2710	18	38	image	image	NOUN
iajs-2710	18	39	,	,	PUNCT
iajs-2710	18	40	which	which	PRON
iajs-2710	18	41	may	may	AUX
iajs-2710	18	42	only	only	ADV
iajs-2710	18	43	contain	contain	VERB
iajs-2710	18	44	a	a	DET
iajs-2710	18	45	part	part	NOUN
iajs-2710	18	46	of	of	ADP
iajs-2710	18	47	the	the	DET
iajs-2710	18	48	brain	brain	NOUN
iajs-2710	18	49	,	,	PUNCT
iajs-2710	18	50	is	be	AUX
iajs-2710	18	51	matched	match	VERB
iajs-2710	18	52	to	to	ADP
iajs-2710	18	53	the	the	DET
iajs-2710	18	54	existing	exist	VERB
iajs-2710	18	55	one	one	NUM
iajs-2710	18	56	,	,	PUNCT
iajs-2710	18	57	and	and	CCONJ
iajs-2710	18	58	the	the	DET
iajs-2710	18	59	mri	mri	NOUN
iajs-2710	18	60	is	be	AUX
iajs-2710	18	61	executed	execute	VERB
iajs-2710	18	62	again	again	ADV
iajs-2710	18	63	.	.	PUNCT
iajs-2710	19	1	this	this	DET
iajs-2710	19	2	multi	multi	ADJ
iajs-2710	19	3	-	-	ADJ
iajs-2710	19	4	view	view	ADJ
iajs-2710	19	5	approach	approach	NOUN
iajs-2710	19	6	ensures	ensure	VERB
iajs-2710	19	7	robust	robust	ADJ
iajs-2710	19	8	text	text	NOUN
iajs-2710	19	9	extraction	extraction	NOUN
iajs-2710	19	10	when	when	SCONJ
iajs-2710	19	11	occlusions	occlusion	NOUN
iajs-2710	19	12	or	or	CCONJ
iajs-2710	19	13	reflections	reflection	NOUN
iajs-2710	19	14	are	be	AUX
iajs-2710	19	15	present	present	ADJ
iajs-2710	19	16	'	'	PUNCT
iajs-2710	19	17	as	as	SCONJ
iajs-2710	19	18	mentioned	mention	VERB
iajs-2710	19	19	in	in	ADP
iajs-2710	19	20	[	[	X
iajs-2710	19	21	1	1	NUM
iajs-2710	19	22	]	]	PUNCT
iajs-2710	19	23	.	.	PUNCT
iajs-2710	20	1	the	the	DET
iajs-2710	20	2	final	final	ADJ
iajs-2710	20	3	output	output	NOUN
iajs-2710	20	4	of	of	ADP
iajs-2710	20	5	the	the	DET
iajs-2710	20	6	algorithm	algorithm	NOUN
iajs-2710	20	7	consists	consist	VERB
iajs-2710	20	8	of	of	ADP
iajs-2710	20	9	the	the	DET
iajs-2710	20	10	detected	detect	VERB
iajs-2710	20	11	brain	brain	NOUN
iajs-2710	20	12	type	type	NOUN
iajs-2710	20	13	,	,	PUNCT
iajs-2710	20	14	the	the	DET
iajs-2710	20	15	recognized	recognize	VERB
iajs-2710	20	16	text	text	NOUN
iajs-2710	20	17	,	,	PUNCT
iajs-2710	20	18	its	its	PRON
iajs-2710	20	19	position	position	NOUN
iajs-2710	20	20	on	on	ADP
iajs-2710	20	21	the	the	DET
iajs-2710	20	22	brain	brain	NOUN
iajs-2710	20	23	,	,	PUNCT
iajs-2710	20	24	as	as	ADV
iajs-2710	20	25	well	well	ADV
iajs-2710	20	26	as	as	ADP
iajs-2710	20	27	its	its	PRON
iajs-2710	20	28	confidence	confidence	NOUN
iajs-2710	20	29	.	.	PUNCT
iajs-2710	21	1	the	the	DET
iajs-2710	21	2	goal	goal	NOUN
iajs-2710	21	3	of	of	ADP
iajs-2710	21	4	the	the	DET
iajs-2710	21	5	practical	practical	ADJ
iajs-2710	21	6	task	task	NOUN
iajs-2710	21	7	is	be	AUX
iajs-2710	21	8	to	to	PART
iajs-2710	21	9	create	create	VERB
iajs-2710	21	10	a	a	DET
iajs-2710	21	11	prototype	prototype	NOUN
iajs-2710	21	12	of	of	ADP
iajs-2710	21	13	a	a	DET
iajs-2710	21	14	deep	deep	ADJ
iajs-2710	21	15	learning	learning	NOUN
iajs-2710	21	16	application	application	NOUN
iajs-2710	21	17	that	that	PRON
iajs-2710	21	18	allows	allow	VERB
iajs-2710	21	19	the	the	DET
iajs-2710	21	20	user	user	NOUN
iajs-2710	21	21	to	to	PART
iajs-2710	21	22	acquire	acquire	VERB
iajs-2710	21	23	images	image	NOUN
iajs-2710	21	24	,	,	PUNCT
iajs-2710	21	25	on	on	ADP
iajs-2710	21	26	which	which	PRON
iajs-2710	21	27	the	the	DET
iajs-2710	21	28	previously	previously	ADV
iajs-2710	21	29	listed	list	VERB
iajs-2710	21	30	steps	step	NOUN
iajs-2710	21	31	to	to	PART
iajs-2710	21	32	extract	extract	VERB
iajs-2710	21	33	the	the	DET
iajs-2710	21	34	content	content	NOUN
iajs-2710	21	35	are	be	AUX
iajs-2710	21	36	performed	perform	VERB
iajs-2710	21	37	.	.	PUNCT
iajs-2710	22	1	deep	deep	ADJ
iajs-2710	22	2	learning	learning	NOUN
iajs-2710	22	3	is	be	AUX
iajs-2710	22	4	a	a	DET
iajs-2710	22	5	machine	machine	NOUN
iajs-2710	22	6	learning	learning	NOUN
iajs-2710	22	7	method	method	NOUN
iajs-2710	22	8	that	that	PRON
iajs-2710	22	9	similarly	similarly	ADV
iajs-2710	22	10	solves	solve	VERB
iajs-2710	22	11	problems	problem	NOUN
iajs-2710	22	12	to	to	ADP
iajs-2710	22	13	how	how	SCONJ
iajs-2710	22	14	a	a	DET
iajs-2710	22	15	human	human	ADJ
iajs-2710	22	16	brain	brain	NOUN
iajs-2710	22	17	solves	solve	NOUN
iajs-2710	22	18	problems	problem	NOUN
iajs-2710	22	19	.	.	PUNCT
iajs-2710	23	1	this	this	DET
iajs-2710	23	2	past	past	ADJ
iajs-2710	23	3	decade	decade	NOUN
iajs-2710	23	4	it	it	PRON
iajs-2710	23	5	has	have	AUX
iajs-2710	23	6	become	become	VERB
iajs-2710	23	7	an	an	DET
iajs-2710	23	8	x	x	NOUN
iajs-2710	23	9	powerful	powerful	ADJ
iajs-2710	23	10	instrument	instrument	NOUN
iajs-2710	23	11	for	for	ADP
iajs-2710	23	12	solving	solve	VERB
iajs-2710	23	13	various	various	ADJ
iajs-2710	23	14	tasks	task	NOUN
iajs-2710	23	15	such	such	ADJ
iajs-2710	23	16	as	as	ADP
iajs-2710	23	17	speech	speech	NOUN
iajs-2710	23	18	recognition	recognition	NOUN
iajs-2710	23	19	,	,	PUNCT
iajs-2710	23	20	language	language	NOUN
iajs-2710	23	21	processing	processing	NOUN
iajs-2710	23	22	,	,	PUNCT
iajs-2710	23	23	and	and	CCONJ
iajs-2710	23	24	numerous	numerous	ADJ
iajs-2710	23	25	imaging	imaging	NOUN
iajs-2710	23	26	tasks	task	NOUN
iajs-2710	23	27	.	.	PUNCT
iajs-2710	24	1	it	it	PRON
iajs-2710	24	2	has	have	AUX
iajs-2710	24	3	also	also	ADV
iajs-2710	24	4	opened	open	VERB
iajs-2710	24	5	up	up	ADP
iajs-2710	24	6	many	many	ADJ
iajs-2710	24	7	possibilities	possibility	NOUN
iajs-2710	24	8	for	for	ADP
iajs-2710	24	9	more	more	ADV
iajs-2710	24	10	accurate	accurate	ADJ
iajs-2710	24	11	tools	tool	NOUN
iajs-2710	24	12	x	x	PUNCT
iajs-2710	24	13	such	such	ADJ
iajs-2710	24	14	as	as	ADP
iajs-2710	24	15	prediction	prediction	NOUN
iajs-2710	24	16	,	,	PUNCT
iajs-2710	24	17	segmentation	segmentation	NOUN
iajs-2710	24	18	,	,	PUNCT
iajs-2710	24	19	and	and	CCONJ
iajs-2710	24	20	analysis	analysis	NOUN
iajs-2710	24	21	of	of	ADP
iajs-2710	24	22	medical	medical	ADJ
iajs-2710	24	23	images	image	NOUN
iajs-2710	24	24	[	[	X
iajs-2710	24	25	2	2	NUM
iajs-2710	24	26	]	]	PUNCT
iajs-2710	24	27	.	.	PUNCT
iajs-2710	25	1	deep	deep	ADJ
iajs-2710	25	2	learning	learning	NOUN
iajs-2710	25	3	methods	method	NOUN
iajs-2710	25	4	are	be	AUX
iajs-2710	25	5	also	also	ADV
iajs-2710	25	6	relatively	relatively	ADV
iajs-2710	25	7	easy	easy	ADJ
iajs-2710	25	8	to	to	PART
iajs-2710	25	9	deploy	deploy	VERB
iajs-2710	25	10	,	,	PUNCT
iajs-2710	25	11	and	and	CCONJ
iajs-2710	25	12	a	a	DET
iajs-2710	25	13	deep	deep	ADJ
iajs-2710	25	14	learning	learning	NOUN
iajs-2710	25	15	architecture	architecture	NOUN
iajs-2710	25	16	that	that	PRON
iajs-2710	25	17	is	be	AUX
iajs-2710	25	18	built	build	VERB
iajs-2710	25	19	for	for	ADP
iajs-2710	25	20	one	one	NUM
iajs-2710	25	21	task	task	NOUN
iajs-2710	25	22	can	can	AUX
iajs-2710	25	23	be	be	AUX
iajs-2710	25	24	trained	train	VERB
iajs-2710	25	25	to	to	PART
iajs-2710	25	26	work	work	VERB
iajs-2710	25	27	,	,	PUNCT
iajs-2710	25	28	as	as	SCONJ
iajs-2710	25	29	we	we	PRON
iajs-2710	25	30	show	show	VERB
iajs-2710	25	31	in	in	ADP
iajs-2710	25	32	table	table	NOUN
iajs-2710	25	33	1	1	NUM
iajs-2710	25	34	.	.	PUNCT
iajs-2710	25	35	table	table	NOUN
iajs-2710	25	36	1	1	NUM
iajs-2710	25	37	:	:	PUNCT
iajs-2710	25	38	table	table	NOUN
iajs-2710	25	39	for	for	ADP
iajs-2710	25	40	predicting	predict	VERB
iajs-2710	25	41	the	the	DET
iajs-2710	25	42	training	training	NOUN
iajs-2710	25	43	process	process	NOUN
iajs-2710	25	44	for	for	ADP
iajs-2710	25	45	the	the	DET
iajs-2710	25	46	architecture	architecture	NOUN
iajs-2710	25	47	.	.	PUNCT
iajs-2710	26	1	batch	batch	NOUN
iajs-2710	26	2	training	training	NOUN
iajs-2710	26	3	yes	yes	NOUN
iajs-2710	26	4	batch	batch	NOUN
iajs-2710	26	5	normalization	normalization	NOUN
iajs-2710	26	6	scalable	scalable	ADJ
iajs-2710	26	7	batch	batch	NOUN
iajs-2710	26	8	size	size	NOUN
iajs-2710	26	9	moderate	moderate	ADJ
iajs-2710	26	10	deep	deep	ADJ
iajs-2710	26	11	learning	learning	NOUN
iajs-2710	26	12	will	will	AUX
iajs-2710	26	13	learn	learn	VERB
iajs-2710	26	14	how	how	SCONJ
iajs-2710	26	15	to	to	PART
iajs-2710	26	16	determine	determine	VERB
iajs-2710	26	17	the	the	DET
iajs-2710	26	18	brain	brain	NOUN
iajs-2710	26	19	masks	mask	NOUN
iajs-2710	26	20	based	base	VERB
iajs-2710	26	21	on	on	ADP
iajs-2710	26	22	a	a	DET
iajs-2710	26	23	training	training	NOUN
iajs-2710	26	24	set	set	NOUN
iajs-2710	26	25	of	of	ADP
iajs-2710	26	26	already	already	ADV
iajs-2710	26	27	segmented	segment	VERB
iajs-2710	26	28	brain	brain	NOUN
iajs-2710	26	29	masks	mask	NOUN
iajs-2710	26	30	with	with	ADP
iajs-2710	26	31	little	little	ADJ
iajs-2710	26	32	tuning	tuning	NOUN
iajs-2710	26	33	required	require	VERB
iajs-2710	26	34	.	.	PUNCT
iajs-2710	27	1	ren	ren	NOUN
iajs-2710	27	2	et	et	PROPN
iajs-2710	27	3	al	al	PROPN
iajs-2710	27	4	.	.	PUNCT
iajs-2710	28	1	[	[	X
iajs-2710	28	2	3	3	X
iajs-2710	28	3	]	]	PUNCT
iajs-2710	28	4	introduce	introduce	VERB
iajs-2710	28	5	a	a	DET
iajs-2710	28	6	method	method	NOUN
iajs-2710	28	7	for	for	ADP
iajs-2710	28	8	brain	brain	NOUN
iajs-2710	28	9	stripping	stripping	NOUN
iajs-2710	28	10	that	that	PRON
iajs-2710	28	11	uses	use	VERB
iajs-2710	28	12	a	a	DET
iajs-2710	28	13	fully	fully	ADV
iajs-2710	28	14	convolutional	convolutional	ADJ
iajs-2710	28	15	neural	neural	ADJ
iajs-2710	28	16	network	network	NOUN
iajs-2710	28	17	.	.	PUNCT
iajs-2710	29	1	their	their	PRON
iajs-2710	29	2	method	method	NOUN
iajs-2710	29	3	is	be	AUX
iajs-2710	29	4	compared	compare	VERB
iajs-2710	29	5	with	with	ADP
iajs-2710	29	6	six	six	NUM
iajs-2710	29	7	existing	exist	VERB
iajs-2710	29	8	brain	brain	NOUN
iajs-2710	29	9	stripping	strip	VERB
iajs-2710	29	10	methods	method	NOUN
iajs-2710	29	11	on	on	ADP
iajs-2710	29	12	three	three	NUM
iajs-2710	29	13	different	different	ADJ
iajs-2710	29	14	data	data	NOUN
iajs-2710	29	15	sets	set	NOUN
iajs-2710	29	16	.	.	PUNCT
iajs-2710	30	1	it	it	PRON
iajs-2710	30	2	performs	perform	VERB
iajs-2710	30	3	better	well	ADV
iajs-2710	30	4	than	than	ADP
iajs-2710	30	5	all	all	PRON
iajs-2710	30	6	of	of	ADP
iajs-2710	30	7	the	the	DET
iajs-2710	30	8	conventional	conventional	ADJ
iajs-2710	30	9	methods	method	NOUN
iajs-2710	30	10	in	in	ADP
iajs-2710	30	11	some	some	DET
iajs-2710	30	12	metrics	metric	NOUN
iajs-2710	30	13	also	also	ADV
iajs-2710	30	14	says	say	VERB
iajs-2710	30	15	that	that	SCONJ
iajs-2710	30	16	its	its	PRON
iajs-2710	30	17	method	method	NOUN
iajs-2710	30	18	should	should	AUX
iajs-2710	30	19	work	work	VERB
iajs-2710	30	20	well	well	ADV
iajs-2710	30	21	on	on	ADP
iajs-2710	30	22	other	other	ADJ
iajs-2710	30	23	medical	medical	ADJ
iajs-2710	30	24	image	image	NOUN
iajs-2710	30	25	modalities	modality	NOUN
iajs-2710	30	26	in	in	ADP
iajs-2710	30	27	contrast	contrast	NOUN
iajs-2710	30	28	to	to	ADP
iajs-2710	30	29	the	the	DET
iajs-2710	30	30	existing	exist	VERB
iajs-2710	30	31	methods	method	NOUN
iajs-2710	30	32	.	.	PUNCT
iajs-2710	31	1	all	all	PRON
iajs-2710	31	2	of	of	ADP
iajs-2710	31	3	the	the	DET
iajs-2710	31	4	patients	patient	NOUN
iajs-2710	31	5	in	in	ADP
iajs-2710	31	6	the	the	DET
iajs-2710	31	7	data	datum	NOUN
iajs-2710	31	8	set	set	VERB
iajs-2710	31	9	have	have	VERB
iajs-2710	31	10	brain	brain	NOUN
iajs-2710	31	11	tumors	tumor	NOUN
iajs-2710	31	12	.	.	PUNCT
iajs-2710	32	1	the	the	DET
iajs-2710	32	2	existing	exist	VERB
iajs-2710	32	3	solutions	solution	NOUN
iajs-2710	32	4	that	that	PRON
iajs-2710	32	5	are	be	AUX
iajs-2710	32	6	not	not	PART
iajs-2710	32	7	based	base	VERB
iajs-2710	32	8	on	on	ADP
iajs-2710	32	9	deep	deep	ADJ
iajs-2710	32	10	learning	learning	NOUN
iajs-2710	32	11	do	do	AUX
iajs-2710	32	12	not	not	PART
iajs-2710	32	13	handle	handle	VERB
iajs-2710	32	14	this	this	DET
iajs-2710	32	15	well	well	NOUN
iajs-2710	32	16	.	.	PUNCT
iajs-2710	33	1	therefore	therefore	ADV
iajs-2710	33	2	,	,	PUNCT
iajs-2710	33	3	it	it	PRON
iajs-2710	33	4	would	would	AUX
iajs-2710	33	5	be	be	AUX
iajs-2710	33	6	interesting	interesting	ADJ
iajs-2710	33	7	to	to	PART
iajs-2710	33	8	see	see	VERB
iajs-2710	33	9	if	if	SCONJ
iajs-2710	33	10	deep	deep	ADJ
iajs-2710	33	11	learning	learning	NOUN
iajs-2710	33	12	can	can	AUX
iajs-2710	33	13	be	be	AUX
iajs-2710	33	14	used	use	VERB
iajs-2710	33	15	to	to	PART
iajs-2710	33	16	tackle	tackle	VERB
iajs-2710	33	17	this	this	DET
iajs-2710	33	18	problem	problem	NOUN
iajs-2710	33	19	.	.	PUNCT
iajs-2710	34	1	in	in	ADP
iajs-2710	34	2	[	[	X
iajs-2710	34	3	4	4	X
iajs-2710	34	4	]	]	PUNCT
iajs-2710	34	5	they	they	PRON
iajs-2710	34	6	showed	show	VERB
iajs-2710	34	7	that	that	SCONJ
iajs-2710	34	8	their	their	PRON
iajs-2710	34	9	deep	deep	ADJ
iajs-2710	34	10	learning	learning	NOUN
iajs-2710	34	11	provided	provide	VERB
iajs-2710	34	12	method	method	NOUN
iajs-2710	34	13	was	be	AUX
iajs-2710	34	14	better	well	ADJ
iajs-2710	34	15	compared	compare	VERB
iajs-2710	34	16	to	to	ADP
iajs-2710	34	17	existing	exist	VERB
iajs-2710	34	18	brain	brain	NOUN
iajs-2710	34	19	stripping	strip	VERB
iajs-2710	34	20	methods	method	NOUN
iajs-2710	34	21	at	at	ADP
iajs-2710	34	22	handling	handle	VERB
iajs-2710	34	23	images	image	NOUN
iajs-2710	34	24	of	of	ADP
iajs-2710	34	25	patients	patient	NOUN
iajs-2710	34	26	with	with	ADP
iajs-2710	34	27	tumors	tumor	NOUN
iajs-2710	34	28	in	in	ADP
iajs-2710	34	29	their	their	PRON
iajs-2710	34	30	data	datum	NOUN
iajs-2710	34	31	set	set	VERB
iajs-2710	34	32	consequently	consequently	ADV
iajs-2710	34	33	,	,	PUNCT
iajs-2710	34	34	this	this	DET
iajs-2710	34	35	research	research	NOUN
iajs-2710	34	36	aims	aim	VERB
iajs-2710	34	37	to	to	PART
iajs-2710	34	38	explore	explore	VERB
iajs-2710	34	39	if	if	SCONJ
iajs-2710	34	40	deep	deep	ADJ
iajs-2710	34	41	learning	learning	NOUN
iajs-2710	34	42	methods	method	NOUN
iajs-2710	34	43	can	can	AUX
iajs-2710	34	44	handle	handle	VERB
iajs-2710	34	45	the	the	DET
iajs-2710	34	46	tumor	tumor	NOUN
iajs-2710	34	47	data	datum	NOUN
iajs-2710	34	48	from	from	ADP
iajs-2710	34	49	the	the	DET
iajs-2710	34	50	data	datum	NOUN
iajs-2710	34	51	set	set	VERB
iajs-2710	34	52	adequately	adequately	ADV
iajs-2710	34	53	.	.	PUNCT
iajs-2710	35	1	there	there	PRON
iajs-2710	35	2	are	be	VERB
iajs-2710	35	3	varying	vary	VERB
iajs-2710	35	4	amounts	amount	NOUN
iajs-2710	35	5	of	of	ADP
iajs-2710	35	6	data	datum	NOUN
iajs-2710	35	7	in	in	ADP
iajs-2710	35	8	the	the	DET
iajs-2710	35	9	three	three	NUM
iajs-2710	35	10	data	datum	NOUN
iajs-2710	35	11	sets	set	NOUN
iajs-2710	35	12	used	use	VERB
iajs-2710	35	13	in	in	ADP
iajs-2710	35	14	this	this	DET
iajs-2710	35	15	paper	paper	NOUN
iajs-2710	35	16	.	.	PUNCT
iajs-2710	36	1	there	there	PRON
iajs-2710	36	2	are	be	VERB
iajs-2710	36	3	many	many	ADV
iajs-2710	36	4	more	more	ADJ
iajs-2710	36	5	mri	mri	NOUN
iajs-2710	36	6	images	image	NOUN
iajs-2710	36	7	in	in	ADP
iajs-2710	36	8	the	the	DET
iajs-2710	36	9	data	datum	NOUN
iajs-2710	36	10	from	from	ADP
iajs-2710	36	11	the	the	DET
iajs-2710	36	12	hospital	hospital	NOUN
iajs-2710	36	13	compared	compare	VERB
iajs-2710	36	14	to	to	ADP
iajs-2710	36	15	the	the	DET
iajs-2710	36	16	other	other	ADJ
iajs-2710	36	17	two	two	NUM
iajs-2710	36	18	data	data	NOUN
iajs-2710	36	19	sets	set	NOUN
iajs-2710	36	20	.	.	PUNCT
iajs-2710	37	1	this	this	DET
iajs-2710	37	2	unbalanced	unbalanced	ADJ
iajs-2710	37	3	composition	composition	NOUN
iajs-2710	37	4	of	of	ADP
iajs-2710	37	5	the	the	DET
iajs-2710	37	6	data	data	NOUN
iajs-2710	37	7	sets	set	NOUN
iajs-2710	37	8	can	can	AUX
iajs-2710	37	9	cause	cause	VERB
iajs-2710	37	10	problems	problem	NOUN
iajs-2710	37	11	for	for	ADP
iajs-2710	37	12	deep	deep	ADJ
iajs-2710	37	13	learning	learning	NOUN
iajs-2710	37	14	methods	method	NOUN
iajs-2710	37	15	.	.	PUNCT
iajs-2710	38	1	it	it	PRON
iajs-2710	38	2	can	can	AUX
iajs-2710	38	3	cause	cause	VERB
iajs-2710	38	4	problems	problem	NOUN
iajs-2710	38	5	such	such	ADJ
iajs-2710	38	6	as	as	ADP
iajs-2710	38	7	the	the	DET
iajs-2710	38	8	deep	deep	ADJ
iajs-2710	38	9	learning	learning	NOUN
iajs-2710	38	10	methods	method	NOUN
iajs-2710	38	11	being	be	AUX
iajs-2710	38	12	ibn	ibn	PROPN
iajs-2710	38	13	al	al	PROPN
iajs-2710	38	14	-	-	PUNCT
iajs-2710	38	15	haitham	haitham	PROPN
iajs-2710	38	16	jour	jour	X
iajs-2710	38	17	.	.	PROPN
iajs-2710	39	1	for	for	ADP
iajs-2710	39	2	pure	pure	ADJ
iajs-2710	39	3	&	&	CCONJ
iajs-2710	39	4	appl	appl	PROPN
iajs-2710	39	5	.	.	PUNCT
iajs-2710	40	1	sci	sci	PROPN
iajs-2710	40	2	.	.	PROPN
iajs-2710	41	1	34(4)2021	34(4)2021	NUM
iajs-2710	41	2	132	132	NUM
iajs-2710	41	3	very	very	ADV
iajs-2710	41	4	good	good	ADJ
iajs-2710	41	5	at	at	ADP
iajs-2710	41	6	predicting	predict	VERB
iajs-2710	41	7	data	datum	NOUN
iajs-2710	41	8	from	from	ADP
iajs-2710	41	9	the	the	DET
iajs-2710	41	10	most	most	ADV
iajs-2710	41	11	extensive	extensive	ADJ
iajs-2710	41	12	data	datum	NOUN
iajs-2710	41	13	set	set	VERB
iajs-2710	41	14	but	but	CCONJ
iajs-2710	41	15	poorer	poor	ADJ
iajs-2710	41	16	on	on	ADP
iajs-2710	41	17	data	datum	NOUN
iajs-2710	41	18	sets	set	NOUN
iajs-2710	41	19	with	with	ADP
iajs-2710	41	20	the	the	DET
iajs-2710	41	21	images	image	NOUN
iajs-2710	41	22	.	.	PUNCT
iajs-2710	42	1	magnetic	magnetic	ADJ
iajs-2710	42	2	resonance	resonance	NOUN
iajs-2710	42	3	imaging	imaging	NOUN
iajs-2710	42	4	(	(	PUNCT
iajs-2710	42	5	mri	mri	NOUN
iajs-2710	42	6	)	)	PUNCT
iajs-2710	42	7	is	be	AUX
iajs-2710	42	8	an	an	DET
iajs-2710	42	9	imaging	imaging	NOUN
iajs-2710	42	10	technique	technique	NOUN
iajs-2710	42	11	that	that	PRON
iajs-2710	42	12	is	be	AUX
iajs-2710	42	13	regularly	regularly	ADV
iajs-2710	42	14	used	use	VERB
iajs-2710	42	15	for	for	ADP
iajs-2710	42	16	taking	take	VERB
iajs-2710	42	17	images	image	NOUN
iajs-2710	42	18	used	use	VERB
iajs-2710	42	19	for	for	ADP
iajs-2710	42	20	medical	medical	ADJ
iajs-2710	42	21	analysis	analysis	NOUN
iajs-2710	42	22	.	.	PUNCT
iajs-2710	43	1	the	the	DET
iajs-2710	43	2	images	image	NOUN
iajs-2710	43	3	are	be	AUX
iajs-2710	43	4	obtained	obtain	VERB
iajs-2710	43	5	by	by	ADP
iajs-2710	43	6	using	use	VERB
iajs-2710	43	7	a	a	DET
iajs-2710	43	8	strong	strong	ADJ
iajs-2710	43	9	magnetic	magnetic	ADJ
iajs-2710	43	10	field	field	NOUN
iajs-2710	43	11	to	to	PART
iajs-2710	43	12	align	align	VERB
iajs-2710	43	13	hydrogen	hydrogen	NOUN
iajs-2710	43	14	atoms	atom	NOUN
iajs-2710	43	15	inside	inside	ADP
iajs-2710	43	16	the	the	DET
iajs-2710	43	17	body	body	NOUN
iajs-2710	43	18	.	.	PUNCT
iajs-2710	44	1	radiofrequency	radiofrequency	NOUN
iajs-2710	44	2	energy	energy	NOUN
iajs-2710	44	3	from	from	ADP
iajs-2710	44	4	the	the	DET
iajs-2710	44	5	machine	machine	NOUN
iajs-2710	44	6	is	be	AUX
iajs-2710	44	7	then	then	ADV
iajs-2710	44	8	used	use	VERB
iajs-2710	44	9	to	to	PART
iajs-2710	44	10	excite	excite	VERB
iajs-2710	44	11	the	the	DET
iajs-2710	44	12	hydrogen	hydrogen	NOUN
iajs-2710	44	13	atoms	atom	NOUN
iajs-2710	44	14	[	[	X
iajs-2710	44	15	5	5	NUM
iajs-2710	44	16	]	]	PUNCT
iajs-2710	44	17	.	.	PUNCT
iajs-2710	45	1	after	after	SCONJ
iajs-2710	45	2	the	the	DET
iajs-2710	45	3	machine	machine	NOUN
iajs-2710	45	4	stops	stop	VERB
iajs-2710	45	5	emitting	emit	VERB
iajs-2710	45	6	radiofrequency	radiofrequency	NOUN
iajs-2710	45	7	energy	energy	NOUN
iajs-2710	45	8	,	,	PUNCT
iajs-2710	45	9	the	the	DET
iajs-2710	45	10	hydrogen	hydrogen	NOUN
iajs-2710	45	11	atoms	atom	NOUN
iajs-2710	45	12	return	return	VERB
iajs-2710	45	13	to	to	ADP
iajs-2710	45	14	their	their	PRON
iajs-2710	45	15	resting	rest	VERB
iajs-2710	45	16	state	state	NOUN
iajs-2710	45	17	,	,	PUNCT
iajs-2710	45	18	causing	cause	VERB
iajs-2710	45	19	the	the	DET
iajs-2710	45	20	atoms	atom	NOUN
iajs-2710	45	21	to	to	PART
iajs-2710	45	22	emit	emit	VERB
iajs-2710	45	23	energy	energy	NOUN
iajs-2710	45	24	.	.	PUNCT
iajs-2710	46	1	the	the	DET
iajs-2710	46	2	energy	energy	NOUN
iajs-2710	46	3	is	be	AUX
iajs-2710	46	4	then	then	ADV
iajs-2710	46	5	read	read	VERB
iajs-2710	46	6	by	by	ADP
iajs-2710	46	7	antennas	antenna	NOUN
iajs-2710	46	8	inside	inside	ADP
iajs-2710	46	9	the	the	DET
iajs-2710	46	10	mri	mri	NOUN
iajs-2710	46	11	machine	machine	NOUN
iajs-2710	46	12	.	.	PUNCT
iajs-2710	47	1	as	as	SCONJ
iajs-2710	47	2	we	we	PRON
iajs-2710	47	3	show	show	VERB
iajs-2710	47	4	in	in	ADP
iajs-2710	47	5	figure	figure	NOUN
iajs-2710	47	6	1	1	NUM
iajs-2710	47	7	,	,	PUNCT
iajs-2710	47	8	we	we	PRON
iajs-2710	47	9	also	also	ADV
iajs-2710	47	10	show	show	VERB
iajs-2710	47	11	an	an	DET
iajs-2710	47	12	example	example	NOUN
iajs-2710	47	13	of	of	ADP
iajs-2710	47	14	a	a	DET
iajs-2710	47	15	simple	simple	ADJ
iajs-2710	47	16	neural	neural	ADJ
iajs-2710	47	17	network	network	NOUN
iajs-2710	47	18	with	with	ADP
iajs-2710	47	19	three	three	NUM
iajs-2710	47	20	layers	layer	NOUN
iajs-2710	47	21	in	in	ADP
iajs-2710	47	22	figure	figure	NOUN
iajs-2710	47	23	2	2	NUM
iajs-2710	47	24	.	.	PUNCT
iajs-2710	47	25	figure	figure	NOUN
iajs-2710	47	26	1	1	NUM
iajs-2710	47	27	.	.	PUNCT
iajs-2710	48	1	blue	blue	ADJ
iajs-2710	48	2	marks	mark	NOUN
iajs-2710	48	3	where	where	SCONJ
iajs-2710	48	4	the	the	DET
iajs-2710	48	5	brain	brain	NOUN
iajs-2710	48	6	is	be	AUX
iajs-2710	48	7	in	in	ADP
iajs-2710	48	8	the	the	DET
iajs-2710	48	9	mri	mri	NOUN
iajs-2710	48	10	scan	scan	NOUN
iajs-2710	48	11	figure	figure	NOUN
iajs-2710	48	12	2	2	NUM
iajs-2710	48	13	.	.	NOUN
iajs-2710	48	14	example	example	NOUN
iajs-2710	48	15	of	of	ADP
iajs-2710	48	16	a	a	DET
iajs-2710	48	17	simple	simple	ADJ
iajs-2710	48	18	neural	neural	ADJ
iajs-2710	48	19	network	network	NOUN
iajs-2710	48	20	with	with	ADP
iajs-2710	48	21	three	three	NUM
iajs-2710	48	22	layers	layer	NOUN
iajs-2710	48	23	.	.	PUNCT
iajs-2710	49	1	1.1.purpose	1.1.purpose	NUM
iajs-2710	49	2	of	of	ADP
iajs-2710	49	3	study	study	VERB
iajs-2710	49	4	the	the	DET
iajs-2710	49	5	overall	overall	ADJ
iajs-2710	49	6	goal	goal	NOUN
iajs-2710	49	7	for	for	ADP
iajs-2710	49	8	this	this	DET
iajs-2710	49	9	study	study	NOUN
iajs-2710	49	10	will	will	AUX
iajs-2710	49	11	be	be	AUX
iajs-2710	49	12	to	to	PART
iajs-2710	49	13	explore	explore	VERB
iajs-2710	49	14	further	further	ADJ
iajs-2710	49	15	deep	deep	ADJ
iajs-2710	49	16	learning	learning	NOUN
iajs-2710	49	17	applied	apply	VERB
iajs-2710	49	18	to	to	ADP
iajs-2710	49	19	mri	mri	NOUN
iajs-2710	49	20	of	of	ADP
iajs-2710	49	21	brain	brain	NOUN
iajs-2710	49	22	stripping	strip	VERB
iajs-2710	49	23	,	,	PUNCT
iajs-2710	49	24	especially	especially	ADV
iajs-2710	49	25	on	on	ADP
iajs-2710	49	26	data	datum	NOUN
iajs-2710	49	27	from	from	ADP
iajs-2710	49	28	the	the	DET
iajs-2710	49	29	hospitals	hospital	NOUN
iajs-2710	49	30	.	.	PUNCT
iajs-2710	50	1	another	another	DET
iajs-2710	50	2	goal	goal	NOUN
iajs-2710	50	3	for	for	ADP
iajs-2710	50	4	this	this	DET
iajs-2710	50	5	paper	paper	NOUN
iajs-2710	50	6	will	will	AUX
iajs-2710	50	7	be	be	AUX
iajs-2710	50	8	to	to	PART
iajs-2710	50	9	examine	examine	VERB
iajs-2710	50	10	how	how	SCONJ
iajs-2710	50	11	different	different	ADJ
iajs-2710	50	12	hardware	hardware	NOUN
iajs-2710	50	13	configurations	configuration	NOUN
iajs-2710	50	14	impact	impact	VERB
iajs-2710	50	15	the	the	DET
iajs-2710	50	16	training	training	NOUN
iajs-2710	50	17	time	time	NOUN
iajs-2710	50	18	of	of	ADP
iajs-2710	50	19	different	different	ADJ
iajs-2710	50	20	cnns	cnn	NOUN
iajs-2710	51	1	[	[	X
iajs-2710	51	2	6	6	NUM
iajs-2710	51	3	]	]	PUNCT
iajs-2710	51	4	.	.	PUNCT
iajs-2710	52	1	also	also	ADV
iajs-2710	52	2	,	,	PUNCT
iajs-2710	52	3	this	this	DET
iajs-2710	52	4	paper	paper	NOUN
iajs-2710	52	5	will	will	AUX
iajs-2710	52	6	test	test	VERB
iajs-2710	52	7	if	if	SCONJ
iajs-2710	52	8	these	these	DET
iajs-2710	52	9	deep	deep	ADJ
iajs-2710	52	10	learning	learning	NOUN
iajs-2710	52	11	methods	method	NOUN
iajs-2710	52	12	can	can	AUX
iajs-2710	52	13	be	be	AUX
iajs-2710	52	14	used	use	VERB
iajs-2710	52	15	to	to	PART
iajs-2710	52	16	do	do	VERB
iajs-2710	52	17	segmentation	segmentation	NOUN
iajs-2710	52	18	.	.	PUNCT
iajs-2710	53	1	based	base	VERB
iajs-2710	53	2	on	on	ADP
iajs-2710	53	3	the	the	DET
iajs-2710	53	4	problem	problem	NOUN
iajs-2710	53	5	description	description	NOUN
iajs-2710	53	6	in	in	ADP
iajs-2710	53	7	the	the	DET
iajs-2710	53	8	previous	previous	ADJ
iajs-2710	53	9	section	section	NOUN
iajs-2710	53	10	and	and	CCONJ
iajs-2710	53	11	the	the	DET
iajs-2710	53	12	goals	goal	NOUN
iajs-2710	53	13	,	,	PUNCT
iajs-2710	53	14	the	the	DET
iajs-2710	53	15	following	follow	VERB
iajs-2710	53	16	research	research	NOUN
iajs-2710	53	17	question	question	NOUN
iajs-2710	53	18	(	(	PUNCT
iajs-2710	53	19	rq	rq	INTJ
iajs-2710	53	20	)	)	PUNCT
iajs-2710	53	21	have	have	AUX
iajs-2710	53	22	been	be	AUX
iajs-2710	53	23	defined	define	VERB
iajs-2710	53	24	and	and	CCONJ
iajs-2710	53	25	will	will	AUX
iajs-2710	53	26	be	be	AUX
iajs-2710	53	27	addressed	address	VERB
iajs-2710	53	28	in	in	ADP
iajs-2710	53	29	this	this	DET
iajs-2710	53	30	paper	paper	NOUN
iajs-2710	53	31	:	:	PUNCT
iajs-2710	53	32	q	q	NOUN
iajs-2710	54	1	1	1	X
iajs-2710	54	2	.	.	PUNCT
iajs-2710	55	1	how	how	SCONJ
iajs-2710	55	2	important	important	ADJ
iajs-2710	55	3	are	be	AUX
iajs-2710	55	4	different	different	ADJ
iajs-2710	55	5	deep	deep	ADJ
iajs-2710	55	6	learning	learning	NOUN
iajs-2710	55	7	architectures	architecture	NOUN
iajs-2710	55	8	to	to	PART
iajs-2710	55	9	train	train	VERB
iajs-2710	55	10	on	on	ADP
iajs-2710	55	11	data	datum	NOUN
iajs-2710	55	12	from	from	ADP
iajs-2710	55	13	the	the	DET
iajs-2710	55	14	same	same	ADJ
iajs-2710	55	15	source	source	NOUN
iajs-2710	55	16	before	before	ADP
iajs-2710	55	17	performing	perform	VERB
iajs-2710	55	18	brain	brain	NOUN
iajs-2710	55	19	stripping	strip	VERB
iajs-2710	55	20	?	?	PUNCT
iajs-2710	55	21	q	q	NOUN
iajs-2710	56	1	2	2	NUM
iajs-2710	56	2	.	.	X
iajs-2710	56	3	how	how	SCONJ
iajs-2710	56	4	important	important	ADJ
iajs-2710	56	5	is	be	AUX
iajs-2710	56	6	the	the	DET
iajs-2710	56	7	balance	balance	NOUN
iajs-2710	56	8	between	between	ADP
iajs-2710	56	9	the	the	DET
iajs-2710	56	10	amount	amount	NOUN
iajs-2710	56	11	of	of	ADP
iajs-2710	56	12	data	datum	NOUN
iajs-2710	56	13	in	in	ADP
iajs-2710	56	14	each	each	DET
iajs-2710	56	15	data	datum	NOUN
iajs-2710	56	16	set	set	VERB
iajs-2710	56	17	for	for	ADP
iajs-2710	56	18	deep	deep	ADJ
iajs-2710	56	19	learning	learning	NOUN
iajs-2710	56	20	architectures	architecture	NOUN
iajs-2710	56	21	when	when	SCONJ
iajs-2710	56	22	doing	do	VERB
iajs-2710	56	23	brain	brain	NOUN
iajs-2710	56	24	stripping	strip	VERB
iajs-2710	56	25	?	?	PUNCT
iajs-2710	56	26	q	q	NOUN
iajs-2710	57	1	3	3	X
iajs-2710	57	2	.	.	PUNCT
iajs-2710	57	3	is	be	AUX
iajs-2710	57	4	it	it	PRON
iajs-2710	57	5	important	important	ADJ
iajs-2710	57	6	for	for	SCONJ
iajs-2710	57	7	deep	deep	ADJ
iajs-2710	57	8	learning	learning	NOUN
iajs-2710	57	9	architectures	architecture	NOUN
iajs-2710	57	10	to	to	PART
iajs-2710	57	11	have	have	VERB
iajs-2710	57	12	mri	mri	NOUN
iajs-2710	57	13	scans	scan	NOUN
iajs-2710	57	14	with	with	ADP
iajs-2710	57	15	the	the	DET
iajs-2710	57	16	same	same	ADJ
iajs-2710	57	17	voxel	voxel	PROPN
iajs-2710	57	18	ibn	ibn	PROPN
iajs-2710	57	19	al	al	PROPN
iajs-2710	57	20	-	-	PUNCT
iajs-2710	57	21	haitham	haitham	PROPN
iajs-2710	57	22	jour	jour	X
iajs-2710	57	23	.	.	PROPN
iajs-2710	58	1	for	for	ADP
iajs-2710	58	2	pure	pure	ADJ
iajs-2710	58	3	&	&	CCONJ
iajs-2710	58	4	appl	appl	PROPN
iajs-2710	58	5	.	.	PUNCT
iajs-2710	59	1	sci	sci	PROPN
iajs-2710	59	2	.	.	PROPN
iajs-2710	60	1	34(4)2021	34(4)2021	NUM
iajs-2710	60	2	133	133	NUM
iajs-2710	60	3	size	size	NOUN
iajs-2710	60	4	when	when	SCONJ
iajs-2710	60	5	performing	perform	VERB
iajs-2710	60	6	brain	brain	NOUN
iajs-2710	60	7	stripping	strip	VERB
iajs-2710	60	8	?	?	PUNCT
iajs-2710	61	1	σ(z	σ(z	NOUN
iajs-2710	61	2	)	)	PUNCT
iajs-2710	62	1	=	=	SYM
iajs-2710	62	2	max	max	X
iajs-2710	62	3	(	(	PUNCT
iajs-2710	62	4	0	0	NUM
iajs-2710	62	5	,	,	PUNCT
iajs-2710	62	6	z	z	NOUN
iajs-2710	62	7	)	)	PUNCT
iajs-2710	62	8	(	(	PUNCT
iajs-2710	62	9	1	1	X
iajs-2710	62	10	)	)	PUNCT
iajs-2710	62	11	with	with	ADP
iajs-2710	62	12	equation	equation	NOUN
iajs-2710	62	13	(	(	PUNCT
iajs-2710	62	14	1	1	X
iajs-2710	62	15	)	)	PUNCT
iajs-2710	62	16	the	the	DET
iajs-2710	62	17	neuron	neuron	NOUN
iajs-2710	62	18	outputs	output	VERB
iajs-2710	62	19	its	its	PRON
iajs-2710	62	20	computed	computed	ADJ
iajs-2710	62	21	value	value	NOUN
iajs-2710	62	22	if	if	SCONJ
iajs-2710	62	23	it	it	PRON
iajs-2710	62	24	is	be	AUX
iajs-2710	62	25	over	over	ADP
iajs-2710	62	26	zero	zero	NUM
iajs-2710	62	27	;	;	PUNCT
iajs-2710	62	28	otherwise	otherwise	ADV
iajs-2710	62	29	,	,	PUNCT
iajs-2710	62	30	it	it	PRON
iajs-2710	62	31	outputs	output	VERB
iajs-2710	62	32	zero	zero	NUM
iajs-2710	62	33	.	.	PUNCT
iajs-2710	63	1	a	a	DET
iajs-2710	63	2	good	good	ADJ
iajs-2710	63	3	and	and	CCONJ
iajs-2710	63	4	non	non	ADJ
iajs-2710	63	5	-	-	ADJ
iajs-2710	63	6	biased	biased	ADJ
iajs-2710	63	7	segmentation	segmentation	NOUN
iajs-2710	63	8	method	method	NOUN
iajs-2710	63	9	for	for	ADP
iajs-2710	63	10	brain	brain	NOUN
iajs-2710	63	11	stripping	strip	VERB
iajs-2710	63	12	is	be	AUX
iajs-2710	63	13	,	,	PUNCT
iajs-2710	63	14	therefor	therefor	ADV
iajs-2710	63	15	,	,	PUNCT
iajs-2710	63	16	a	a	DET
iajs-2710	63	17	very	very	ADV
iajs-2710	63	18	valuable	valuable	ADJ
iajs-2710	63	19	tool	tool	NOUN
iajs-2710	63	20	.	.	PUNCT
iajs-2710	64	1	a	a	DET
iajs-2710	64	2	neural	neural	ADJ
iajs-2710	64	3	network	network	NOUN
iajs-2710	64	4	is	be	AUX
iajs-2710	64	5	trained	train	VERB
iajs-2710	64	6	by	by	ADP
iajs-2710	64	7	giving	give	VERB
iajs-2710	64	8	it	it	PRON
iajs-2710	64	9	example	example	NOUN
iajs-2710	64	10	cases	case	NOUN
iajs-2710	64	11	and	and	CCONJ
iajs-2710	64	12	their	their	PRON
iajs-2710	64	13	corresponding	corresponding	ADJ
iajs-2710	64	14	solutions	solution	NOUN
iajs-2710	64	15	.	.	PUNCT
iajs-2710	65	1	the	the	DET
iajs-2710	65	2	network	network	NOUN
iajs-2710	65	3	computes	compute	VERB
iajs-2710	65	4	the	the	DET
iajs-2710	65	5	prediction	prediction	NOUN
iajs-2710	65	6	and	and	CCONJ
iajs-2710	65	7	the	the	DET
iajs-2710	65	8	loss	loss	NOUN
iajs-2710	65	9	for	for	ADP
iajs-2710	65	10	the	the	DET
iajs-2710	65	11	example	example	NOUN
iajs-2710	65	12	cases	case	NOUN
iajs-2710	65	13	.	.	PUNCT
iajs-2710	66	1	1.2	1.2	NUM
iajs-2710	66	2	.	.	X
iajs-2710	67	1	back	back	ADV
iajs-2710	67	2	training	train	VERB
iajs-2710	67	3	the	the	DET
iajs-2710	67	4	network	network	NOUN
iajs-2710	67	5	can	can	AUX
iajs-2710	67	6	update	update	VERB
iajs-2710	67	7	its	its	PRON
iajs-2710	67	8	parameter	parameter	NOUN
iajs-2710	67	9	after	after	ADP
iajs-2710	67	10	seeing	see	VERB
iajs-2710	67	11	more	more	ADJ
iajs-2710	67	12	than	than	ADP
iajs-2710	67	13	one	one	NUM
iajs-2710	67	14	example	example	NOUN
iajs-2710	67	15	.	.	PUNCT
iajs-2710	68	1	this	this	PRON
iajs-2710	68	2	is	be	AUX
iajs-2710	68	3	called	call	VERB
iajs-2710	68	4	batch	batch	NOUN
iajs-2710	68	5	training	training	NOUN
iajs-2710	68	6	.	.	PUNCT
iajs-2710	69	1	when	when	SCONJ
iajs-2710	69	2	batch	batch	NOUN
iajs-2710	69	3	training	training	NOUN
iajs-2710	69	4	is	be	AUX
iajs-2710	69	5	used	use	VERB
iajs-2710	69	6	,	,	PUNCT
iajs-2710	69	7	the	the	DET
iajs-2710	69	8	network	network	NOUN
iajs-2710	69	9	is	be	AUX
iajs-2710	69	10	fed	feed	VERB
iajs-2710	69	11	a	a	DET
iajs-2710	69	12	batch	batch	NOUN
iajs-2710	69	13	of	of	ADP
iajs-2710	69	14	example	example	NOUN
iajs-2710	69	15	cases	case	NOUN
iajs-2710	69	16	;	;	PUNCT
iajs-2710	69	17	the	the	DET
iajs-2710	69	18	loss	loss	NOUN
iajs-2710	69	19	is	be	AUX
iajs-2710	69	20	computed	compute	VERB
iajs-2710	69	21	and	and	CCONJ
iajs-2710	69	22	averaged	average	VERB
iajs-2710	69	23	for	for	ADP
iajs-2710	69	24	the	the	DET
iajs-2710	69	25	batch	batch	NOUN
iajs-2710	69	26	.	.	PUNCT
iajs-2710	70	1	the	the	DET
iajs-2710	70	2	number	number	NOUN
iajs-2710	70	3	of	of	ADP
iajs-2710	70	4	examples	example	NOUN
iajs-2710	70	5	fed	feed	VERB
iajs-2710	70	6	into	into	ADP
iajs-2710	70	7	the	the	DET
iajs-2710	70	8	network	network	NOUN
iajs-2710	70	9	is	be	AUX
iajs-2710	70	10	called	call	VERB
iajs-2710	70	11	the	the	DET
iajs-2710	70	12	batch	batch	NOUN
iajs-2710	70	13	size	size	NOUN
iajs-2710	70	14	.	.	PUNCT
iajs-2710	71	1	since	since	SCONJ
iajs-2710	71	2	the	the	DET
iajs-2710	71	3	loss	loss	NOUN
iajs-2710	71	4	is	be	AUX
iajs-2710	71	5	averaged	average	VERB
iajs-2710	71	6	over	over	ADP
iajs-2710	71	7	a	a	DET
iajs-2710	71	8	set	set	NOUN
iajs-2710	71	9	of	of	ADP
iajs-2710	71	10	example	example	NOUN
iajs-2710	71	11	cases	case	NOUN
iajs-2710	71	12	,	,	PUNCT
iajs-2710	71	13	it	it	PRON
iajs-2710	71	14	becomes	become	VERB
iajs-2710	71	15	a	a	DET
iajs-2710	71	16	more	more	ADV
iajs-2710	71	17	accurate	accurate	ADJ
iajs-2710	71	18	estimation	estimation	NOUN
iajs-2710	71	19	of	of	ADP
iajs-2710	71	20	how	how	SCONJ
iajs-2710	71	21	close	close	ADJ
iajs-2710	71	22	the	the	DET
iajs-2710	71	23	network	network	NOUN
iajs-2710	71	24	’s	’s	PART
iajs-2710	71	25	function	function	NOUN
iajs-2710	71	26	is	be	AUX
iajs-2710	71	27	to	to	ADP
iajs-2710	71	28	the	the	DET
iajs-2710	71	29	problem	problem	NOUN
iajs-2710	71	30	’s	’s	PART
iajs-2710	71	31	underlying	underlie	VERB
iajs-2710	71	32	function	function	NOUN
iajs-2710	71	33	instead	instead	ADV
iajs-2710	71	34	of	of	ADP
iajs-2710	71	35	just	just	ADV
iajs-2710	71	36	one	one	NUM
iajs-2710	71	37	example	example	NOUN
iajs-2710	71	38	case	case	NOUN
iajs-2710	71	39	.	.	PUNCT
iajs-2710	72	1	the	the	DET
iajs-2710	72	2	updates	update	NOUN
iajs-2710	72	3	to	to	ADP
iajs-2710	72	4	the	the	DET
iajs-2710	72	5	parameters	parameter	NOUN
iajs-2710	72	6	are	be	AUX
iajs-2710	72	7	therefore	therefore	ADV
iajs-2710	72	8	more	more	ADV
iajs-2710	72	9	stable	stable	ADJ
iajs-2710	72	10	.	.	PUNCT
iajs-2710	73	1	consequently	consequently	ADV
iajs-2710	73	2	,	,	PUNCT
iajs-2710	73	3	the	the	DET
iajs-2710	73	4	network	network	NOUN
iajs-2710	73	5	can	can	AUX
iajs-2710	73	6	learn	learn	VERB
iajs-2710	73	7	more	more	ADV
iajs-2710	73	8	smoothly	smoothly	ADV
iajs-2710	73	9	[	[	X
iajs-2710	73	10	7	7	NUM
iajs-2710	73	11	]	]	PUNCT
iajs-2710	73	12	.	.	PUNCT
iajs-2710	74	1	a	a	DET
iajs-2710	74	2	more	more	ADV
iajs-2710	74	3	significant	significant	ADJ
iajs-2710	74	4	learning	learning	NOUN
iajs-2710	74	5	rate	rate	NOUN
iajs-2710	74	6	can	can	AUX
iajs-2710	74	7	also	also	ADV
iajs-2710	74	8	be	be	AUX
iajs-2710	74	9	used	use	VERB
iajs-2710	74	10	when	when	SCONJ
iajs-2710	74	11	larger	large	ADJ
iajs-2710	74	12	batch	batch	NOUN
iajs-2710	74	13	size	size	NOUN
iajs-2710	74	14	is	be	AUX
iajs-2710	74	15	used	use	VERB
iajs-2710	74	16	.	.	PUNCT
iajs-2710	75	1	1.3	1.3	NUM
iajs-2710	75	2	.	.	PUNCT
iajs-2710	76	1	optimizers	optimizer	NOUN
iajs-2710	76	2	there	there	PRON
iajs-2710	76	3	are	be	VERB
iajs-2710	76	4	different	different	ADJ
iajs-2710	76	5	alternatives	alternative	NOUN
iajs-2710	76	6	to	to	ADP
iajs-2710	76	7	plain	plain	ADJ
iajs-2710	76	8	backpropagation	backpropagation	NOUN
iajs-2710	76	9	for	for	ADP
iajs-2710	76	10	training	train	VERB
iajs-2710	76	11	neural	neural	ADJ
iajs-2710	76	12	networks	network	NOUN
iajs-2710	76	13	.	.	PUNCT
iajs-2710	77	1	ling	ling	PROPN
iajs-2710	77	2	,	,	PUNCT
iajs-2710	77	3	h	h	NOUN
iajs-2710	78	1	[	[	X
iajs-2710	78	2	8	8	NUM
iajs-2710	78	3	]	]	PUNCT
iajs-2710	78	4	,	,	PUNCT
iajs-2710	78	5	provides	provide	VERB
iajs-2710	78	6	an	an	DET
iajs-2710	78	7	overview	overview	NOUN
iajs-2710	78	8	of	of	ADP
iajs-2710	78	9	some	some	PRON
iajs-2710	78	10	of	of	ADP
iajs-2710	78	11	the	the	DET
iajs-2710	78	12	alternatives	alternative	NOUN
iajs-2710	78	13	.	.	PUNCT
iajs-2710	79	1	using	use	VERB
iajs-2710	79	2	momentum	momentum	NOUN
iajs-2710	79	3	,	,	PUNCT
iajs-2710	79	4	the	the	DET
iajs-2710	79	5	updates	update	NOUN
iajs-2710	79	6	can	can	AUX
iajs-2710	79	7	be	be	AUX
iajs-2710	79	8	estimated	estimate	VERB
iajs-2710	79	9	to	to	PART
iajs-2710	79	10	be	be	AUX
iajs-2710	79	11	larger	large	ADJ
iajs-2710	79	12	or	or	CCONJ
iajs-2710	79	13	lower	low	ADJ
iajs-2710	79	14	for	for	ADP
iajs-2710	79	15	the	the	DET
iajs-2710	79	16	parameters	parameter	NOUN
iajs-2710	79	17	for	for	ADP
iajs-2710	79	18	each	each	DET
iajs-2710	79	19	update	update	NOUN
iajs-2710	79	20	step	step	NOUN
iajs-2710	79	21	.	.	PUNCT
iajs-2710	80	1	it	it	PRON
iajs-2710	80	2	does	do	VERB
iajs-2710	80	3	this	this	PRON
iajs-2710	80	4	by	by	ADP
iajs-2710	80	5	adding	add	VERB
iajs-2710	80	6	a	a	DET
iajs-2710	80	7	fraction	fraction	NOUN
iajs-2710	80	8	of	of	ADP
iajs-2710	80	9	the	the	DET
iajs-2710	80	10	last	last	ADJ
iajs-2710	80	11	update	update	NOUN
iajs-2710	80	12	to	to	ADP
iajs-2710	80	13	the	the	DET
iajs-2710	80	14	current	current	ADJ
iajs-2710	80	15	update	update	NOUN
iajs-2710	80	16	value	value	NOUN
iajs-2710	80	17	.	.	PUNCT
iajs-2710	81	1	it	it	PRON
iajs-2710	81	2	approximates	approximate	VERB
iajs-2710	81	3	future	future	ADJ
iajs-2710	81	4	values	value	NOUN
iajs-2710	81	5	of	of	ADP
iajs-2710	81	6	the	the	DET
iajs-2710	81	7	parameters	parameter	NOUN
iajs-2710	81	8	to	to	PART
iajs-2710	81	9	be	be	AUX
iajs-2710	81	10	updated	update	VERB
iajs-2710	81	11	.	.	PUNCT
iajs-2710	82	1	then	then	ADV
iajs-2710	82	2	it	it	PRON
iajs-2710	82	3	uses	use	VERB
iajs-2710	82	4	this	this	PRON
iajs-2710	82	5	to	to	PART
iajs-2710	82	6	update	update	VERB
iajs-2710	82	7	the	the	DET
iajs-2710	82	8	parameters	parameter	NOUN
iajs-2710	82	9	.	.	PUNCT
iajs-2710	83	1	1.4	1.4	NUM
iajs-2710	83	2	.	.	PUNCT
iajs-2710	84	1	aim	aim	NOUN
iajs-2710	84	2	of	of	ADP
iajs-2710	84	3	study	study	VERB
iajs-2710	84	4	a	a	DET
iajs-2710	84	5	system	system	NOUN
iajs-2710	84	6	for	for	ADP
iajs-2710	84	7	real	real	ADJ
iajs-2710	84	8	-	-	PUNCT
iajs-2710	84	9	time	time	NOUN
iajs-2710	84	10	brain	brain	NOUN
iajs-2710	84	11	recognition	recognition	NOUN
iajs-2710	84	12	using	use	VERB
iajs-2710	84	13	deep	deep	ADJ
iajs-2710	84	14	earning	earning	NOUN
iajs-2710	84	15	-	-	PUNCT
iajs-2710	84	16	based	base	VERB
iajs-2710	84	17	cnn	cnn	PROPN
iajs-2710	84	18	technique	technique	NOUN
iajs-2710	84	19	.	.	PUNCT
iajs-2710	85	1	the	the	DET
iajs-2710	85	2	study	study	NOUN
iajs-2710	85	3	is	be	AUX
iajs-2710	85	4	designed	design	VERB
iajs-2710	85	5	and	and	CCONJ
iajs-2710	85	6	implemented	implement	VERB
iajs-2710	85	7	a	a	DET
iajs-2710	85	8	complete	complete	ADJ
iajs-2710	85	9	real	real	ADJ
iajs-2710	85	10	-	-	PUNCT
iajs-2710	85	11	time	time	NOUN
iajs-2710	85	12	magnetic	magnetic	ADJ
iajs-2710	85	13	resonance	resonance	NOUN
iajs-2710	85	14	system	system	NOUN
iajs-2710	85	15	based	base	VERB
iajs-2710	85	16	on	on	ADP
iajs-2710	85	17	deep	deep	ADJ
iajs-2710	85	18	learning	learning	NOUN
iajs-2710	85	19	.	.	PUNCT
iajs-2710	86	1	the	the	DET
iajs-2710	86	2	system	system	NOUN
iajs-2710	86	3	broadcasts	broadcast	VERB
iajs-2710	86	4	the	the	DET
iajs-2710	86	5	location	location	NOUN
iajs-2710	86	6	and	and	CCONJ
iajs-2710	86	7	mr	mr	PROPN
iajs-2710	86	8	detection	detection	NOUN
iajs-2710	86	9	of	of	ADP
iajs-2710	86	10	the	the	DET
iajs-2710	86	11	brain	brain	NOUN
iajs-2710	86	12	through	through	ADP
iajs-2710	86	13	a	a	DET
iajs-2710	86	14	deep	deep	ADJ
iajs-2710	86	15	learning	learning	NOUN
iajs-2710	86	16	based	base	VERB
iajs-2710	86	17	approach	approach	NOUN
iajs-2710	86	18	and	and	CCONJ
iajs-2710	86	19	can	can	AUX
iajs-2710	86	20	be	be	AUX
iajs-2710	86	21	used	use	VERB
iajs-2710	86	22	by	by	ADP
iajs-2710	86	23	other	other	ADJ
iajs-2710	86	24	applications	application	NOUN
iajs-2710	86	25	.	.	PUNCT
iajs-2710	87	1	an	an	DET
iajs-2710	87	2	inexpensive	inexpensive	ADJ
iajs-2710	87	3	way	way	NOUN
iajs-2710	87	4	to	to	PART
iajs-2710	87	5	generate	generate	VERB
iajs-2710	87	6	accurate	accurate	ADJ
iajs-2710	87	7	labeled	label	VERB
iajs-2710	87	8	data	datum	NOUN
iajs-2710	87	9	using	use	VERB
iajs-2710	87	10	cnn	cnn	PROPN
iajs-2710	87	11	for	for	ADP
iajs-2710	87	12	magnetic	magnetic	ADJ
iajs-2710	87	13	resonance	resonance	NOUN
iajs-2710	87	14	samples	sample	NOUN
iajs-2710	87	15	.	.	PUNCT
iajs-2710	88	1	we	we	PRON
iajs-2710	88	2	use	use	VERB
iajs-2710	88	3	deep	deep	ADJ
iajs-2710	88	4	learning	learning	NOUN
iajs-2710	88	5	to	to	PART
iajs-2710	88	6	easily	easily	ADV
iajs-2710	88	7	generate	generate	VERB
iajs-2710	88	8	labeled	label	VERB
iajs-2710	88	9	data	datum	NOUN
iajs-2710	88	10	using	use	VERB
iajs-2710	88	11	the	the	DET
iajs-2710	88	12	aligned	aligned	ADJ
iajs-2710	88	13	rgb	rgb	PROPN
iajs-2710	88	14	and	and	CCONJ
iajs-2710	88	15	depth	depth	NOUN
iajs-2710	88	16	images	image	NOUN
iajs-2710	88	17	.	.	PUNCT
iajs-2710	89	1	we	we	PRON
iajs-2710	89	2	found	find	VERB
iajs-2710	89	3	this	this	PRON
iajs-2710	89	4	expensively	expensively	ADV
iajs-2710	89	5	and	and	CCONJ
iajs-2710	89	6	through	through	ADP
iajs-2710	89	7	deep	deep	ADJ
iajs-2710	89	8	learning	learning	NOUN
iajs-2710	89	9	,	,	PUNCT
iajs-2710	89	10	developers	developer	NOUN
iajs-2710	89	11	can	can	AUX
iajs-2710	89	12	generate	generate	VERB
iajs-2710	89	13	their	their	PRON
iajs-2710	89	14	customized	customize	VERB
iajs-2710	89	15	system	system	NOUN
iajs-2710	89	16	without	without	ADP
iajs-2710	89	17	difficulty	difficulty	NOUN
iajs-2710	89	18	.	.	PUNCT
iajs-2710	90	1	another	another	DET
iajs-2710	90	2	advantage	advantage	NOUN
iajs-2710	90	3	of	of	ADP
iajs-2710	90	4	our	our	PRON
iajs-2710	90	5	approach	approach	NOUN
iajs-2710	90	6	is	be	AUX
iajs-2710	90	7	that	that	SCONJ
iajs-2710	90	8	the	the	DET
iajs-2710	90	9	system	system	NOUN
iajs-2710	90	10	uses	use	VERB
iajs-2710	90	11	actual	actual	ADJ
iajs-2710	90	12	raw	raw	ADJ
iajs-2710	90	13	depth	depth	NOUN
iajs-2710	90	14	mr	mr	PROPN
iajs-2710	90	15	images	image	NOUN
iajs-2710	90	16	as	as	ADP
iajs-2710	90	17	training	training	NOUN
iajs-2710	90	18	samples	sample	NOUN
iajs-2710	90	19	.	.	PUNCT
iajs-2710	91	1	these	these	PRON
iajs-2710	91	2	naturally	naturally	ADV
iajs-2710	91	3	capture	capture	VERB
iajs-2710	91	4	realistic	realistic	ADJ
iajs-2710	91	5	noise	noise	NOUN
iajs-2710	91	6	such	such	ADJ
iajs-2710	91	7	as	as	ADP
iajs-2710	91	8	shadows	shadow	NOUN
iajs-2710	91	9	and	and	CCONJ
iajs-2710	91	10	hardware	hardware	NOUN
iajs-2710	91	11	noise	noise	NOUN
iajs-2710	91	12	.	.	PUNCT
iajs-2710	92	1	using	use	VERB
iajs-2710	92	2	computer	computer	NOUN
iajs-2710	92	3	-	-	PUNCT
iajs-2710	92	4	generated	generate	VERB
iajs-2710	92	5	graphics	graphic	NOUN
iajs-2710	92	6	are	be	AUX
iajs-2710	92	7	very	very	ADV
iajs-2710	92	8	difficult	difficult	ADJ
iajs-2710	92	9	to	to	PART
iajs-2710	92	10	simulate	simulate	VERB
iajs-2710	92	11	these	these	DET
iajs-2710	92	12	noisy	noisy	ADJ
iajs-2710	92	13	effects	effect	NOUN
iajs-2710	92	14	.	.	PUNCT
iajs-2710	93	1	note	note	VERB
iajs-2710	93	2	that	that	SCONJ
iajs-2710	93	3	the	the	DET
iajs-2710	93	4	end	end	NOUN
iajs-2710	93	5	-	-	PUNCT
iajs-2710	93	6	users	user	NOUN
iajs-2710	93	7	do	do	AUX
iajs-2710	93	8	need	need	VERB
iajs-2710	93	9	to	to	PART
iajs-2710	93	10	use	use	VERB
iajs-2710	93	11	deep	deep	ADJ
iajs-2710	93	12	learning	learning	NOUN
iajs-2710	93	13	;	;	PUNCT
iajs-2710	93	14	they	they	PRON
iajs-2710	93	15	are	be	AUX
iajs-2710	93	16	only	only	ADV
iajs-2710	93	17	used	use	VERB
iajs-2710	93	18	in	in	ADP
iajs-2710	93	19	training	training	NOUN
iajs-2710	93	20	.	.	PUNCT
iajs-2710	94	1	a	a	DET
iajs-2710	94	2	computational	computational	ADJ
iajs-2710	94	3	insight	insight	NOUN
iajs-2710	94	4	about	about	ADP
iajs-2710	94	5	the	the	DET
iajs-2710	94	6	convolutional	convolutional	ADJ
iajs-2710	94	7	neural	neural	ADJ
iajs-2710	94	8	network	network	NOUN
iajs-2710	94	9	(	(	PUNCT
iajs-2710	94	10	cnn	cnn	PROPN
iajs-2710	94	11	)	)	PUNCT
iajs-2710	94	12	based	base	VERB
iajs-2710	94	13	data	datum	NOUN
iajs-2710	94	14	model	model	NOUN
iajs-2710	94	15	.	.	PUNCT
iajs-2710	95	1	to	to	ADP
iajs-2710	95	2	the	the	DET
iajs-2710	95	3	best	good	ADJ
iajs-2710	95	4	of	of	ADP
iajs-2710	95	5	our	our	PRON
iajs-2710	95	6	knowledge	knowledge	NOUN
iajs-2710	95	7	,	,	PUNCT
iajs-2710	95	8	there	there	PRON
iajs-2710	95	9	seems	seem	VERB
iajs-2710	95	10	to	to	PART
iajs-2710	95	11	be	be	AUX
iajs-2710	95	12	literature	literature	NOUN
iajs-2710	95	13	comparing	compare	VERB
iajs-2710	95	14	svm	svm	NOUN
iajs-2710	95	15	and	and	CCONJ
iajs-2710	95	16	random	random	ADJ
iajs-2710	95	17	forest	forest	NOUN
iajs-2710	95	18	from	from	ADP
iajs-2710	95	19	a	a	DET
iajs-2710	95	20	computational	computational	ADJ
iajs-2710	95	21	perspective	perspective	NOUN
iajs-2710	95	22	.	.	PUNCT
iajs-2710	96	1	we	we	PRON
iajs-2710	96	2	provide	provide	VERB
iajs-2710	96	3	an	an	DET
iajs-2710	96	4	indepth	indepth	ADJ
iajs-2710	96	5	complexity	complexity	NOUN
iajs-2710	96	6	analysis	analysis	NOUN
iajs-2710	96	7	of	of	ADP
iajs-2710	96	8	the	the	DET
iajs-2710	96	9	two	two	NUM
iajs-2710	96	10	methods	method	NOUN
iajs-2710	96	11	rather	rather	ADV
iajs-2710	96	12	than	than	ADP
iajs-2710	96	13	merely	merely	ADV
iajs-2710	96	14	reporting	report	VERB
iajs-2710	96	15	experimental	experimental	ADJ
iajs-2710	96	16	accuracy	accuracy	NOUN
iajs-2710	96	17	as	as	SCONJ
iajs-2710	96	18	done	do	VERB
iajs-2710	96	19	in	in	ADP
iajs-2710	96	20	most	most	ADJ
iajs-2710	96	21	machine	machine	NOUN
iajs-2710	96	22	learning	learn	VERB
iajs-2710	96	23	literature	literature	NOUN
iajs-2710	96	24	extensive	extensive	ADJ
iajs-2710	96	25	experimental	experimental	ADJ
iajs-2710	96	26	evaluations	evaluation	NOUN
iajs-2710	96	27	of	of	ADP
iajs-2710	96	28	the	the	DET
iajs-2710	96	29	system	system	NOUN
iajs-2710	96	30	we	we	PRON
iajs-2710	96	31	conduct	conduct	VERB
iajs-2710	96	32	extensive	extensive	ADJ
iajs-2710	96	33	experiments	experiment	NOUN
iajs-2710	96	34	evaluating	evaluate	VERB
iajs-2710	96	35	the	the	DET
iajs-2710	96	36	effectiveness	effectiveness	NOUN
iajs-2710	96	37	of	of	ADP
iajs-2710	96	38	the	the	DET
iajs-2710	96	39	random	random	PROPN
iajs-2710	96	40	ibn	ibn	PROPN
iajs-2710	96	41	al	al	PROPN
iajs-2710	96	42	-	-	PUNCT
iajs-2710	96	43	haitham	haitham	PROPN
iajs-2710	96	44	jour	jour	X
iajs-2710	96	45	.	.	PROPN
iajs-2710	96	46	for	for	ADP
iajs-2710	96	47	pure	pure	ADJ
iajs-2710	96	48	&	&	CCONJ
iajs-2710	96	49	appl	appl	PROPN
iajs-2710	96	50	.	.	PUNCT
iajs-2710	97	1	sci	sci	PROPN
iajs-2710	97	2	.	.	PROPN
iajs-2710	98	1	34(4)2021	34(4)2021	NUM
iajs-2710	98	2	134	134	NUM
iajs-2710	98	3	forest	forest	NOUN
iajs-2710	98	4	classifier	classifier	NOUN
iajs-2710	98	5	by	by	ADP
iajs-2710	98	6	systematically	systematically	ADV
iajs-2710	98	7	exploring	explore	VERB
iajs-2710	98	8	a	a	DET
iajs-2710	98	9	large	large	ADJ
iajs-2710	98	10	space	space	NOUN
iajs-2710	98	11	of	of	ADP
iajs-2710	98	12	parameters	parameter	NOUN
iajs-2710	98	13	.	.	PUNCT
iajs-2710	99	1	interesting	interesting	ADJ
iajs-2710	99	2	results	result	NOUN
iajs-2710	99	3	lead	lead	VERB
iajs-2710	99	4	to	to	ADP
iajs-2710	99	5	a	a	DET
iajs-2710	99	6	deeper	deep	ADJ
iajs-2710	99	7	understanding	understanding	NOUN
iajs-2710	99	8	of	of	ADP
iajs-2710	99	9	cnn	cnn	PROPN
iajs-2710	99	10	.	.	PUNCT
iajs-2710	100	1	2.related	2.related	NUM
iajs-2710	100	2	work	work	NOUN
iajs-2710	100	3	researchers	researcher	NOUN
iajs-2710	100	4	in	in	ADP
iajs-2710	100	5	[	[	X
iajs-2710	100	6	9	9	NUM
iajs-2710	100	7	]	]	X
iajs-2710	100	8	propose	propose	VERB
iajs-2710	100	9	an	an	DET
iajs-2710	100	10	algorithm	algorithm	NOUN
iajs-2710	100	11	for	for	ADP
iajs-2710	100	12	rectangular	rectangular	ADJ
iajs-2710	100	13	segment	segment	NOUN
iajs-2710	100	14	objects	object	NOUN
iajs-2710	100	15	that	that	PRON
iajs-2710	100	16	may	may	AUX
iajs-2710	100	17	overlap	overlap	VERB
iajs-2710	100	18	and	and	CCONJ
iajs-2710	100	19	are	be	AUX
iajs-2710	100	20	placed	place	VERB
iajs-2710	100	21	on	on	ADP
iajs-2710	100	22	a	a	DET
iajs-2710	100	23	lightly	lightly	ADV
iajs-2710	100	24	textured	textured	ADJ
iajs-2710	100	25	background	background	NOUN
iajs-2710	100	26	with	with	ADP
iajs-2710	100	27	unknown	unknown	ADJ
iajs-2710	100	28	color	color	NOUN
iajs-2710	100	29	,	,	PUNCT
iajs-2710	100	30	which	which	PRON
iajs-2710	100	31	is	be	AUX
iajs-2710	100	32	the	the	DET
iajs-2710	100	33	usual	usual	ADJ
iajs-2710	100	34	output	output	NOUN
iajs-2710	100	35	of	of	ADP
iajs-2710	100	36	scanner	scanner	NOUN
iajs-2710	100	37	preview	preview	NOUN
iajs-2710	100	38	images	image	NOUN
iajs-2710	100	39	.	.	PUNCT
iajs-2710	101	1	the	the	DET
iajs-2710	101	2	authors	author	NOUN
iajs-2710	101	3	in	in	ADP
iajs-2710	101	4	[	[	X
iajs-2710	101	5	10	10	NUM
iajs-2710	101	6	]	]	PUNCT
iajs-2710	101	7	aim	aim	NOUN
iajs-2710	101	8	at	at	ADP
iajs-2710	101	9	detecting	detect	VERB
iajs-2710	101	10	the	the	DET
iajs-2710	101	11	background	background	NOUN
iajs-2710	101	12	color	color	NOUN
iajs-2710	101	13	,	,	PUNCT
iajs-2710	101	14	which	which	PRON
iajs-2710	101	15	is	be	AUX
iajs-2710	101	16	challenging	challenge	VERB
iajs-2710	101	17	when	when	SCONJ
iajs-2710	101	18	the	the	DET
iajs-2710	101	19	image	image	NOUN
iajs-2710	101	20	consists	consist	VERB
iajs-2710	101	21	primarily	primarily	ADV
iajs-2710	101	22	of	of	ADP
iajs-2710	101	23	differently	differently	ADV
iajs-2710	101	24	colored	colored	ADJ
iajs-2710	101	25	foreground	foreground	NOUN
iajs-2710	101	26	objects	object	NOUN
iajs-2710	101	27	,	,	PUNCT
iajs-2710	101	28	but	but	CCONJ
iajs-2710	101	29	it	it	PRON
iajs-2710	101	30	allows	allow	VERB
iajs-2710	101	31	them	they	PRON
iajs-2710	101	32	to	to	PART
iajs-2710	101	33	segment	segment	VERB
iajs-2710	101	34	the	the	DET
iajs-2710	101	35	objects	object	NOUN
iajs-2710	101	36	more	more	ADV
iajs-2710	101	37	easily	easily	ADV
iajs-2710	101	38	.	.	PUNCT
iajs-2710	102	1	to	to	PART
iajs-2710	102	2	retrieve	retrieve	VERB
iajs-2710	102	3	the	the	DET
iajs-2710	102	4	background	background	NOUN
iajs-2710	102	5	color	color	NOUN
iajs-2710	102	6	,	,	PUNCT
iajs-2710	102	7	they	they	PRON
iajs-2710	102	8	first	first	ADV
iajs-2710	102	9	separate	separate	VERB
iajs-2710	102	10	the	the	DET
iajs-2710	102	11	image	image	NOUN
iajs-2710	102	12	into	into	ADP
iajs-2710	102	13	line	line	NOUN
iajs-2710	102	14	segments	segment	NOUN
iajs-2710	102	15	with	with	ADP
iajs-2710	102	16	the	the	DET
iajs-2710	102	17	same	same	ADJ
iajs-2710	102	18	tinby	tinby	NOUN
iajs-2710	102	19	calculating	calculate	VERB
iajs-2710	102	20	the	the	DET
iajs-2710	102	21	neighboring	neighbor	VERB
iajs-2710	102	22	color	color	NOUN
iajs-2710	102	23	differences	difference	NOUN
iajs-2710	102	24	.	.	PUNCT
iajs-2710	103	1	under	under	ADP
iajs-2710	103	2	the	the	DET
iajs-2710	103	3	assumption	assumption	NOUN
iajs-2710	103	4	that	that	SCONJ
iajs-2710	103	5	the	the	DET
iajs-2710	103	6	background	background	NOUN
iajs-2710	103	7	color	color	NOUN
iajs-2710	103	8	segments	segment	NOUN
iajs-2710	103	9	are	be	AUX
iajs-2710	103	10	long	long	ADJ
iajs-2710	103	11	,	,	PUNCT
iajs-2710	103	12	a	a	DET
iajs-2710	103	13	voting	voting	NOUN
iajs-2710	103	14	scheme	scheme	NOUN
iajs-2710	103	15	is	be	AUX
iajs-2710	103	16	used	use	VERB
iajs-2710	103	17	to	to	PART
iajs-2710	103	18	extract	extract	VERB
iajs-2710	103	19	possible	possible	ADJ
iajs-2710	103	20	background	background	NOUN
iajs-2710	103	21	colors	color	NOUN
iajs-2710	103	22	.	.	PUNCT
iajs-2710	104	1	for	for	ADP
iajs-2710	104	2	each	each	DET
iajs-2710	104	3	background	background	NOUN
iajs-2710	104	4	color	color	NOUN
iajs-2710	104	5	candidate	candidate	NOUN
iajs-2710	104	6	,	,	PUNCT
iajs-2710	104	7	the	the	DET
iajs-2710	104	8	edge	edge	NOUN
iajs-2710	104	9	strength	strength	NOUN
iajs-2710	104	10	at	at	ADP
iajs-2710	104	11	the	the	DET
iajs-2710	104	12	boundaries	boundary	NOUN
iajs-2710	104	13	to	to	ADP
iajs-2710	104	14	non	non	ADJ
iajs-2710	104	15	-	-	ADJ
iajs-2710	104	16	background	background	ADJ
iajs-2710	104	17	colors	color	NOUN
iajs-2710	104	18	is	be	AUX
iajs-2710	104	19	calculated	calculate	VERB
iajs-2710	104	20	.	.	PUNCT
iajs-2710	105	1	the	the	DET
iajs-2710	105	2	authors	author	NOUN
iajs-2710	105	3	observed	observe	VERB
iajs-2710	105	4	that	that	SCONJ
iajs-2710	105	5	the	the	DET
iajs-2710	105	6	gradient	gradient	NOUN
iajs-2710	105	7	between	between	ADP
iajs-2710	105	8	background	background	NOUN
iajs-2710	105	9	and	and	CCONJ
iajs-2710	105	10	object	object	VERB
iajs-2710	105	11	colors	color	NOUN
iajs-2710	105	12	is	be	AUX
iajs-2710	105	13	larger	large	ADJ
iajs-2710	105	14	than	than	SCONJ
iajs-2710	105	15	it	it	PRON
iajs-2710	105	16	is	be	AUX
iajs-2710	105	17	between	between	ADP
iajs-2710	105	18	foreground	foreground	NOUN
iajs-2710	105	19	colors	color	NOUN
iajs-2710	105	20	and	and	CCONJ
iajs-2710	105	21	that	that	SCONJ
iajs-2710	105	22	the	the	DET
iajs-2710	105	23	number	number	NOUN
iajs-2710	105	24	of	of	ADP
iajs-2710	105	25	edge	edge	NOUN
iajs-2710	105	26	pixels	pixel	NOUN
iajs-2710	105	27	correlates	correlate	VERB
iajs-2710	105	28	with	with	ADP
iajs-2710	105	29	the	the	DET
iajs-2710	105	30	number	number	NOUN
iajs-2710	105	31	of	of	ADP
iajs-2710	105	32	foreground	foreground	NOUN
iajs-2710	105	33	objects	object	NOUN
iajs-2710	105	34	.	.	PUNCT
iajs-2710	106	1	therefore	therefore	ADV
iajs-2710	106	2	,	,	PUNCT
iajs-2710	106	3	they	they	PRON
iajs-2710	106	4	determine	determine	VERB
iajs-2710	106	5	the	the	DET
iajs-2710	106	6	true	true	ADJ
iajs-2710	106	7	background	background	NOUN
iajs-2710	106	8	color	color	NOUN
iajs-2710	106	9	by	by	ADP
iajs-2710	106	10	only	only	ADV
iajs-2710	106	11	using	use	VERB
iajs-2710	106	12	line	line	NOUN
iajs-2710	106	13	segments	segment	NOUN
iajs-2710	106	14	that	that	PRON
iajs-2710	106	15	exceed	exceed	VERB
iajs-2710	106	16	a	a	DET
iajs-2710	106	17	certain	certain	ADJ
iajs-2710	106	18	length	length	NOUN
iajs-2710	106	19	,	,	PUNCT
iajs-2710	106	20	are	be	AUX
iajs-2710	106	21	of	of	ADP
iajs-2710	106	22	the	the	DET
iajs-2710	106	23	most	most	ADV
iajs-2710	106	24	frequent	frequent	ADJ
iajs-2710	106	25	color	color	NOUN
iajs-2710	106	26	,	,	PUNCT
iajs-2710	106	27	and	and	CCONJ
iajs-2710	106	28	have	have	VERB
iajs-2710	106	29	many	many	ADJ
iajs-2710	106	30	edge	edge	NOUN
iajs-2710	106	31	points	point	NOUN
iajs-2710	106	32	with	with	ADP
iajs-2710	106	33	high	high	ADJ
iajs-2710	106	34	gradient	gradient	ADJ
iajs-2710	106	35	values	value	NOUN
iajs-2710	106	36	,	,	PUNCT
iajs-2710	106	37	as	as	SCONJ
iajs-2710	106	38	mentioned	mention	VERB
iajs-2710	106	39	in	in	ADP
iajs-2710	106	40	[	[	X
iajs-2710	106	41	11	11	NUM
iajs-2710	106	42	]	]	PUNCT
iajs-2710	106	43	.	.	PUNCT
iajs-2710	107	1	connected	connected	ADJ
iajs-2710	107	2	components	component	NOUN
iajs-2710	107	3	are	be	AUX
iajs-2710	107	4	extracted	extract	VERB
iajs-2710	107	5	and	and	CCONJ
iajs-2710	107	6	used	use	VERB
iajs-2710	107	7	to	to	PART
iajs-2710	107	8	fit	fit	VERB
iajs-2710	107	9	lines	line	NOUN
iajs-2710	107	10	from	from	ADP
iajs-2710	107	11	these	these	DET
iajs-2710	107	12	edge	edge	NOUN
iajs-2710	107	13	pixels	pixel	NOUN
iajs-2710	107	14	,	,	PUNCT
iajs-2710	107	15	with	with	ADP
iajs-2710	107	16	weights	weight	NOUN
iajs-2710	107	17	derived	derive	VERB
iajs-2710	107	18	from	from	ADP
iajs-2710	107	19	the	the	DET
iajs-2710	107	20	edge	edge	NOUN
iajs-2710	107	21	strength	strength	NOUN
iajs-2710	107	22	.	.	PUNCT
iajs-2710	108	1	neighboring	neighboring	NOUN
iajs-2710	108	2	pixels	pixel	NOUN
iajs-2710	108	3	located	locate	VERB
iajs-2710	108	4	in	in	ADP
iajs-2710	108	5	the	the	DET
iajs-2710	108	6	direction	direction	NOUN
iajs-2710	108	7	of	of	ADP
iajs-2710	108	8	the	the	DET
iajs-2710	108	9	line	line	NOUN
iajs-2710	108	10	are	be	AUX
iajs-2710	108	11	added	add	VERB
iajs-2710	108	12	until	until	SCONJ
iajs-2710	108	13	a	a	DET
iajs-2710	108	14	stopping	stopping	NOUN
iajs-2710	108	15	criterion	criterion	NOUN
iajs-2710	108	16	is	be	AUX
iajs-2710	108	17	reached	reach	VERB
iajs-2710	108	18	orthogonal	orthogonal	ADJ
iajs-2710	108	19	lines	line	NOUN
iajs-2710	108	20	are	be	AUX
iajs-2710	108	21	used	use	VERB
iajs-2710	108	22	to	to	PART
iajs-2710	108	23	calculate	calculate	VERB
iajs-2710	108	24	the	the	DET
iajs-2710	108	25	corners	corner	NOUN
iajs-2710	108	26	of	of	ADP
iajs-2710	108	27	the	the	DET
iajs-2710	108	28	objects	object	NOUN
iajs-2710	108	29	and	and	CCONJ
iajs-2710	108	30	the	the	DET
iajs-2710	108	31	line	line	NOUN
iajs-2710	108	32	segments	segment	NOUN
iajs-2710	108	33	that	that	PRON
iajs-2710	108	34	form	form	VERB
iajs-2710	108	35	the	the	DET
iajs-2710	108	36	rectangle	rectangle	NOUN
iajs-2710	108	37	.	.	PUNCT
iajs-2710	109	1	to	to	PART
iajs-2710	109	2	eliminate	eliminate	VERB
iajs-2710	109	3	wrong	wrong	ADJ
iajs-2710	109	4	line	line	NOUN
iajs-2710	109	5	segments	segment	NOUN
iajs-2710	109	6	,	,	PUNCT
iajs-2710	109	7	the	the	DET
iajs-2710	109	8	median	median	NOUN
iajs-2710	109	9	and	and	CCONJ
iajs-2710	109	10	mean	mean	VERB
iajs-2710	109	11	color	color	NOUN
iajs-2710	109	12	differences	difference	NOUN
iajs-2710	109	13	between	between	ADP
iajs-2710	109	14	foreground	foreground	NOUN
iajs-2710	109	15	and	and	CCONJ
iajs-2710	109	16	background	background	NOUN
iajs-2710	109	17	along	along	ADP
iajs-2710	109	18	the	the	DET
iajs-2710	109	19	line	line	NOUN
iajs-2710	109	20	segments	segment	NOUN
iajs-2710	109	21	are	be	AUX
iajs-2710	109	22	calculated	calculate	VERB
iajs-2710	109	23	and	and	CCONJ
iajs-2710	109	24	used	use	VERB
iajs-2710	109	25	to	to	PART
iajs-2710	109	26	derive	derive	VERB
iajs-2710	109	27	the	the	DET
iajs-2710	109	28	parameters	parameter	NOUN
iajs-2710	109	29	of	of	ADP
iajs-2710	109	30	a	a	DET
iajs-2710	109	31	score	score	NOUN
iajs-2710	109	32	function	function	NOUN
iajs-2710	109	33	from	from	ADP
iajs-2710	109	34	many	many	ADJ
iajs-2710	109	35	automatically	automatically	ADV
iajs-2710	109	36	generated	generate	VERB
iajs-2710	109	37	images	image	NOUN
iajs-2710	109	38	.	.	PUNCT
iajs-2710	110	1	next	next	ADV
iajs-2710	110	2	,	,	PUNCT
iajs-2710	110	3	for	for	ADP
iajs-2710	110	4	each	each	DET
iajs-2710	110	5	rectangle	rectangle	ADJ
iajs-2710	110	6	candidate	candidate	NOUN
iajs-2710	110	7	,	,	PUNCT
iajs-2710	110	8	the	the	DET
iajs-2710	110	9	same	same	ADJ
iajs-2710	110	10	values	value	NOUN
iajs-2710	110	11	used	use	VERB
iajs-2710	110	12	for	for	ADP
iajs-2710	110	13	line	line	NOUN
iajs-2710	110	14	fitting	fitting	ADJ
iajs-2710	110	15	and	and	CCONJ
iajs-2710	110	16	a	a	DET
iajs-2710	110	17	score	score	NOUN
iajs-2710	110	18	that	that	PRON
iajs-2710	110	19	relates	relate	VERB
iajs-2710	110	20	to	to	ADP
iajs-2710	110	21	the	the	DET
iajs-2710	110	22	number	number	NOUN
iajs-2710	110	23	of	of	ADP
iajs-2710	110	24	background	background	NOUN
iajs-2710	110	25	pixels	pixel	NOUN
iajs-2710	110	26	in	in	ADP
iajs-2710	110	27	the	the	DET
iajs-2710	110	28	rectangle	rectangle	NOUN
iajs-2710	110	29	are	be	AUX
iajs-2710	110	30	input	input	VERB
iajs-2710	110	31	into	into	ADP
iajs-2710	110	32	a	a	DET
iajs-2710	110	33	support	support	NOUN
iajs-2710	110	34	vector	vector	NOUN
iajs-2710	110	35	machine	machine	NOUN
iajs-2710	110	36	(	(	PUNCT
iajs-2710	110	37	svm	svm	ADJ
iajs-2710	110	38	)	)	PUNCT
iajs-2710	110	39	classifier	classifier	NOUN
iajs-2710	110	40	,	,	PUNCT
iajs-2710	110	41	which	which	PRON
iajs-2710	110	42	determines	determine	VERB
iajs-2710	110	43	if	if	SCONJ
iajs-2710	110	44	the	the	DET
iajs-2710	110	45	rectangle	rectangle	ADJ
iajs-2710	110	46	candidate	candidate	NOUN
iajs-2710	110	47	is	be	AUX
iajs-2710	110	48	a	a	DET
iajs-2710	110	49	proper	proper	ADJ
iajs-2710	110	50	object	object	NOUN
iajs-2710	110	51	or	or	CCONJ
iajs-2710	110	52	not	not	PART
iajs-2710	110	53	.	.	PUNCT
iajs-2710	111	1	to	to	PART
iajs-2710	111	2	find	find	VERB
iajs-2710	111	3	better	well	ADJ
iajs-2710	111	4	matches	match	NOUN
iajs-2710	111	5	,	,	PUNCT
iajs-2710	111	6	the	the	DET
iajs-2710	111	7	rectangle	rectangle	NOUN
iajs-2710	111	8	candidates	candidate	NOUN
iajs-2710	111	9	are	be	AUX
iajs-2710	111	10	also	also	ADV
iajs-2710	111	11	shifted	shift	VERB
iajs-2710	111	12	in	in	ADP
iajs-2710	111	13	the	the	DET
iajs-2710	111	14	local	local	ADJ
iajs-2710	111	15	neighborhood	neighborhood	NOUN
iajs-2710	111	16	.	.	PUNCT
iajs-2710	112	1	a	a	DET
iajs-2710	112	2	candidate	candidate	NOUN
iajs-2710	112	3	is	be	AUX
iajs-2710	112	4	accepted	accept	VERB
iajs-2710	112	5	when	when	SCONJ
iajs-2710	112	6	at	at	ADP
iajs-2710	112	7	most	most	ADV
iajs-2710	112	8	10	10	NUM
iajs-2710	112	9	%	%	NOUN
iajs-2710	112	10	of	of	ADP
iajs-2710	112	11	the	the	DET
iajs-2710	112	12	pixels	pixel	NOUN
iajs-2710	112	13	inside	inside	ADP
iajs-2710	112	14	the	the	DET
iajs-2710	112	15	rectangle	rectangle	NOUN
iajs-2710	112	16	are	be	AUX
iajs-2710	112	17	classified	classify	VERB
iajs-2710	112	18	as	as	ADP
iajs-2710	112	19	background	background	NOUN
iajs-2710	112	20	.	.	PUNCT
iajs-2710	113	1	in	in	ADP
iajs-2710	113	2	summary	summary	NOUN
iajs-2710	113	3	,	,	PUNCT
iajs-2710	113	4	all	all	DET
iajs-2710	113	5	approaches	approach	NOUN
iajs-2710	113	6	are	be	AUX
iajs-2710	113	7	specifically	specifically	ADV
iajs-2710	113	8	designed	design	VERB
iajs-2710	113	9	to	to	PART
iajs-2710	113	10	be	be	AUX
iajs-2710	113	11	fast	fast	ADJ
iajs-2710	113	12	and	and	CCONJ
iajs-2710	113	13	detect	detect	VERB
iajs-2710	113	14	potentially	potentially	ADV
iajs-2710	113	15	imperfect	imperfect	ADJ
iajs-2710	113	16	rectangular	rectangular	ADJ
iajs-2710	113	17	objects	object	NOUN
iajs-2710	113	18	with	with	ADP
iajs-2710	113	19	possible	possible	ADJ
iajs-2710	113	20	overlap	overlap	NOUN
iajs-2710	113	21	or	or	CCONJ
iajs-2710	113	22	missing	miss	VERB
iajs-2710	113	23	corners	corner	NOUN
iajs-2710	113	24	.	.	PUNCT
iajs-2710	114	1	however	however	ADV
iajs-2710	114	2	,	,	PUNCT
iajs-2710	114	3	they	they	PRON
iajs-2710	114	4	rely	rely	VERB
iajs-2710	114	5	on	on	ADP
iajs-2710	114	6	the	the	DET
iajs-2710	114	7	uniform	uniform	ADJ
iajs-2710	114	8	background	background	NOUN
iajs-2710	114	9	color	color	NOUN
iajs-2710	114	10	,	,	PUNCT
iajs-2710	114	11	which	which	PRON
iajs-2710	114	12	also	also	ADV
iajs-2710	114	13	must	must	AUX
iajs-2710	114	14	be	be	AUX
iajs-2710	114	15	distinct	distinct	ADJ
iajs-2710	114	16	from	from	ADP
iajs-2710	114	17	the	the	DET
iajs-2710	114	18	majority	majority	NOUN
iajs-2710	114	19	of	of	ADP
iajs-2710	114	20	the	the	DET
iajs-2710	114	21	content	content	NOUN
iajs-2710	114	22	found	find	VERB
iajs-2710	114	23	in	in	ADP
iajs-2710	114	24	the	the	DET
iajs-2710	114	25	foreground	foreground	NOUN
iajs-2710	114	26	objects	object	NOUN
iajs-2710	114	27	.	.	PUNCT
iajs-2710	115	1	our	our	PRON
iajs-2710	115	2	application	application	NOUN
iajs-2710	115	3	usually	usually	ADV
iajs-2710	115	4	does	do	AUX
iajs-2710	115	5	not	not	PART
iajs-2710	115	6	satisfy	satisfy	VERB
iajs-2710	115	7	both	both	DET
iajs-2710	115	8	conditions	condition	NOUN
iajs-2710	115	9	,	,	PUNCT
iajs-2710	115	10	as	as	SCONJ
iajs-2710	115	11	brains	brain	NOUN
iajs-2710	115	12	are	be	AUX
iajs-2710	115	13	mounted	mount	VERB
iajs-2710	115	14	on	on	ADP
iajs-2710	115	15	arbitrary	arbitrary	ADJ
iajs-2710	115	16	background	background	NOUN
iajs-2710	115	17	,	,	PUNCT
iajs-2710	115	18	and	and	CCONJ
iajs-2710	115	19	unknown	unknown	ADJ
iajs-2710	115	20	lighting	lighting	NOUN
iajs-2710	115	21	conditions	condition	NOUN
iajs-2710	115	22	may	may	AUX
iajs-2710	115	23	cause	cause	VERB
iajs-2710	115	24	significant	significant	ADJ
iajs-2710	115	25	brightness	brightness	NOUN
iajs-2710	115	26	changes	change	NOUN
iajs-2710	115	27	.	.	PUNCT
iajs-2710	116	1	also	also	ADV
iajs-2710	116	2	,	,	PUNCT
iajs-2710	116	3	the	the	DET
iajs-2710	116	4	color	color	NOUN
iajs-2710	116	5	of	of	ADP
iajs-2710	116	6	the	the	DET
iajs-2710	116	7	brain	brain	NOUN
iajs-2710	116	8	is	be	AUX
iajs-2710	116	9	not	not	PART
iajs-2710	116	10	necessarily	necessarily	ADV
iajs-2710	116	11	different	different	ADJ
iajs-2710	116	12	from	from	ADP
iajs-2710	116	13	the	the	DET
iajs-2710	116	14	background	background	NOUN
iajs-2710	116	15	.	.	PUNCT
iajs-2710	117	1	hence	hence	ADV
iajs-2710	117	2	,	,	PUNCT
iajs-2710	117	3	the	the	DET
iajs-2710	117	4	only	only	ADJ
iajs-2710	117	5	way	way	NOUN
iajs-2710	117	6	of	of	ADP
iajs-2710	117	7	distinguishing	distinguish	VERB
iajs-2710	117	8	them	they	PRON
iajs-2710	117	9	from	from	ADP
iajs-2710	117	10	the	the	DET
iajs-2710	117	11	background	background	NOUN
iajs-2710	117	12	is	be	AUX
iajs-2710	117	13	by	by	ADP
iajs-2710	117	14	the	the	DET
iajs-2710	117	15	border	border	NOUN
iajs-2710	117	16	of	of	ADP
iajs-2710	117	17	the	the	DET
iajs-2710	117	18	brain	brain	NOUN
iajs-2710	117	19	3.methodology	3.methodology	NUM
iajs-2710	117	20	an	an	DET
iajs-2710	117	21	efficient	efficient	ADJ
iajs-2710	117	22	rectangle	rectangle	NOUN
iajs-2710	117	23	detection	detection	NOUN
iajs-2710	117	24	system	system	NOUN
iajs-2710	117	25	is	be	AUX
iajs-2710	117	26	intended	intend	VERB
iajs-2710	117	27	to	to	PART
iajs-2710	117	28	be	be	AUX
iajs-2710	117	29	used	use	VERB
iajs-2710	117	30	on	on	ADP
iajs-2710	117	31	mobile	mobile	ADJ
iajs-2710	117	32	devices	device	NOUN
iajs-2710	117	33	.	.	PUNCT
iajs-2710	118	1	first	first	ADV
iajs-2710	118	2	,	,	PUNCT
iajs-2710	118	3	they	they	PRON
iajs-2710	118	4	extract	extract	VERB
iajs-2710	118	5	the	the	DET
iajs-2710	118	6	edge	edge	NOUN
iajs-2710	118	7	map	map	NOUN
iajs-2710	118	8	using	use	VERB
iajs-2710	118	9	the	the	DET
iajs-2710	118	10	canny	canny	ADJ
iajs-2710	118	11	edge	edge	NOUN
iajs-2710	118	12	detector	detector	NOUN
iajs-2710	118	13	.	.	PUNCT
iajs-2710	119	1	the	the	DET
iajs-2710	119	2	threshold	threshold	NOUN
iajs-2710	119	3	parameters	parameter	NOUN
iajs-2710	119	4	are	be	AUX
iajs-2710	119	5	automatically	automatically	ADV
iajs-2710	119	6	selected	select	VERB
iajs-2710	119	7	.	.	PUNCT
iajs-2710	120	1	to	to	PART
iajs-2710	120	2	improve	improve	VERB
iajs-2710	120	3	the	the	DET
iajs-2710	120	4	robustness	robustness	NOUN
iajs-2710	120	5	and	and	CCONJ
iajs-2710	120	6	increase	increase	VERB
iajs-2710	120	7	speed	speed	NOUN
iajs-2710	120	8	,	,	PUNCT
iajs-2710	120	9	all	all	DET
iajs-2710	120	10	edges	edge	NOUN
iajs-2710	120	11	produced	produce	VERB
iajs-2710	120	12	by	by	ADP
iajs-2710	120	13	text	text	NOUN
iajs-2710	120	14	are	be	AUX
iajs-2710	120	15	removed	remove	VERB
iajs-2710	120	16	.	.	PUNCT
iajs-2710	121	1	consequently	consequently	ADV
iajs-2710	121	2	,	,	PUNCT
iajs-2710	121	3	a	a	DET
iajs-2710	121	4	lower	low	ADJ
iajs-2710	121	5	number	number	NOUN
iajs-2710	121	6	of	of	ADP
iajs-2710	121	7	lines	line	NOUN
iajs-2710	121	8	need	need	VERB
iajs-2710	121	9	to	to	PART
iajs-2710	121	10	be	be	AUX
iajs-2710	121	11	processed	process	VERB
iajs-2710	121	12	.	.	PUNCT
iajs-2710	122	1	they	they	PRON
iajs-2710	122	2	do	do	VERB
iajs-2710	122	3	this	this	PRON
iajs-2710	122	4	by	by	ADP
iajs-2710	122	5	extracting	extract	VERB
iajs-2710	122	6	connected	connected	ADJ
iajs-2710	122	7	components	component	NOUN
iajs-2710	122	8	and	and	CCONJ
iajs-2710	122	9	calculating	calculate	VERB
iajs-2710	122	10	the	the	DET
iajs-2710	122	11	bounding	bounding	NOUN
iajs-2710	122	12	box	box	NOUN
iajs-2710	122	13	for	for	ADP
iajs-2710	122	14	each	each	DET
iajs-2710	122	15	one	one	NUM
iajs-2710	122	16	.	.	PUNCT
iajs-2710	123	1	the	the	DET
iajs-2710	123	2	ibn	ibn	PROPN
iajs-2710	123	3	al	al	PROPN
iajs-2710	123	4	-	-	PUNCT
iajs-2710	123	5	haitham	haitham	PROPN
iajs-2710	123	6	jour	jour	X
iajs-2710	123	7	.	.	PROPN
iajs-2710	123	8	for	for	ADP
iajs-2710	123	9	pure	pure	ADJ
iajs-2710	123	10	&	&	CCONJ
iajs-2710	123	11	appl	appl	PROPN
iajs-2710	123	12	.	.	PUNCT
iajs-2710	124	1	sci	sci	PROPN
iajs-2710	124	2	.	.	PROPN
iajs-2710	125	1	34(4)2021	34(4)2021	NUM
iajs-2710	125	2	135	135	NUM
iajs-2710	125	3	aspect	aspect	NOUN
iajs-2710	125	4	ratio	ratio	NOUN
iajs-2710	125	5	,	,	PUNCT
iajs-2710	125	6	height	height	NOUN
iajs-2710	125	7	of	of	ADP
iajs-2710	125	8	the	the	DET
iajs-2710	125	9	bounding	bounding	NOUN
iajs-2710	125	10	box	box	NOUN
iajs-2710	125	11	,	,	PUNCT
iajs-2710	125	12	and	and	CCONJ
iajs-2710	125	13	a	a	DET
iajs-2710	125	14	number	number	NOUN
iajs-2710	125	15	of	of	ADP
iajs-2710	125	16	pixels	pixel	NOUN
iajs-2710	125	17	about	about	ADP
iajs-2710	125	18	the	the	DET
iajs-2710	125	19	bounding	bounding	NOUN
iajs-2710	125	20	area	area	NOUN
iajs-2710	125	21	are	be	AUX
iajs-2710	125	22	used	use	VERB
iajs-2710	125	23	as	as	ADP
iajs-2710	125	24	filtering	filter	VERB
iajs-2710	125	25	criteria	criterion	NOUN
iajs-2710	125	26	next	next	ADV
iajs-2710	125	27	,	,	PUNCT
iajs-2710	125	28	the	the	DET
iajs-2710	125	29	filtered	filter	VERB
iajs-2710	125	30	image	image	NOUN
iajs-2710	125	31	is	be	AUX
iajs-2710	125	32	used	use	VERB
iajs-2710	125	33	to	to	PART
iajs-2710	125	34	extract	extract	VERB
iajs-2710	125	35	lines	line	NOUN
iajs-2710	125	36	by	by	ADP
iajs-2710	125	37	applying	apply	VERB
iajs-2710	125	38	the	the	DET
iajs-2710	125	39	hough	hough	PROPN
iajs-2710	125	40	transform	transform	NOUN
iajs-2710	125	41	.	.	PUNCT
iajs-2710	126	1	suppose	suppose	VERB
iajs-2710	126	2	their	their	PRON
iajs-2710	126	3	angle	angle	NOUN
iajs-2710	126	4	does	do	AUX
iajs-2710	126	5	not	not	PART
iajs-2710	126	6	differ	differ	VERB
iajs-2710	126	7	more	more	ADJ
iajs-2710	126	8	than	than	ADP
iajs-2710	126	9	fourteen	fourteen	NUM
iajs-2710	126	10	degrees	degree	NOUN
iajs-2710	126	11	,	,	PUNCT
iajs-2710	126	12	two	two	NUM
iajs-2710	126	13	lines	line	NOUN
iajs-2710	126	14	from	from	ADP
iajs-2710	126	15	a	a	DET
iajs-2710	126	16	line	line	NOUN
iajs-2710	126	17	bundle	bundle	NOUN
iajs-2710	126	18	,	,	PUNCT
iajs-2710	126	19	accounting	account	VERB
iajs-2710	126	20	for	for	ADP
iajs-2710	126	21	some	some	DET
iajs-2710	126	22	perspective	perspective	ADJ
iajs-2710	126	23	distortion	distortion	NOUN
iajs-2710	126	24	.	.	PUNCT
iajs-2710	127	1	the	the	DET
iajs-2710	127	2	authors	author	NOUN
iajs-2710	127	3	then	then	ADV
iajs-2710	127	4	group	group	NOUN
iajs-2710	127	5	line	line	NOUN
iajs-2710	127	6	bundles	bundle	NOUN
iajs-2710	127	7	to	to	AUX
iajs-2710	127	8	rectangle	rectangle	VERB
iajs-2710	127	9	hypotheses	hypothesis	NOUN
iajs-2710	127	10	if	if	SCONJ
iajs-2710	127	11	all	all	DET
iajs-2710	127	12	line	line	NOUN
iajs-2710	127	13	intersections	intersection	NOUN
iajs-2710	127	14	are	be	AUX
iajs-2710	127	15	inside	inside	ADP
iajs-2710	127	16	the	the	DET
iajs-2710	127	17	image	image	NOUN
iajs-2710	127	18	.	.	PUNCT
iajs-2710	128	1	finally	finally	ADV
iajs-2710	128	2	,	,	PUNCT
iajs-2710	128	3	they	they	PRON
iajs-2710	128	4	compute	compute	VERB
iajs-2710	128	5	the	the	DET
iajs-2710	128	6	edge	edge	NOUN
iajs-2710	128	7	support	support	NOUN
iajs-2710	128	8	on	on	ADP
iajs-2710	128	9	the	the	DET
iajs-2710	128	10	dilated	dilate	VERB
iajs-2710	128	11	edge	edge	NOUN
iajs-2710	128	12	image	image	NOUN
iajs-2710	128	13	,	,	PUNCT
iajs-2710	128	14	where	where	SCONJ
iajs-2710	128	15	the	the	DET
iajs-2710	128	16	most	most	ADV
iajs-2710	128	17	dominant	dominant	ADJ
iajs-2710	128	18	rectangle	rectangle	NOUN
iajs-2710	128	19	hypothesis	hypothesis	NOUN
iajs-2710	128	20	with	with	ADP
iajs-2710	128	21	the	the	DET
iajs-2710	128	22	highest	high	ADJ
iajs-2710	128	23	edge	edge	NOUN
iajs-2710	128	24	support	support	NOUN
iajs-2710	128	25	is	be	AUX
iajs-2710	128	26	the	the	DET
iajs-2710	128	27	resulting	result	VERB
iajs-2710	128	28	rectangle	rectangle	NOUN
iajs-2710	128	29	.	.	PUNCT
iajs-2710	129	1	the	the	DET
iajs-2710	129	2	edge	edge	NOUN
iajs-2710	129	3	map	map	NOUN
iajs-2710	129	4	is	be	AUX
iajs-2710	129	5	dilated	dilate	VERB
iajs-2710	129	6	to	to	PART
iajs-2710	129	7	increase	increase	VERB
iajs-2710	129	8	robustness	robustness	NOUN
iajs-2710	129	9	against	against	ADP
iajs-2710	129	10	camera	camera	NOUN
iajs-2710	129	11	distortions	distortion	NOUN
iajs-2710	129	12	,	,	PUNCT
iajs-2710	129	13	causing	cause	VERB
iajs-2710	129	14	lines	line	NOUN
iajs-2710	129	15	that	that	PRON
iajs-2710	129	16	are	be	AUX
iajs-2710	129	17	not	not	PART
iajs-2710	129	18	completely	completely	ADV
iajs-2710	129	19	straight	straight	ADJ
iajs-2710	129	20	.	.	PUNCT
iajs-2710	130	1	a	a	DET
iajs-2710	130	2	more	more	ADV
iajs-2710	130	3	generic	generic	ADJ
iajs-2710	130	4	approach	approach	NOUN
iajs-2710	130	5	to	to	ADP
iajs-2710	130	6	extracting	extract	VERB
iajs-2710	130	7	rectangles	rectangle	NOUN
iajs-2710	130	8	using	use	VERB
iajs-2710	130	9	a	a	DET
iajs-2710	130	10	windowed	windowed	ADJ
iajs-2710	130	11	hough	hough	NOUN
iajs-2710	130	12	transform	transform	NOUN
iajs-2710	130	13	is	be	AUX
iajs-2710	130	14	proposed	propose	VERB
iajs-2710	130	15	.	.	PUNCT
iajs-2710	131	1	they	they	PRON
iajs-2710	131	2	use	use	VERB
iajs-2710	131	3	a	a	DET
iajs-2710	131	4	ring	ring	NOUN
iajs-2710	131	5	-	-	PUNCT
iajs-2710	131	6	shaped	shape	VERB
iajs-2710	131	7	sliding	sliding	NOUN
iajs-2710	131	8	window	window	NOUN
iajs-2710	131	9	,	,	PUNCT
iajs-2710	131	10	where	where	SCONJ
iajs-2710	131	11	the	the	DET
iajs-2710	131	12	outer	outer	ADJ
iajs-2710	131	13	diameter	diameter	NOUN
iajs-2710	131	14	approximately	approximately	ADV
iajs-2710	131	15	equals	equal	VERB
iajs-2710	131	16	the	the	DET
iajs-2710	131	17	size	size	NOUN
iajs-2710	131	18	of	of	ADP
iajs-2710	131	19	the	the	DET
iajs-2710	131	20	largest	large	ADJ
iajs-2710	131	21	and	and	CCONJ
iajs-2710	131	22	the	the	DET
iajs-2710	131	23	inner	inner	ADJ
iajs-2710	131	24	diameter	diameter	NOUN
iajs-2710	131	25	the	the	DET
iajs-2710	131	26	size	size	NOUN
iajs-2710	131	27	of	of	ADP
iajs-2710	131	28	the	the	DET
iajs-2710	131	29	smallest	small	ADJ
iajs-2710	131	30	rectangle	rectangle	NOUN
iajs-2710	131	31	that	that	PRON
iajs-2710	131	32	can	can	AUX
iajs-2710	131	33	be	be	AUX
iajs-2710	131	34	detected	detect	VERB
iajs-2710	131	35	.	.	PUNCT
iajs-2710	132	1	next	next	ADV
iajs-2710	132	2	,	,	PUNCT
iajs-2710	132	3	the	the	DET
iajs-2710	132	4	hough	hough	PROPN
iajs-2710	132	5	transform	transform	NOUN
iajs-2710	132	6	of	of	ADP
iajs-2710	132	7	the	the	DET
iajs-2710	132	8	region	region	NOUN
iajs-2710	132	9	under	under	ADP
iajs-2710	132	10	the	the	DET
iajs-2710	132	11	sliding	slide	VERB
iajs-2710	132	12	window	window	NOUN
iajs-2710	132	13	is	be	AUX
iajs-2710	132	14	calculated	calculate	VERB
iajs-2710	132	15	,	,	PUNCT
iajs-2710	132	16	where	where	SCONJ
iajs-2710	132	17	the	the	DET
iajs-2710	132	18	discretization	discretization	NOUN
iajs-2710	132	19	depends	depend	VERB
iajs-2710	132	20	on	on	ADP
iajs-2710	132	21	the	the	DET
iajs-2710	132	22	outer	outer	ADJ
iajs-2710	132	23	ring	ring	NOUN
iajs-2710	132	24	diameter	diameter	NOUN
iajs-2710	132	25	.	.	PUNCT
iajs-2710	133	1	to	to	PART
iajs-2710	133	2	detect	detect	VERB
iajs-2710	133	3	the	the	DET
iajs-2710	133	4	peaks	peak	NOUN
iajs-2710	133	5	in	in	ADP
iajs-2710	133	6	a	a	DET
iajs-2710	133	7	robust	robust	ADJ
iajs-2710	133	8	manner	manner	NOUN
iajs-2710	133	9	,	,	PUNCT
iajs-2710	133	10	a	a	DET
iajs-2710	133	11	modified	modify	VERB
iajs-2710	133	12	butterfly	butterfly	NOUN
iajs-2710	133	13	evaluator	evaluator	NOUN
iajs-2710	133	14	is	be	AUX
iajs-2710	133	15	applied	apply	VERB
iajs-2710	133	16	to	to	ADP
iajs-2710	133	17	the	the	DET
iajs-2710	133	18	accumulator	accumulator	NOUN
iajs-2710	133	19	.	.	PUNCT
iajs-2710	134	1	to	to	PART
iajs-2710	134	2	retrieve	retrieve	VERB
iajs-2710	134	3	the	the	DET
iajs-2710	134	4	lines	line	NOUN
iajs-2710	134	5	,	,	PUNCT
iajs-2710	134	6	the	the	DET
iajs-2710	134	7	accumulator	accumulator	NOUN
iajs-2710	134	8	is	be	AUX
iajs-2710	134	9	pnsr	pnsr	VERB
iajs-2710	134	10	,	,	PUNCT
iajs-2710	134	11	as	as	SCONJ
iajs-2710	134	12	shown	show	VERB
iajs-2710	134	13	in	in	ADP
iajs-2710	134	14	equation	equation	NOUN
iajs-2710	134	15	(	(	PUNCT
iajs-2710	134	16	1	1	NUM
iajs-2710	134	17	)	)	PUNCT
iajs-2710	134	18	down	down	ADV
iajs-2710	134	19	below	below	ADV
iajs-2710	134	20	.	.	PUNCT
iajs-2710	135	1	𝑃𝑁𝑆𝑅	𝑃𝑁𝑆𝑅	NOUN
iajs-2710	135	2	=	=	PUNCT
iajs-2710	135	3	𝑚𝑎𝑥𝑖,𝑡|𝑀𝑅𝐼|𝑚𝑜𝑑𝑒𝑙	𝑚𝑎𝑥𝑖,𝑡|𝑀𝑅𝐼|𝑚𝑜𝑑𝑒𝑙	PROPN
iajs-2710	135	4	𝑛𝑜𝑖𝑠𝑒𝑐𝑙𝑒𝑎𝑛+𝑡𝑒𝑠𝑡	𝑛𝑜𝑖𝑠𝑒𝑐𝑙𝑒𝑎𝑛+𝑡𝑒𝑠𝑡	PROPN
iajs-2710	135	5	(	(	PUNCT
iajs-2710	135	6	1	1	NUM
iajs-2710	135	7	)	)	PUNCT
iajs-2710	135	8	several	several	ADJ
iajs-2710	135	9	schematic	schematic	ADJ
iajs-2710	135	10	drawings	drawing	NOUN
iajs-2710	135	11	are	be	AUX
iajs-2710	135	12	also	also	ADV
iajs-2710	135	13	frequently	frequently	ADV
iajs-2710	135	14	present	present	ADJ
iajs-2710	135	15	,	,	PUNCT
iajs-2710	135	16	which	which	PRON
iajs-2710	135	17	results	result	VERB
iajs-2710	135	18	in	in	ADP
iajs-2710	135	19	a	a	DET
iajs-2710	135	20	large	large	ADJ
iajs-2710	135	21	number	number	NOUN
iajs-2710	135	22	of	of	ADP
iajs-2710	135	23	lines	line	NOUN
iajs-2710	135	24	that	that	PRON
iajs-2710	135	25	can	can	AUX
iajs-2710	135	26	not	not	PART
iajs-2710	135	27	be	be	AUX
iajs-2710	135	28	easily	easily	ADV
iajs-2710	135	29	removed	remove	VERB
iajs-2710	135	30	beforehand	beforehand	ADV
iajs-2710	135	31	.	.	PUNCT
iajs-2710	136	1	with	with	ADP
iajs-2710	136	2	the	the	DET
iajs-2710	136	3	examined	examine	VERB
iajs-2710	136	4	approaches	approach	NOUN
iajs-2710	136	5	,	,	PUNCT
iajs-2710	136	6	grouping	group	VERB
iajs-2710	136	7	and	and	CCONJ
iajs-2710	136	8	checking	check	VERB
iajs-2710	136	9	the	the	DET
iajs-2710	136	10	hypotheses	hypothesis	NOUN
iajs-2710	136	11	is	be	AUX
iajs-2710	136	12	time	time	NOUN
iajs-2710	136	13	-	-	PUNCT
iajs-2710	136	14	consuming	consume	VERB
iajs-2710	136	15	.	.	PUNCT
iajs-2710	137	1	the	the	DET
iajs-2710	137	2	printed	print	VERB
iajs-2710	137	3	lines	line	NOUN
iajs-2710	137	4	inside	inside	ADP
iajs-2710	137	5	the	the	DET
iajs-2710	137	6	brain	brain	NOUN
iajs-2710	137	7	may	may	AUX
iajs-2710	137	8	also	also	ADV
iajs-2710	137	9	exhibit	exhibit	VERB
iajs-2710	137	10	stronger	strong	ADJ
iajs-2710	137	11	edge	edge	NOUN
iajs-2710	137	12	characteristics	characteristic	NOUN
iajs-2710	137	13	than	than	ADP
iajs-2710	137	14	the	the	DET
iajs-2710	137	15	actual	actual	ADJ
iajs-2710	137	16	separation	separation	NOUN
iajs-2710	137	17	between	between	ADP
iajs-2710	137	18	the	the	DET
iajs-2710	137	19	brain	brain	NOUN
iajs-2710	137	20	and	and	CCONJ
iajs-2710	137	21	the	the	DET
iajs-2710	137	22	background	background	NOUN
iajs-2710	137	23	,	,	PUNCT
iajs-2710	137	24	thus	thus	ADV
iajs-2710	137	25	leading	lead	VERB
iajs-2710	137	26	to	to	ADP
iajs-2710	137	27	wrong	wrong	ADJ
iajs-2710	137	28	detection	detection	NOUN
iajs-2710	137	29	results	result	NOUN
iajs-2710	137	30	.	.	PUNCT
iajs-2710	138	1	3.1	3.1	NUM
iajs-2710	138	2	software	software	NOUN
iajs-2710	138	3	implementation	implementation	NOUN
iajs-2710	138	4	an	an	DET
iajs-2710	138	5	approach	approach	NOUN
iajs-2710	138	6	that	that	PRON
iajs-2710	138	7	employs	employ	VERB
iajs-2710	138	8	deep	deep	ADJ
iajs-2710	138	9	learning	learning	NOUN
iajs-2710	138	10	approaches	approach	NOUN
iajs-2710	138	11	and	and	CCONJ
iajs-2710	138	12	applies	apply	VERB
iajs-2710	138	13	to	to	ADP
iajs-2710	138	14	forms	form	NOUN
iajs-2710	138	15	without	without	ADP
iajs-2710	138	16	tables	table	NOUN
iajs-2710	138	17	or	or	CCONJ
iajs-2710	138	18	tabular	tabular	NOUN
iajs-2710	138	19	structures	structure	NOUN
iajs-2710	138	20	is	be	AUX
iajs-2710	138	21	developed	develop	VERB
iajs-2710	138	22	in	in	ADP
iajs-2710	138	23	matlab	matlab	PROPN
iajs-2710	138	24	.	.	PUNCT
iajs-2710	139	1	they	they	PRON
iajs-2710	139	2	use	use	VERB
iajs-2710	139	3	different	different	ADJ
iajs-2710	139	4	primitives	primitive	NOUN
iajs-2710	139	5	that	that	PRON
iajs-2710	139	6	occur	occur	VERB
iajs-2710	139	7	on	on	ADP
iajs-2710	139	8	forms	form	NOUN
iajs-2710	139	9	,	,	PUNCT
iajs-2710	139	10	such	such	ADJ
iajs-2710	139	11	as	as	ADP
iajs-2710	139	12	text	text	NOUN
iajs-2710	139	13	,	,	PUNCT
iajs-2710	139	14	lines	line	NOUN
iajs-2710	139	15	,	,	PUNCT
iajs-2710	139	16	vertical	vertical	ADJ
iajs-2710	139	17	distances	distance	NOUN
iajs-2710	139	18	between	between	ADP
iajs-2710	139	19	adjacent	adjacent	ADJ
iajs-2710	139	20	rows	row	NOUN
iajs-2710	139	21	,	,	PUNCT
iajs-2710	139	22	intents	intent	NOUN
iajs-2710	139	23	(	(	PUNCT
iajs-2710	139	24	positive	positive	ADJ
iajs-2710	139	25	and	and	CCONJ
iajs-2710	139	26	negative	negative	ADJ
iajs-2710	139	27	)	)	PUNCT
iajs-2710	139	28	,	,	PUNCT
iajs-2710	139	29	and	and	CCONJ
iajs-2710	139	30	nine	nine	NUM
iajs-2710	139	31	types	type	NOUN
iajs-2710	139	32	of	of	ADP
iajs-2710	139	33	corners	corner	NOUN
iajs-2710	139	34	encoded	encode	VERB
iajs-2710	139	35	into	into	ADP
iajs-2710	139	36	a	a	DET
iajs-2710	139	37	string	string	NOUN
iajs-2710	139	38	by	by	ADP
iajs-2710	139	39	iterating	iterate	VERB
iajs-2710	139	40	over	over	ADP
iajs-2710	139	41	the	the	DET
iajs-2710	139	42	objects	object	NOUN
iajs-2710	139	43	that	that	PRON
iajs-2710	139	44	are	be	AUX
iajs-2710	139	45	sorted	sort	VERB
iajs-2710	139	46	by	by	ADP
iajs-2710	139	47	their	their	PRON
iajs-2710	139	48	vertical	vertical	ADJ
iajs-2710	139	49	position	position	NOUN
iajs-2710	139	50	.	.	PUNCT
iajs-2710	140	1	the	the	DET
iajs-2710	140	2	number	number	NOUN
iajs-2710	140	3	of	of	ADP
iajs-2710	140	4	common	common	ADJ
iajs-2710	140	5	tokens	token	NOUN
iajs-2710	140	6	of	of	ADP
iajs-2710	140	7	the	the	DET
iajs-2710	140	8	learned	learn	VERB
iajs-2710	140	9	blank	blank	NOUN
iajs-2710	140	10	and	and	CCONJ
iajs-2710	140	11	the	the	DET
iajs-2710	140	12	new	new	ADJ
iajs-2710	140	13	incoming	incoming	ADJ
iajs-2710	140	14	form	form	NOUN
iajs-2710	140	15	is	be	AUX
iajs-2710	140	16	counted	count	VERB
iajs-2710	140	17	with	with	ADP
iajs-2710	140	18	and	and	CCONJ
iajs-2710	140	19	without	without	ADP
iajs-2710	140	20	the	the	DET
iajs-2710	140	21	text	text	NOUN
iajs-2710	140	22	blocks	block	NOUN
iajs-2710	140	23	and	and	CCONJ
iajs-2710	140	24	combined	combine	VERB
iajs-2710	140	25	into	into	ADP
iajs-2710	140	26	a	a	DET
iajs-2710	140	27	score	score	NOUN
iajs-2710	140	28	to	to	PART
iajs-2710	140	29	match	match	VERB
iajs-2710	140	30	a	a	DET
iajs-2710	140	31	new	new	ADJ
iajs-2710	140	32	document	document	NOUN
iajs-2710	140	33	.	.	PUNCT
iajs-2710	141	1	3.2	3.2	NUM
iajs-2710	141	2	.	.	PUNCT
iajs-2710	141	3	material	material	NOUN
iajs-2710	141	4	and	and	CCONJ
iajs-2710	141	5	methods	method	NOUN
iajs-2710	141	6	a	a	DET
iajs-2710	141	7	convolutional	convolutional	ADJ
iajs-2710	141	8	neural	neural	ADJ
iajs-2710	141	9	network	network	NOUN
iajs-2710	141	10	consists	consist	VERB
iajs-2710	141	11	of	of	ADP
iajs-2710	141	12	many	many	ADJ
iajs-2710	141	13	layers	layer	NOUN
iajs-2710	141	14	,	,	PUNCT
iajs-2710	141	15	where	where	SCONJ
iajs-2710	141	16	each	each	DET
iajs-2710	141	17	layer	layer	NOUN
iajs-2710	141	18	is	be	AUX
iajs-2710	141	19	trained	train	VERB
iajs-2710	141	20	on	on	ADP
iajs-2710	141	21	a	a	DET
iajs-2710	141	22	different	different	ADJ
iajs-2710	141	23	subset	subset	NOUN
iajs-2710	141	24	of	of	ADP
iajs-2710	141	25	the	the	DET
iajs-2710	141	26	training	training	NOUN
iajs-2710	141	27	set	set	NOUN
iajs-2710	141	28	.	.	PUNCT
iajs-2710	142	1	the	the	DET
iajs-2710	142	2	elements	element	NOUN
iajs-2710	142	3	in	in	ADP
iajs-2710	142	4	the	the	DET
iajs-2710	142	5	subsets	subset	NOUN
iajs-2710	142	6	are	be	AUX
iajs-2710	142	7	generated	generate	VERB
iajs-2710	142	8	by	by	ADP
iajs-2710	142	9	bagging	bagging	NOUN
iajs-2710	142	10	,	,	PUNCT
iajs-2710	142	11	which	which	PRON
iajs-2710	142	12	chooses	choose	VERB
iajs-2710	142	13	elements	element	NOUN
iajs-2710	142	14	randomly	randomly	ADV
iajs-2710	142	15	and	and	CCONJ
iajs-2710	142	16	with	with	ADP
iajs-2710	142	17	restitution	restitution	NOUN
iajs-2710	142	18	.	.	PUNCT
iajs-2710	143	1	therefore	therefore	ADV
iajs-2710	143	2	,	,	PUNCT
iajs-2710	143	3	a	a	DET
iajs-2710	143	4	sample	sample	NOUN
iajs-2710	143	5	may	may	AUX
iajs-2710	143	6	appear	appear	VERB
iajs-2710	143	7	multiple	multiple	ADJ
iajs-2710	143	8	times	time	NOUN
iajs-2710	143	9	.	.	PUNCT
iajs-2710	144	1	when	when	SCONJ
iajs-2710	144	2	training	train	VERB
iajs-2710	144	3	the	the	DET
iajs-2710	144	4	layers	layer	NOUN
iajs-2710	144	5	,	,	PUNCT
iajs-2710	144	6	a	a	DET
iajs-2710	144	7	random	random	ADJ
iajs-2710	144	8	subset	subset	NOUN
iajs-2710	144	9	of	of	ADP
iajs-2710	144	10	the	the	DET
iajs-2710	144	11	features	feature	NOUN
iajs-2710	144	12	in	in	ADP
iajs-2710	144	13	the	the	DET
iajs-2710	144	14	feature	feature	NOUN
iajs-2710	144	15	vector	vector	NOUN
iajs-2710	144	16	is	be	AUX
iajs-2710	144	17	used	use	VERB
iajs-2710	144	18	to	to	PART
iajs-2710	144	19	split	split	VERB
iajs-2710	144	20	the	the	DET
iajs-2710	144	21	samples	sample	NOUN
iajs-2710	144	22	for	for	ADP
iajs-2710	144	23	each	each	DET
iajs-2710	144	24	node	node	NOUN
iajs-2710	144	25	.	.	PUNCT
iajs-2710	145	1	in	in	ADP
iajs-2710	145	2	our	our	PRON
iajs-2710	145	3	case	case	NOUN
iajs-2710	145	4	,	,	PUNCT
iajs-2710	145	5	the	the	DET
iajs-2710	145	6	number	number	NOUN
iajs-2710	145	7	of	of	ADP
iajs-2710	145	8	features	feature	NOUN
iajs-2710	145	9	used	use	VERB
iajs-2710	145	10	for	for	ADP
iajs-2710	145	11	the	the	DET
iajs-2710	145	12	splits	split	NOUN
iajs-2710	145	13	is	be	AUX
iajs-2710	145	14	half	half	DET
iajs-2710	145	15	the	the	DET
iajs-2710	145	16	square	square	ADJ
iajs-2710	145	17	root	root	NOUN
iajs-2710	145	18	of	of	ADP
iajs-2710	145	19	all	all	DET
iajs-2710	145	20	features	feature	NOUN
iajs-2710	145	21	.	.	PUNCT
iajs-2710	146	1	from	from	ADP
iajs-2710	146	2	all	all	DET
iajs-2710	146	3	calculated	calculate	VERB
iajs-2710	146	4	splits	split	NOUN
iajs-2710	146	5	,	,	PUNCT
iajs-2710	146	6	the	the	DET
iajs-2710	146	7	one	one	NOUN
iajs-2710	146	8	that	that	PRON
iajs-2710	146	9	causes	cause	VERB
iajs-2710	146	10	the	the	DET
iajs-2710	146	11	most	most	ADV
iajs-2710	146	12	significant	significant	ADJ
iajs-2710	146	13	decrease	decrease	NOUN
iajs-2710	146	14	of	of	ADP
iajs-2710	146	15	entropy	entropy	PROPN
iajs-2710	146	16	and	and	CCONJ
iajs-2710	146	17	,	,	PUNCT
iajs-2710	146	18	therefore	therefore	ADV
iajs-2710	146	19	,	,	PUNCT
iajs-2710	146	20	the	the	DET
iajs-2710	146	21	largest	large	ADJ
iajs-2710	146	22	information	information	NOUN
iajs-2710	146	23	gain	gain	NOUN
iajs-2710	146	24	of	of	ADP
iajs-2710	146	25	the	the	DET
iajs-2710	146	26	label	label	NOUN
iajs-2710	146	27	histogram	histogram	NOUN
iajs-2710	146	28	is	be	AUX
iajs-2710	146	29	used	use	VERB
iajs-2710	146	30	.	.	PUNCT
iajs-2710	147	1	in	in	ADP
iajs-2710	147	2	our	our	PRON
iajs-2710	147	3	case	case	NOUN
iajs-2710	147	4	,	,	PUNCT
iajs-2710	147	5	the	the	DET
iajs-2710	147	6	learning	learning	NOUN
iajs-2710	147	7	is	be	AUX
iajs-2710	147	8	completed	complete	VERB
iajs-2710	147	9	if	if	SCONJ
iajs-2710	147	10	cnn	cnn	PROPN
iajs-2710	147	11	-	-	PUNCT
iajs-2710	147	12	layers	layer	NOUN
iajs-2710	147	13	are	be	AUX
iajs-2710	147	14	generated	generate	VERB
iajs-2710	147	15	or	or	CCONJ
iajs-2710	147	16	the	the	DET
iajs-2710	147	17	estimated	estimate	VERB
iajs-2710	147	18	classification	classification	NOUN
iajs-2710	147	19	error	error	NOUN
iajs-2710	147	20	is	be	AUX
iajs-2710	147	21	smaller	small	ADJ
iajs-2710	147	22	than	than	ADP
iajs-2710	147	23	1	1	NUM
iajs-2710	147	24	%	%	NOUN
iajs-2710	147	25	.	.	PUNCT
iajs-2710	148	1	the	the	DET
iajs-2710	148	2	error	error	NOUN
iajs-2710	148	3	is	be	AUX
iajs-2710	148	4	estimated	estimate	VERB
iajs-2710	148	5	during	during	ADP
iajs-2710	148	6	training	training	NOUN
iajs-2710	148	7	by	by	ADP
iajs-2710	148	8	classifying	classify	VERB
iajs-2710	148	9	samples	sample	NOUN
iajs-2710	148	10	that	that	PRON
iajs-2710	148	11	were	be	AUX
iajs-2710	148	12	not	not	PART
iajs-2710	148	13	chosen	choose	VERB
iajs-2710	148	14	by	by	ADP
iajs-2710	148	15	the	the	DET
iajs-2710	148	16	bagging	bagging	NOUN
iajs-2710	148	17	procedure	procedure	NOUN
iajs-2710	148	18	.	.	PUNCT
iajs-2710	149	1	the	the	DET
iajs-2710	149	2	layers	layer	NOUN
iajs-2710	149	3	in	in	ADP
iajs-2710	149	4	the	the	DET
iajs-2710	149	5	ibn	ibn	PROPN
iajs-2710	149	6	al	al	PROPN
iajs-2710	149	7	-	-	PUNCT
iajs-2710	149	8	haitham	haitham	PROPN
iajs-2710	149	9	jour	jour	X
iajs-2710	149	10	.	.	PROPN
iajs-2710	150	1	for	for	ADP
iajs-2710	150	2	pure	pure	ADJ
iajs-2710	150	3	&	&	CCONJ
iajs-2710	150	4	appl	appl	PROPN
iajs-2710	150	5	.	.	PUNCT
iajs-2710	151	1	sci	sci	PROPN
iajs-2710	151	2	.	.	PROPN
iajs-2710	152	1	34(4)2021	34(4)2021	NUM
iajs-2710	152	2	136	136	NUM
iajs-2710	152	3	convolutional	convolutional	ADJ
iajs-2710	152	4	neural	neural	ADJ
iajs-2710	152	5	network	network	NOUN
iajs-2710	152	6	are	be	AUX
iajs-2710	152	7	not	not	PART
iajs-2710	152	8	pruned	prune	VERB
iajs-2710	152	9	.	.	PUNCT
iajs-2710	153	1	for	for	ADP
iajs-2710	153	2	classification	classification	NOUN
iajs-2710	153	3	,	,	PUNCT
iajs-2710	153	4	each	each	DET
iajs-2710	153	5	tree	tree	NOUN
iajs-2710	153	6	generates	generate	VERB
iajs-2710	153	7	a	a	DET
iajs-2710	153	8	result	result	NOUN
iajs-2710	153	9	from	from	ADP
iajs-2710	153	10	the	the	DET
iajs-2710	153	11	input	input	NOUN
iajs-2710	153	12	data	datum	NOUN
iajs-2710	153	13	,	,	PUNCT
iajs-2710	153	14	and	and	CCONJ
iajs-2710	153	15	a	a	DET
iajs-2710	153	16	majority	majority	NOUN
iajs-2710	153	17	vote	vote	NOUN
iajs-2710	153	18	is	be	AUX
iajs-2710	153	19	used	use	VERB
iajs-2710	153	20	to	to	PART
iajs-2710	153	21	derive	derive	VERB
iajs-2710	153	22	the	the	DET
iajs-2710	153	23	final	final	ADJ
iajs-2710	153	24	class	class	NOUN
iajs-2710	153	25	label	label	NOUN
iajs-2710	153	26	.	.	PUNCT
iajs-2710	154	1	figure	figure	NOUN
iajs-2710	154	2	3	3	NUM
iajs-2710	154	3	:	:	PUNCT
iajs-2710	154	4	architecture	architecture	NOUN
iajs-2710	154	5	of	of	ADP
iajs-2710	154	6	neural	neural	ADJ
iajs-2710	154	7	network	network	NOUN
iajs-2710	154	8	approach	approach	NOUN
iajs-2710	154	9	for	for	ADP
iajs-2710	154	10	the	the	DET
iajs-2710	154	11	segmentation	segmentation	NOUN
iajs-2710	154	12	of	of	ADP
iajs-2710	154	13	mri	mri	NOUN
iajs-2710	154	14	samples	sample	NOUN
iajs-2710	154	15	.	.	PUNCT
iajs-2710	155	1	it	it	PRON
iajs-2710	155	2	is	be	AUX
iajs-2710	155	3	shown	show	VERB
iajs-2710	155	4	in	in	ADP
iajs-2710	155	5	figure	figure	NOUN
iajs-2710	155	6	3	3	NUM
iajs-2710	155	7	that	that	DET
iajs-2710	155	8	architecture	architecture	NOUN
iajs-2710	155	9	of	of	ADP
iajs-2710	155	10	the	the	DET
iajs-2710	155	11	neural	neural	ADJ
iajs-2710	155	12	network	network	NOUN
iajs-2710	155	13	approach	approach	NOUN
iajs-2710	155	14	for	for	ADP
iajs-2710	155	15	the	the	DET
iajs-2710	155	16	segmentation	segmentation	NOUN
iajs-2710	155	17	of	of	ADP
iajs-2710	155	18	mri	mri	NOUN
iajs-2710	155	19	samples	sample	NOUN
iajs-2710	155	20	we	we	PRON
iajs-2710	155	21	use	use	VERB
iajs-2710	155	22	convolutional	convolutional	ADJ
iajs-2710	155	23	neural	neural	ADJ
iajs-2710	155	24	networks	network	NOUN
iajs-2710	155	25	because	because	SCONJ
iajs-2710	155	26	they	they	PRON
iajs-2710	155	27	have	have	VERB
iajs-2710	155	28	several	several	ADJ
iajs-2710	155	29	advantages	advantage	NOUN
iajs-2710	155	30	.	.	PUNCT
iajs-2710	156	1	we	we	PRON
iajs-2710	156	2	state	state	VERB
iajs-2710	156	3	that	that	SCONJ
iajs-2710	156	4	increasing	increase	VERB
iajs-2710	156	5	the	the	DET
iajs-2710	156	6	number	number	NOUN
iajs-2710	156	7	of	of	ADP
iajs-2710	156	8	layers	layer	NOUN
iajs-2710	156	9	does	do	AUX
iajs-2710	156	10	not	not	PART
iajs-2710	156	11	cause	cause	VERB
iajs-2710	156	12	overfitting	overfitte	VERB
iajs-2710	156	13	.	.	PUNCT
iajs-2710	157	1	therefore	therefore	ADV
iajs-2710	157	2	,	,	PUNCT
iajs-2710	157	3	a	a	DET
iajs-2710	157	4	large	large	ADJ
iajs-2710	157	5	number	number	NOUN
iajs-2710	157	6	can	can	AUX
iajs-2710	157	7	be	be	AUX
iajs-2710	157	8	used	use	VERB
iajs-2710	157	9	safely	safely	ADV
iajs-2710	157	10	,	,	PUNCT
iajs-2710	157	11	as	as	SCONJ
iajs-2710	157	12	it	it	PRON
iajs-2710	157	13	increases	increase	VERB
iajs-2710	157	14	accuracy	accuracy	NOUN
iajs-2710	157	15	.	.	PUNCT
iajs-2710	158	1	however	however	ADV
iajs-2710	158	2	,	,	PUNCT
iajs-2710	158	3	with	with	ADP
iajs-2710	158	4	an	an	DET
iajs-2710	158	5	increasing	increase	VERB
iajs-2710	158	6	number	number	NOUN
iajs-2710	158	7	of	of	ADP
iajs-2710	158	8	layers	layer	NOUN
iajs-2710	158	9	,	,	PUNCT
iajs-2710	158	10	the	the	DET
iajs-2710	158	11	improvement	improvement	NOUN
iajs-2710	158	12	in	in	ADP
iajs-2710	158	13	classification	classification	NOUN
iajs-2710	158	14	accuracy	accuracy	NOUN
iajs-2710	158	15	declines	decline	VERB
iajs-2710	158	16	at	at	ADP
iajs-2710	158	17	a	a	DET
iajs-2710	158	18	certain	certain	ADJ
iajs-2710	158	19	point	point	NOUN
iajs-2710	158	20	.	.	PUNCT
iajs-2710	159	1	furthermore	furthermore	ADV
iajs-2710	159	2	,	,	PUNCT
iajs-2710	159	3	a	a	DET
iajs-2710	159	4	larger	large	ADJ
iajs-2710	159	5	number	number	NOUN
iajs-2710	159	6	of	of	ADP
iajs-2710	159	7	layers	layer	NOUN
iajs-2710	159	8	increases	increase	VERB
iajs-2710	159	9	the	the	DET
iajs-2710	159	10	time	time	NOUN
iajs-2710	159	11	needed	need	VERB
iajs-2710	159	12	for	for	ADP
iajs-2710	159	13	training	training	NOUN
iajs-2710	159	14	and	and	CCONJ
iajs-2710	159	15	linearly	linearly	ADV
iajs-2710	159	16	increases	increase	VERB
iajs-2710	159	17	the	the	DET
iajs-2710	159	18	time	time	NOUN
iajs-2710	159	19	for	for	ADP
iajs-2710	159	20	classification	classification	NOUN
iajs-2710	159	21	.	.	PUNCT
iajs-2710	160	1	training	training	NOUN
iajs-2710	160	2	and	and	CCONJ
iajs-2710	160	3	classification	classification	NOUN
iajs-2710	160	4	are	be	AUX
iajs-2710	160	5	also	also	ADV
iajs-2710	160	6	speedy	speedy	ADJ
iajs-2710	160	7	since	since	SCONJ
iajs-2710	160	8	each	each	DET
iajs-2710	160	9	tree	tree	NOUN
iajs-2710	160	10	can	can	AUX
iajs-2710	160	11	be	be	AUX
iajs-2710	160	12	processed	process	VERB
iajs-2710	160	13	in	in	ADP
iajs-2710	160	14	parallel	parallel	NOUN
iajs-2710	160	15	.	.	PUNCT
iajs-2710	161	1	finally	finally	ADV
iajs-2710	161	2	,	,	PUNCT
iajs-2710	161	3	a	a	DET
iajs-2710	161	4	very	very	ADV
iajs-2710	161	5	important	important	ADJ
iajs-2710	161	6	factor	factor	NOUN
iajs-2710	161	7	is	be	AUX
iajs-2710	161	8	classification	classification	NOUN
iajs-2710	161	9	performance	performance	NOUN
iajs-2710	161	10	.	.	PUNCT
iajs-2710	162	1	supervised	supervise	VERB
iajs-2710	162	2	deep	deep	ADJ
iajs-2710	162	3	learning	learning	NOUN
iajs-2710	162	4	compares	compare	VERB
iajs-2710	162	5	some	some	DET
iajs-2710	162	6	popular	popular	ADJ
iajs-2710	162	7	approaches	approach	NOUN
iajs-2710	162	8	,	,	PUNCT
iajs-2710	162	9	including	include	VERB
iajs-2710	162	10	support	support	NOUN
iajs-2710	162	11	vector	vector	NOUN
iajs-2710	162	12	machines	machine	NOUN
iajs-2710	162	13	,	,	PUNCT
iajs-2710	162	14	boosted	boost	VERB
iajs-2710	162	15	layers	layer	NOUN
iajs-2710	162	16	,	,	PUNCT
iajs-2710	162	17	convolutional	convolutional	ADJ
iajs-2710	162	18	neural	neural	ADJ
iajs-2710	162	19	networks	network	NOUN
iajs-2710	162	20	,	,	PUNCT
iajs-2710	162	21	and	and	CCONJ
iajs-2710	162	22	others	other	NOUN
iajs-2710	162	23	.	.	PUNCT
iajs-2710	163	1	the	the	DET
iajs-2710	163	2	dataset	dataset	NOUN
iajs-2710	163	3	contains	contain	VERB
iajs-2710	163	4	mri	mri	NOUN
iajs-2710	163	5	sample	sample	NOUN
iajs-2710	163	6	for	for	ADP
iajs-2710	163	7	training	training	NOUN
iajs-2710	163	8	and	and	CCONJ
iajs-2710	163	9	testing	test	VERB
iajs-2710	163	10	the	the	DET
iajs-2710	163	11	automated	automate	VERB
iajs-2710	163	12	system	system	NOUN
iajs-2710	163	13	.	.	PUNCT
iajs-2710	164	1	the	the	DET
iajs-2710	164	2	research	research	NOUN
iajs-2710	164	3	concludes	conclude	VERB
iajs-2710	164	4	that	that	SCONJ
iajs-2710	164	5	there	there	PRON
iajs-2710	164	6	exists	exist	VERB
iajs-2710	164	7	no	no	DET
iajs-2710	164	8	universally	universally	ADV
iajs-2710	164	9	superior	superior	ADJ
iajs-2710	164	10	algorithm	algorithm	NOUN
iajs-2710	164	11	,	,	PUNCT
iajs-2710	164	12	as	as	SCONJ
iajs-2710	164	13	no	no	DET
iajs-2710	164	14	one	one	NOUN
iajs-2710	164	15	excelled	excel	VERB
iajs-2710	164	16	at	at	ADP
iajs-2710	164	17	each	each	DET
iajs-2710	164	18	problem	problem	NOUN
iajs-2710	164	19	.	.	PUNCT
iajs-2710	165	1	their	their	PRON
iajs-2710	165	2	test	test	NOUN
iajs-2710	165	3	results	result	NOUN
iajs-2710	165	4	show	show	VERB
iajs-2710	165	5	that	that	SCONJ
iajs-2710	165	6	calibrated	calibrate	VERB
iajs-2710	165	7	boosted	boost	VERB
iajs-2710	165	8	layers	layer	NOUN
iajs-2710	165	9	,	,	PUNCT
iajs-2710	165	10	convolutional	convolutional	ADJ
iajs-2710	165	11	neural	neural	ADJ
iajs-2710	165	12	networks	network	NOUN
iajs-2710	165	13	,	,	PUNCT
iajs-2710	165	14	and	and	CCONJ
iajs-2710	165	15	bagged	bag	VERB
iajs-2710	165	16	layers	layer	NOUN
iajs-2710	165	17	generally	generally	ADV
iajs-2710	165	18	deliver	deliver	VERB
iajs-2710	165	19	the	the	DET
iajs-2710	165	20	best	good	ADJ
iajs-2710	165	21	performance	performance	NOUN
iajs-2710	165	22	.	.	PUNCT
iajs-2710	166	1	the	the	DET
iajs-2710	166	2	dataset	dataset	NOUN
iajs-2710	166	3	was	be	AUX
iajs-2710	166	4	achieved	achieve	VERB
iajs-2710	166	5	from	from	ADP
iajs-2710	166	6	an	an	DET
iajs-2710	166	7	open	open	ADJ
iajs-2710	166	8	-	-	PUNCT
iajs-2710	166	9	source	source	NOUN
iajs-2710	166	10	repository	repository	NOUN
iajs-2710	166	11	;	;	PUNCT
iajs-2710	166	12	the	the	DET
iajs-2710	166	13	link	link	NOUN
iajs-2710	166	14	is	be	AUX
iajs-2710	166	15	given	give	VERB
iajs-2710	166	16	by	by	ADP
iajs-2710	166	17	:	:	PUNCT
iajs-2710	166	18	https://openfmri.org	https://openfmri.org	PROPN
iajs-2710	166	19	3.3.training	3.3.training	NUM
iajs-2710	166	20	of	of	ADP
iajs-2710	166	21	system	system	NOUN
iajs-2710	166	22	we	we	PRON
iajs-2710	166	23	evaluate	evaluate	VERB
iajs-2710	166	24	our	our	PRON
iajs-2710	166	25	use	use	NOUN
iajs-2710	166	26	of	of	ADP
iajs-2710	166	27	convolutional	convolutional	ADJ
iajs-2710	166	28	neural	neural	ADJ
iajs-2710	166	29	networks	network	NOUN
iajs-2710	166	30	.	.	PUNCT
iajs-2710	167	1	the	the	DET
iajs-2710	167	2	research	research	NOUN
iajs-2710	167	3	employs	employ	VERB
iajs-2710	167	4	maximally	maximally	ADV
iajs-2710	167	5	stable	stable	ADJ
iajs-2710	167	6	extremal	extremal	ADJ
iajs-2710	167	7	regions	region	NOUN
iajs-2710	167	8	to	to	PART
iajs-2710	167	9	locate	locate	VERB
iajs-2710	167	10	brains	brain	NOUN
iajs-2710	167	11	.	.	PUNCT
iajs-2710	168	1	the	the	DET
iajs-2710	168	2	brains	brain	NOUN
iajs-2710	168	3	are	be	AUX
iajs-2710	168	4	located	locate	VERB
iajs-2710	168	5	by	by	ADP
iajs-2710	168	6	searching	search	VERB
iajs-2710	168	7	for	for	ADP
iajs-2710	168	8	some	some	DET
iajs-2710	168	9	smaller	small	ADJ
iajs-2710	168	10	areas	area	NOUN
iajs-2710	168	11	placed	place	VERB
iajs-2710	168	12	within	within	ADP
iajs-2710	168	13	a	a	DET
iajs-2710	168	14	larger	large	ADJ
iajs-2710	168	15	one	one	NOUN
iajs-2710	168	16	.	.	PUNCT
iajs-2710	169	1	in	in	ADP
iajs-2710	169	2	cnn	cnn	PROPN
iajs-2710	169	3	,	,	PUNCT
iajs-2710	169	4	most	most	ADJ
iajs-2710	169	5	of	of	ADP
iajs-2710	169	6	these	these	DET
iajs-2710	169	7	systems	system	NOUN
iajs-2710	169	8	are	be	AUX
iajs-2710	169	9	designed	design	VERB
iajs-2710	169	10	to	to	PART
iajs-2710	169	11	detect	detect	VERB
iajs-2710	169	12	text	text	NOUN
iajs-2710	169	13	in	in	ADP
iajs-2710	169	14	natural	natural	ADJ
iajs-2710	169	15	images	image	NOUN
iajs-2710	169	16	.	.	PUNCT
iajs-2710	170	1	since	since	SCONJ
iajs-2710	170	2	our	our	PRON
iajs-2710	170	3	brain	brain	NOUN
iajs-2710	170	4	images	image	NOUN
iajs-2710	170	5	do	do	AUX
iajs-2710	170	6	not	not	PART
iajs-2710	170	7	contain	contain	VERB
iajs-2710	170	8	nearly	nearly	ADV
iajs-2710	170	9	as	as	ADV
iajs-2710	170	10	much	much	ADJ
iajs-2710	170	11	clutter	clutter	NOUN
iajs-2710	170	12	as	as	ADP
iajs-2710	170	13	natural	natural	ADJ
iajs-2710	170	14	images	image	NOUN
iajs-2710	170	15	,	,	PUNCT
iajs-2710	170	16	such	such	ADJ
iajs-2710	170	17	sophisticated	sophisticated	ADJ
iajs-2710	170	18	approaches	approach	NOUN
iajs-2710	170	19	like	like	ADP
iajs-2710	170	20	mri	mri	NOUN
iajs-2710	170	21	are	be	AUX
iajs-2710	170	22	not	not	PART
iajs-2710	170	23	needed	need	VERB
iajs-2710	170	24	.	.	PUNCT
iajs-2710	171	1	instead	instead	ADV
iajs-2710	171	2	,	,	PUNCT
iajs-2710	171	3	we	we	PRON
iajs-2710	171	4	employ	employ	VERB
iajs-2710	171	5	a	a	DET
iajs-2710	171	6	similar	similar	ADJ
iajs-2710	171	7	mri	mri	NOUN
iajs-2710	171	8	and	and	CCONJ
iajs-2710	171	9	grouping	grouping	NOUN
iajs-2710	171	10	-	-	PUNCT
iajs-2710	171	11	based	base	VERB
iajs-2710	171	12	approach	approach	NOUN
iajs-2710	171	13	to	to	PART
iajs-2710	171	14	extract	extract	VERB
iajs-2710	171	15	mri	mri	NOUN
iajs-2710	171	16	from	from	ADP
iajs-2710	171	17	samples	sample	NOUN
iajs-2710	171	18	for	for	ADP
iajs-2710	171	19	brain	brain	NOUN
iajs-2710	171	20	detection	detection	NOUN
iajs-2710	171	21	.	.	PUNCT
iajs-2710	172	1	we	we	PRON
iajs-2710	172	2	have	have	VERB
iajs-2710	172	3	the	the	DET
iajs-2710	172	4	extracted	extract	VERB
iajs-2710	172	5	up	up	ADP
iajs-2710	172	6	-	-	PUNCT
iajs-2710	172	7	right	right	ADJ
iajs-2710	172	8	brain	brain	NOUN
iajs-2710	172	9	image	image	NOUN
iajs-2710	172	10	and	and	CCONJ
iajs-2710	172	11	a	a	DET
iajs-2710	172	12	list	list	NOUN
iajs-2710	172	13	that	that	PRON
iajs-2710	172	14	contains	contain	VERB
iajs-2710	172	15	the	the	DET
iajs-2710	172	16	position	position	NOUN
iajs-2710	172	17	,	,	PUNCT
iajs-2710	172	18	content	content	NOUN
iajs-2710	172	19	type	type	NOUN
iajs-2710	172	20	,	,	PUNCT
iajs-2710	172	21	and	and	CCONJ
iajs-2710	172	22	name	name	NOUN
iajs-2710	172	23	of	of	ADP
iajs-2710	172	24	the	the	DET
iajs-2710	172	25	areas	area	NOUN
iajs-2710	172	26	that	that	PRON
iajs-2710	172	27	should	should	AUX
iajs-2710	172	28	be	be	AUX
iajs-2710	172	29	extracted	extract	VERB
iajs-2710	172	30	.	.	PUNCT
iajs-2710	173	1	since	since	SCONJ
iajs-2710	173	2	the	the	DET
iajs-2710	173	3	brain	brain	NOUN
iajs-2710	173	4	is	be	AUX
iajs-2710	173	5	not	not	PART
iajs-2710	173	6	ibn	ibn	PROPN
iajs-2710	173	7	al	al	PROPN
iajs-2710	173	8	-	-	PUNCT
iajs-2710	173	9	haitham	haitham	PROPN
iajs-2710	173	10	jour	jour	X
iajs-2710	173	11	.	.	PROPN
iajs-2710	174	1	for	for	ADP
iajs-2710	174	2	pure	pure	ADJ
iajs-2710	174	3	&	&	CCONJ
iajs-2710	174	4	appl	appl	PROPN
iajs-2710	174	5	.	.	PUNCT
iajs-2710	175	1	sci	sci	PROPN
iajs-2710	175	2	.	.	PROPN
iajs-2710	176	1	34(4)2021	34(4)2021	NUM
iajs-2710	176	2	137	137	NUM
iajs-2710	176	3	always	always	ADV
iajs-2710	176	4	extracted	extract	VERB
iajs-2710	176	5	perfectly	perfectly	ADV
iajs-2710	176	6	,	,	PUNCT
iajs-2710	176	7	we	we	PRON
iajs-2710	176	8	need	need	VERB
iajs-2710	176	9	to	to	PART
iajs-2710	176	10	adjust	adjust	VERB
iajs-2710	176	11	the	the	DET
iajs-2710	176	12	given	give	VERB
iajs-2710	176	13	areas	area	NOUN
iajs-2710	176	14	,	,	PUNCT
iajs-2710	176	15	to	to	PART
iajs-2710	176	16	align	align	VERB
iajs-2710	176	17	with	with	ADP
iajs-2710	176	18	the	the	DET
iajs-2710	176	19	brain	brain	NOUN
iajs-2710	176	20	's	's	PART
iajs-2710	176	21	content	content	NOUN
iajs-2710	176	22	.	.	PUNCT
iajs-2710	177	1	figure	figure	VERB
iajs-2710	177	2	4	4	NUM
iajs-2710	177	3	:	:	PUNCT
iajs-2710	177	4	the	the	DET
iajs-2710	177	5	training	training	NOUN
iajs-2710	177	6	and	and	CCONJ
iajs-2710	177	7	testing	testing	NOUN
iajs-2710	177	8	graph	graph	NOUN
iajs-2710	177	9	for	for	ADP
iajs-2710	177	10	neural	neural	ADJ
iajs-2710	177	11	network	network	NOUN
iajs-2710	177	12	model	model	NOUN
iajs-2710	177	13	with	with	ADP
iajs-2710	177	14	dropout	dropout	NOUN
iajs-2710	177	15	.	.	PUNCT
iajs-2710	178	1	so	so	ADV
iajs-2710	178	2	in	in	ADP
iajs-2710	178	3	figure	figure	NOUN
iajs-2710	178	4	4	4	NUM
iajs-2710	178	5	,	,	PUNCT
iajs-2710	178	6	we	we	PRON
iajs-2710	178	7	show	show	VERB
iajs-2710	178	8	the	the	DET
iajs-2710	178	9	training	training	NOUN
iajs-2710	178	10	and	and	CCONJ
iajs-2710	178	11	testing	testing	NOUN
iajs-2710	178	12	graph	graph	NOUN
iajs-2710	178	13	for	for	ADP
iajs-2710	178	14	neural	neural	ADJ
iajs-2710	178	15	network	network	NOUN
iajs-2710	178	16	model	model	NOUN
iajs-2710	178	17	with	with	ADP
iajs-2710	178	18	dropout	dropout	NOUN
iajs-2710	178	19	,	,	PUNCT
iajs-2710	178	20	images	image	NOUN
iajs-2710	178	21	tend	tend	VERB
iajs-2710	178	22	to	to	PART
iajs-2710	178	23	portray	portray	VERB
iajs-2710	178	24	similar	similar	ADJ
iajs-2710	178	25	features	feature	NOUN
iajs-2710	178	26	at	at	ADP
iajs-2710	178	27	different	different	ADJ
iajs-2710	178	28	spatial	spatial	ADJ
iajs-2710	178	29	locations	location	NOUN
iajs-2710	178	30	.	.	PUNCT
iajs-2710	179	1	accordingly	accordingly	ADV
iajs-2710	179	2	,	,	PUNCT
iajs-2710	179	3	units	unit	NOUN
iajs-2710	179	4	with	with	ADP
iajs-2710	179	5	receptive	receptive	ADJ
iajs-2710	179	6	fields	field	NOUN
iajs-2710	179	7	at	at	ADP
iajs-2710	179	8	different	different	ADJ
iajs-2710	179	9	locations	location	NOUN
iajs-2710	179	10	will	will	AUX
iajs-2710	179	11	have	have	VERB
iajs-2710	179	12	the	the	DET
iajs-2710	179	13	same	same	ADJ
iajs-2710	179	14	weight	weight	NOUN
iajs-2710	179	15	vectors	vector	NOUN
iajs-2710	179	16	to	to	PART
iajs-2710	179	17	extract	extract	VERB
iajs-2710	179	18	similar	similar	ADJ
iajs-2710	179	19	features	feature	NOUN
iajs-2710	179	20	,	,	PUNCT
iajs-2710	179	21	known	know	VERB
iajs-2710	179	22	as	as	ADP
iajs-2710	179	23	parameter	parameter	NOUN
iajs-2710	179	24	sharing	sharing	NOUN
iajs-2710	179	25	and	and	CCONJ
iajs-2710	179	26	further	far	ADV
iajs-2710	179	27	reduces	reduce	VERB
iajs-2710	179	28	the	the	DET
iajs-2710	179	29	dimensionality	dimensionality	NOUN
iajs-2710	179	30	of	of	ADP
iajs-2710	179	31	the	the	DET
iajs-2710	179	32	problem	problem	NOUN
iajs-2710	179	33	.	.	PUNCT
iajs-2710	180	1	3.4	3.4	NUM
iajs-2710	180	2	.	.	PUNCT
iajs-2710	180	3	baseline	baseline	PROPN
iajs-2710	180	4	parameters	parameter	NOUN
iajs-2710	180	5	for	for	ADP
iajs-2710	180	6	mri	mri	NOUN
iajs-2710	180	7	the	the	DET
iajs-2710	180	8	output	output	NOUN
iajs-2710	180	9	of	of	ADP
iajs-2710	180	10	the	the	DET
iajs-2710	180	11	first	first	ADJ
iajs-2710	180	12	stage	stage	NOUN
iajs-2710	180	13	is	be	AUX
iajs-2710	180	14	an	an	DET
iajs-2710	180	15	image	image	NOUN
iajs-2710	180	16	of	of	ADP
iajs-2710	180	17	the	the	DET
iajs-2710	180	18	same	same	ADJ
iajs-2710	180	19	dimensions	dimension	NOUN
iajs-2710	180	20	as	as	ADP
iajs-2710	180	21	the	the	DET
iajs-2710	180	22	input	input	NOUN
iajs-2710	180	23	image	image	NOUN
iajs-2710	180	24	that	that	PRON
iajs-2710	180	25	contains	contain	VERB
iajs-2710	180	26	the	the	DET
iajs-2710	180	27	stroke	stroke	NOUN
iajs-2710	180	28	width	width	VERB
iajs-2710	180	29	for	for	ADP
iajs-2710	180	30	each	each	DET
iajs-2710	180	31	pixel	pixel	NOUN
iajs-2710	180	32	.	.	PUNCT
iajs-2710	181	1	first	first	ADV
iajs-2710	181	2	,	,	PUNCT
iajs-2710	181	3	they	they	PRON
iajs-2710	181	4	compute	compute	VERB
iajs-2710	181	5	the	the	DET
iajs-2710	181	6	edge	edge	NOUN
iajs-2710	181	7	map	map	NOUN
iajs-2710	181	8	of	of	ADP
iajs-2710	181	9	the	the	DET
iajs-2710	181	10	input	input	NOUN
iajs-2710	181	11	image	image	NOUN
iajs-2710	181	12	using	use	VERB
iajs-2710	181	13	the	the	DET
iajs-2710	181	14	canny	canny	ADJ
iajs-2710	181	15	edge	edge	NOUN
iajs-2710	181	16	detector	detector	NOUN
iajs-2710	181	17	and	and	CCONJ
iajs-2710	181	18	initialize	initialize	VERB
iajs-2710	181	19	all	all	DET
iajs-2710	181	20	the	the	DET
iajs-2710	181	21	stroke	stroke	NOUN
iajs-2710	181	22	width	width	PROPN
iajs-2710	181	23	result	result	VERB
iajs-2710	181	24	values	value	NOUN
iajs-2710	181	25	to	to	PART
iajs-2710	181	26	infinity	infinity	VERB
iajs-2710	181	27	.	.	PUNCT
iajs-2710	182	1	for	for	ADP
iajs-2710	182	2	each	each	DET
iajs-2710	182	3	returned	return	VERB
iajs-2710	182	4	edge	edge	NOUN
iajs-2710	182	5	pixel	pixel	NOUN
iajs-2710	182	6	,	,	PUNCT
iajs-2710	182	7	the	the	DET
iajs-2710	182	8	gradient	gradient	ADJ
iajs-2710	182	9	direction	direction	NOUN
iajs-2710	182	10	is	be	AUX
iajs-2710	182	11	followed	follow	VERB
iajs-2710	182	12	until	until	SCONJ
iajs-2710	182	13	another	another	DET
iajs-2710	182	14	edge	edge	NOUN
iajs-2710	182	15	pixel	pixel	NOUN
iajs-2710	182	16	is	be	AUX
iajs-2710	182	17	found	find	VERB
iajs-2710	182	18	.	.	PUNCT
iajs-2710	183	1	suppose	suppose	VERB
iajs-2710	183	2	the	the	DET
iajs-2710	183	3	gradient	gradient	ADJ
iajs-2710	183	4	direction	direction	NOUN
iajs-2710	183	5	of	of	ADP
iajs-2710	183	6	the	the	DET
iajs-2710	183	7	second	second	ADJ
iajs-2710	183	8	edge	edge	NOUN
iajs-2710	183	9	pixel	pixel	NOUN
iajs-2710	183	10	roughly	roughly	ADV
iajs-2710	183	11	points	point	VERB
iajs-2710	183	12	back	back	ADV
iajs-2710	183	13	to	to	ADP
iajs-2710	183	14	the	the	DET
iajs-2710	183	15	starting	starting	NOUN
iajs-2710	183	16	pixel	pixel	NOUN
iajs-2710	183	17	.	.	PUNCT
iajs-2710	184	1	in	in	ADP
iajs-2710	184	2	that	that	DET
iajs-2710	184	3	case	case	NOUN
iajs-2710	184	4	,	,	PUNCT
iajs-2710	184	5	all	all	DET
iajs-2710	184	6	stroke	stroke	NOUN
iajs-2710	184	7	width	width	ADJ
iajs-2710	184	8	values	value	NOUN
iajs-2710	184	9	on	on	ADP
iajs-2710	184	10	the	the	DET
iajs-2710	184	11	line	line	NOUN
iajs-2710	184	12	connecting	connect	VERB
iajs-2710	184	13	them	they	PRON
iajs-2710	184	14	are	be	AUX
iajs-2710	184	15	set	set	VERB
iajs-2710	184	16	to	to	ADP
iajs-2710	184	17	the	the	DET
iajs-2710	184	18	distance	distance	NOUN
iajs-2710	184	19	between	between	ADP
iajs-2710	184	20	the	the	DET
iajs-2710	184	21	starting	starting	NOUN
iajs-2710	184	22	and	and	CCONJ
iajs-2710	184	23	the	the	DET
iajs-2710	184	24	end	end	NOUN
iajs-2710	184	25	pixel	pixel	PROPN
iajs-2710	184	26	,	,	PUNCT
iajs-2710	184	27	but	but	CCONJ
iajs-2710	184	28	only	only	ADV
iajs-2710	184	29	if	if	SCONJ
iajs-2710	184	30	they	they	PRON
iajs-2710	184	31	do	do	AUX
iajs-2710	184	32	not	not	PART
iajs-2710	184	33	already	already	ADV
iajs-2710	184	34	have	have	VERB
iajs-2710	184	35	a	a	DET
iajs-2710	184	36	lower	low	ADJ
iajs-2710	184	37	value	value	NOUN
iajs-2710	184	38	.	.	PUNCT
iajs-2710	185	1	when	when	SCONJ
iajs-2710	185	2	all	all	DET
iajs-2710	185	3	edge	edge	NOUN
iajs-2710	185	4	pixels	pixel	NOUN
iajs-2710	185	5	are	be	AUX
iajs-2710	185	6	processed	process	VERB
iajs-2710	185	7	,	,	PUNCT
iajs-2710	185	8	all	all	PRON
iajs-2710	185	9	start	start	VERB
iajs-2710	185	10	pixels	pixel	NOUN
iajs-2710	185	11	where	where	SCONJ
iajs-2710	185	12	an	an	DET
iajs-2710	185	13	end	end	NOUN
iajs-2710	185	14	pixel	pixel	NOUN
iajs-2710	185	15	was	be	AUX
iajs-2710	185	16	found	find	VERB
iajs-2710	185	17	are	be	AUX
iajs-2710	185	18	revisited	revisit	VERB
iajs-2710	185	19	.	.	PUNCT
iajs-2710	186	1	the	the	DET
iajs-2710	186	2	stroke	stroke	NOUN
iajs-2710	186	3	width	width	VERB
iajs-2710	186	4	values	value	NOUN
iajs-2710	186	5	on	on	ADP
iajs-2710	186	6	the	the	DET
iajs-2710	186	7	lines	line	NOUN
iajs-2710	186	8	connecting	connect	VERB
iajs-2710	186	9	them	they	PRON
iajs-2710	186	10	are	be	AUX
iajs-2710	186	11	set	set	VERB
iajs-2710	186	12	to	to	ADP
iajs-2710	186	13	the	the	DET
iajs-2710	186	14	median	median	ADJ
iajs-2710	186	15	value	value	NOUN
iajs-2710	186	16	of	of	ADP
iajs-2710	186	17	all	all	DET
iajs-2710	186	18	pixels	pixel	NOUN
iajs-2710	186	19	on	on	ADP
iajs-2710	186	20	the	the	DET
iajs-2710	186	21	line	line	NOUN
iajs-2710	186	22	.	.	PUNCT
iajs-2710	187	1	the	the	DET
iajs-2710	187	2	research	research	NOUN
iajs-2710	187	3	note	note	VERB
iajs-2710	187	4	that	that	SCONJ
iajs-2710	187	5	this	this	PRON
iajs-2710	187	6	is	be	AUX
iajs-2710	187	7	necessary	necessary	ADJ
iajs-2710	187	8	to	to	PART
iajs-2710	187	9	get	get	VERB
iajs-2710	187	10	correct	correct	ADJ
iajs-2710	187	11	results	result	NOUN
iajs-2710	187	12	in	in	ADP
iajs-2710	187	13	corners	corner	NOUN
iajs-2710	187	14	,	,	PUNCT
iajs-2710	187	15	next	next	ADV
iajs-2710	187	16	,	,	PUNCT
iajs-2710	187	17	they	they	PRON
iajs-2710	187	18	extract	extract	VERB
iajs-2710	187	19	connected	connected	ADJ
iajs-2710	187	20	components	component	NOUN
iajs-2710	187	21	,	,	PUNCT
iajs-2710	187	22	where	where	SCONJ
iajs-2710	187	23	neighboring	neighboring	NOUN
iajs-2710	187	24	pixels	pixel	NOUN
iajs-2710	187	25	are	be	AUX
iajs-2710	187	26	assigned	assign	VERB
iajs-2710	187	27	to	to	ADP
iajs-2710	187	28	the	the	DET
iajs-2710	187	29	same	same	ADJ
iajs-2710	187	30	contour	contour	NOUN
iajs-2710	187	31	if	if	SCONJ
iajs-2710	187	32	their	their	PRON
iajs-2710	187	33	stroke	stroke	NOUN
iajs-2710	187	34	widths	width	NOUN
iajs-2710	187	35	are	be	AUX
iajs-2710	187	36	similar	similar	ADJ
iajs-2710	187	37	.	.	PUNCT
iajs-2710	188	1	these	these	DET
iajs-2710	188	2	contours	contours	NOUN
iajs-2710	188	3	are	be	AUX
iajs-2710	188	4	filtered	filter	VERB
iajs-2710	188	5	to	to	PART
iajs-2710	188	6	retrieve	retrieve	VERB
iajs-2710	188	7	text	text	NOUN
iajs-2710	188	8	regions	region	NOUN
iajs-2710	188	9	.	.	PUNCT
iajs-2710	189	1	a	a	DET
iajs-2710	189	2	contour	contour	NOUN
iajs-2710	189	3	is	be	AUX
iajs-2710	189	4	discarded	discard	VERB
iajs-2710	189	5	if	if	SCONJ
iajs-2710	189	6	the	the	DET
iajs-2710	189	7	stroke	stroke	NOUN
iajs-2710	189	8	width	width	ADJ
iajs-2710	189	9	variance	variance	NOUN
iajs-2710	189	10	of	of	ADP
iajs-2710	189	11	its	its	PRON
iajs-2710	189	12	enclosed	enclose	VERB
iajs-2710	189	13	pixels	pixel	NOUN
iajs-2710	189	14	is	be	AUX
iajs-2710	189	15	too	too	ADV
iajs-2710	189	16	large	large	ADJ
iajs-2710	189	17	or	or	CCONJ
iajs-2710	189	18	when	when	SCONJ
iajs-2710	189	19	its	its	PRON
iajs-2710	189	20	aspect	aspect	NOUN
iajs-2710	189	21	ratio	ratio	NOUN
iajs-2710	189	22	or	or	CCONJ
iajs-2710	189	23	diameter	diameter	NOUN
iajs-2710	189	24	to	to	PART
iajs-2710	189	25	stroke	stroke	NOUN
iajs-2710	189	26	width	width	NOUN
iajs-2710	189	27	is	be	AUX
iajs-2710	189	28	not	not	PART
iajs-2710	189	29	within	within	ADP
iajs-2710	189	30	a	a	DET
iajs-2710	189	31	threshold	threshold	NOUN
iajs-2710	189	32	.	.	PUNCT
iajs-2710	190	1	furthermore	furthermore	ADV
iajs-2710	190	2	,	,	PUNCT
iajs-2710	190	3	the	the	DET
iajs-2710	190	4	bounding	bounding	NOUN
iajs-2710	190	5	box	box	NOUN
iajs-2710	190	6	of	of	ADP
iajs-2710	190	7	a	a	DET
iajs-2710	190	8	contour	contour	NOUN
iajs-2710	190	9	must	must	AUX
iajs-2710	190	10	be	be	AUX
iajs-2710	190	11	appropriately	appropriately	ADV
iajs-2710	190	12	sized	sized	ADJ
iajs-2710	190	13	and	and	CCONJ
iajs-2710	190	14	not	not	PART
iajs-2710	190	15	contain	contain	VERB
iajs-2710	190	16	more	more	ADJ
iajs-2710	190	17	than	than	ADP
iajs-2710	190	18	two	two	NUM
iajs-2710	190	19	inner	inner	ADJ
iajs-2710	190	20	contours	contours	NOUN
iajs-2710	190	21	.	.	PUNCT
iajs-2710	191	1	the	the	DET
iajs-2710	191	2	resulting	result	VERB
iajs-2710	191	3	letters	letter	NOUN
iajs-2710	191	4	are	be	AUX
iajs-2710	191	5	grouped	group	VERB
iajs-2710	191	6	into	into	ADP
iajs-2710	191	7	pairs	pair	NOUN
iajs-2710	191	8	if	if	SCONJ
iajs-2710	191	9	they	they	PRON
iajs-2710	191	10	have	have	VERB
iajs-2710	191	11	a	a	DET
iajs-2710	191	12	similar	similar	ADJ
iajs-2710	191	13	stroke	stroke	NOUN
iajs-2710	191	14	width	width	NOUN
iajs-2710	191	15	,	,	PUNCT
iajs-2710	191	16	height	height	NOUN
iajs-2710	191	17	,	,	PUNCT
iajs-2710	191	18	and	and	CCONJ
iajs-2710	191	19	color	color	NOUN
iajs-2710	191	20	and	and	CCONJ
iajs-2710	191	21	are	be	AUX
iajs-2710	191	22	not	not	PART
iajs-2710	191	23	located	locate	VERB
iajs-2710	191	24	too	too	ADV
iajs-2710	191	25	far	far	ADV
iajs-2710	191	26	apart	apart	ADV
iajs-2710	191	27	.	.	PUNCT
iajs-2710	192	1	finally	finally	ADV
iajs-2710	192	2	,	,	PUNCT
iajs-2710	192	3	the	the	DET
iajs-2710	192	4	ibn	ibn	PROPN
iajs-2710	192	5	al	al	PROPN
iajs-2710	192	6	-	-	PUNCT
iajs-2710	192	7	haitham	haitham	PROPN
iajs-2710	192	8	jour	jour	X
iajs-2710	192	9	.	.	PROPN
iajs-2710	193	1	for	for	ADP
iajs-2710	193	2	pure	pure	ADJ
iajs-2710	193	3	&	&	CCONJ
iajs-2710	193	4	appl	appl	PROPN
iajs-2710	193	5	.	.	PUNCT
iajs-2710	194	1	sci	sci	PROPN
iajs-2710	194	2	.	.	PROPN
iajs-2710	195	1	34(4)2021	34(4)2021	NUM
iajs-2710	195	2	138	138	NUM
iajs-2710	195	3	brain	brain	NOUN
iajs-2710	195	4	pairs	pair	NOUN
iajs-2710	195	5	are	be	AUX
iajs-2710	195	6	merged	merge	VERB
iajs-2710	195	7	into	into	ADP
iajs-2710	195	8	text	text	NOUN
iajs-2710	195	9	lines	line	NOUN
iajs-2710	195	10	,	,	PUNCT
iajs-2710	195	11	and	and	CCONJ
iajs-2710	195	12	word	word	NOUN
iajs-2710	195	13	boundaries	boundary	NOUN
iajs-2710	195	14	are	be	AUX
iajs-2710	195	15	detected	detect	VERB
iajs-2710	195	16	using	use	VERB
iajs-2710	195	17	a	a	DET
iajs-2710	195	18	histogram	histogram	NOUN
iajs-2710	195	19	of	of	ADP
iajs-2710	195	20	the	the	DET
iajs-2710	195	21	brain	brain	NOUN
iajs-2710	195	22	distances	distance	NOUN
iajs-2710	195	23	.	.	PUNCT
iajs-2710	196	1	4.results	4.result	NOUN
iajs-2710	196	2	the	the	DET
iajs-2710	196	3	final	final	ADJ
iajs-2710	196	4	grouped	group	VERB
iajs-2710	196	5	regions	region	NOUN
iajs-2710	196	6	are	be	AUX
iajs-2710	196	7	obtained	obtain	VERB
iajs-2710	196	8	by	by	ADP
iajs-2710	196	9	applying	apply	VERB
iajs-2710	196	10	the	the	DET
iajs-2710	196	11	previous	previous	ADJ
iajs-2710	196	12	clustering	clustering	ADJ
iajs-2710	196	13	steps	step	NOUN
iajs-2710	196	14	again	again	ADV
iajs-2710	196	15	to	to	ADP
iajs-2710	196	16	the	the	DET
iajs-2710	196	17	co	co	NOUN
iajs-2710	196	18	-	-	NOUN
iajs-2710	196	19	occurrence	occurrence	ADJ
iajs-2710	196	20	matrix	matrix	NOUN
iajs-2710	196	21	.	.	PUNCT
iajs-2710	197	1	a	a	DET
iajs-2710	197	2	cnn	cnn	PROPN
iajs-2710	197	3	classifier	classifier	NOUN
iajs-2710	197	4	is	be	AUX
iajs-2710	197	5	used	use	VERB
iajs-2710	197	6	to	to	PART
iajs-2710	197	7	prune	prune	NOUN
iajs-2710	197	8	regions	region	NOUN
iajs-2710	197	9	that	that	PRON
iajs-2710	197	10	do	do	AUX
iajs-2710	197	11	not	not	PART
iajs-2710	197	12	have	have	VERB
iajs-2710	197	13	a	a	DET
iajs-2710	197	14	brain	brain	NOUN
iajs-2710	197	15	-	-	PUNCT
iajs-2710	197	16	shaped	shape	VERB
iajs-2710	197	17	object	object	NOUN
iajs-2710	197	18	.	.	PUNCT
iajs-2710	198	1	finally	finally	ADV
iajs-2710	198	2	,	,	PUNCT
iajs-2710	198	3	a	a	DET
iajs-2710	198	4	cnn	cnn	PROPN
iajs-2710	198	5	classifier	classifier	NOUN
iajs-2710	198	6	is	be	AUX
iajs-2710	198	7	used	use	VERB
iajs-2710	198	8	to	to	PART
iajs-2710	198	9	remove	remove	VERB
iajs-2710	198	10	clustered	clustered	ADJ
iajs-2710	198	11	regions	region	NOUN
iajs-2710	198	12	that	that	PRON
iajs-2710	198	13	do	do	AUX
iajs-2710	198	14	not	not	PART
iajs-2710	198	15	contain	contain	VERB
iajs-2710	198	16	text	text	NOUN
iajs-2710	198	17	.	.	PUNCT
iajs-2710	199	1	regions	region	NOUN
iajs-2710	199	2	for	for	ADP
iajs-2710	199	3	the	the	DET
iajs-2710	199	4	class	class	NOUN
iajs-2710	199	5	and	and	CCONJ
iajs-2710	199	6	classifier	classifier	NOUN
iajs-2710	199	7	determine	determine	VERB
iajs-2710	199	8	whether	whether	SCONJ
iajs-2710	199	9	the	the	DET
iajs-2710	199	10	input	input	NOUN
iajs-2710	199	11	region	region	NOUN
iajs-2710	199	12	is	be	AUX
iajs-2710	199	13	a	a	DET
iajs-2710	199	14	brain	brain	NOUN
iajs-2710	199	15	or	or	CCONJ
iajs-2710	199	16	not	not	PART
iajs-2710	199	17	,	,	PUNCT
iajs-2710	199	18	as	as	SCONJ
iajs-2710	199	19	we	we	PRON
iajs-2710	199	20	show	show	VERB
iajs-2710	199	21	in	in	ADP
iajs-2710	199	22	figure	figure	NOUN
iajs-2710	199	23	5	5	NUM
iajs-2710	199	24	in	in	ADP
iajs-2710	199	25	three	three	NUM
iajs-2710	199	26	-	-	PUNCT
iajs-2710	199	27	stage	stage	NOUN
iajs-2710	199	28	input	input	NOUN
iajs-2710	199	29	and	and	CCONJ
iajs-2710	199	30	segmentation	segmentation	NOUN
iajs-2710	199	31	mri	mri	NOUN
iajs-2710	199	32	scan	scan	NOUN
iajs-2710	199	33	.	.	PUNCT
iajs-2710	200	1	the	the	DET
iajs-2710	200	2	detected	detect	VERB
iajs-2710	200	3	text	text	NOUN
iajs-2710	200	4	regions	region	NOUN
iajs-2710	200	5	are	be	AUX
iajs-2710	200	6	grouped	group	VERB
iajs-2710	200	7	into	into	ADP
iajs-2710	200	8	brains	brain	NOUN
iajs-2710	200	9	by	by	ADP
iajs-2710	200	10	incorporating	incorporate	VERB
iajs-2710	200	11	knowledge	knowledge	NOUN
iajs-2710	200	12	of	of	ADP
iajs-2710	200	13	the	the	DET
iajs-2710	200	14	layout	layout	PROPN
iajs-2710	200	15	.	.	PUNCT
iajs-2710	201	1	input	input	NOUN
iajs-2710	201	2	segmentation	segmentation	NOUN
iajs-2710	201	3	mri	mri	NOUN
iajs-2710	201	4	scan	scan	PROPN
iajs-2710	201	5	sample	sample	NOUN
iajs-2710	201	6	:	:	PUNCT
iajs-2710	201	7	1	1	NUM
iajs-2710	201	8	sample	sample	NOUN
iajs-2710	201	9	:	:	PUNCT
iajs-2710	201	10	2	2	NUM
iajs-2710	201	11	sample	sample	NOUN
iajs-2710	201	12	:	:	PUNCT
iajs-2710	201	13	3	3	NUM
iajs-2710	201	14	figure	figure	NOUN
iajs-2710	201	15	5	5	NUM
iajs-2710	201	16	:	:	PUNCT
iajs-2710	201	17	the	the	DET
iajs-2710	201	18	three	three	NUM
iajs-2710	201	19	-	-	PUNCT
iajs-2710	201	20	phase	phase	NOUN
iajs-2710	201	21	processing	processing	NOUN
iajs-2710	201	22	of	of	ADP
iajs-2710	201	23	mri	mri	NOUN
iajs-2710	201	24	samples	sample	NOUN
iajs-2710	201	25	from	from	ADP
iajs-2710	201	26	input	input	NOUN
iajs-2710	201	27	,	,	PUNCT
iajs-2710	201	28	segmentation	segmentation	NOUN
iajs-2710	201	29	to	to	ADP
iajs-2710	201	30	the	the	DET
iajs-2710	201	31	scan	scan	NOUN
iajs-2710	201	32	.	.	PUNCT
iajs-2710	202	1	the	the	DET
iajs-2710	202	2	opened	open	VERB
iajs-2710	202	3	image	image	NOUN
iajs-2710	202	4	is	be	AUX
iajs-2710	202	5	subtracted	subtract	VERB
iajs-2710	202	6	pixel	pixel	ADJ
iajs-2710	202	7	-	-	ADJ
iajs-2710	202	8	wise	wise	ADJ
iajs-2710	202	9	from	from	ADP
iajs-2710	202	10	the	the	DET
iajs-2710	202	11	original	original	ADJ
iajs-2710	202	12	image	image	NOUN
iajs-2710	202	13	.	.	PUNCT
iajs-2710	203	1	since	since	SCONJ
iajs-2710	203	2	the	the	DET
iajs-2710	203	3	brain	brain	NOUN
iajs-2710	203	4	width	width	NOUN
iajs-2710	203	5	is	be	AUX
iajs-2710	203	6	small	small	ADJ
iajs-2710	203	7	about	about	ADP
iajs-2710	203	8	the	the	DET
iajs-2710	203	9	structuring	structuring	NOUN
iajs-2710	203	10	element	element	NOUN
iajs-2710	203	11	,	,	PUNCT
iajs-2710	203	12	they	they	PRON
iajs-2710	203	13	remain	remain	VERB
iajs-2710	203	14	intact	intact	ADJ
iajs-2710	203	15	.	.	PUNCT
iajs-2710	204	1	the	the	DET
iajs-2710	204	2	graph	graph	NOUN
iajs-2710	204	3	illustrates	illustrate	VERB
iajs-2710	204	4	this	this	PRON
iajs-2710	204	5	for	for	ADP
iajs-2710	204	6	the	the	DET
iajs-2710	204	7	first	first	ADJ
iajs-2710	204	8	sample	sample	NOUN
iajs-2710	204	9	region	region	NOUN
iajs-2710	204	10	.	.	PUNCT
iajs-2710	205	1	as	as	SCONJ
iajs-2710	205	2	the	the	DET
iajs-2710	205	3	lines	line	NOUN
iajs-2710	205	4	are	be	AUX
iajs-2710	205	5	not	not	PART
iajs-2710	205	6	leveled	level	VERB
iajs-2710	205	7	,	,	PUNCT
iajs-2710	205	8	some	some	DET
iajs-2710	205	9	parts	part	NOUN
iajs-2710	205	10	of	of	ADP
iajs-2710	205	11	them	they	PRON
iajs-2710	205	12	stay	stay	VERB
iajs-2710	205	13	for	for	ADP
iajs-2710	205	14	mri	mri	NOUN
iajs-2710	205	15	.	.	PUNCT
iajs-2710	206	1	however	however	ADV
iajs-2710	206	2	,	,	PUNCT
iajs-2710	206	3	using	use	VERB
iajs-2710	206	4	the	the	DET
iajs-2710	206	5	same	same	ADJ
iajs-2710	206	6	approach	approach	NOUN
iajs-2710	206	7	to	to	PART
iajs-2710	206	8	remove	remove	VERB
iajs-2710	206	9	vertical	vertical	ADJ
iajs-2710	206	10	lines	line	NOUN
iajs-2710	206	11	would	would	AUX
iajs-2710	206	12	also	also	ADV
iajs-2710	206	13	remove	remove	VERB
iajs-2710	206	14	most	most	ADJ
iajs-2710	206	15	of	of	ADP
iajs-2710	206	16	the	the	DET
iajs-2710	206	17	text	text	NOUN
iajs-2710	206	18	.	.	PUNCT
iajs-2710	207	1	to	to	PART
iajs-2710	207	2	prevent	prevent	VERB
iajs-2710	207	3	this	this	PRON
iajs-2710	207	4	,	,	PUNCT
iajs-2710	207	5	the	the	DET
iajs-2710	207	6	presence	presence	NOUN
iajs-2710	207	7	and	and	CCONJ
iajs-2710	207	8	location	location	NOUN
iajs-2710	207	9	of	of	ADP
iajs-2710	207	10	borders	border	NOUN
iajs-2710	207	11	are	be	AUX
iajs-2710	207	12	determined	determine	VERB
iajs-2710	207	13	first	first	ADV
iajs-2710	207	14	,	,	PUNCT
iajs-2710	207	15	and	and	CCONJ
iajs-2710	207	16	only	only	ADV
iajs-2710	207	17	those	those	DET
iajs-2710	207	18	regions	region	NOUN
iajs-2710	207	19	are	be	AUX
iajs-2710	207	20	filtered	filter	VERB
iajs-2710	207	21	.	.	PUNCT
iajs-2710	208	1	at	at	ADP
iajs-2710	208	2	the	the	DET
iajs-2710	208	3	first	first	ADJ
iajs-2710	208	4	20	20	NUM
iajs-2710	208	5	%	%	NOUN
iajs-2710	208	6	of	of	ADP
iajs-2710	208	7	the	the	DET
iajs-2710	208	8	left	left	ADJ
iajs-2710	208	9	and	and	CCONJ
iajs-2710	208	10	right	right	ADJ
iajs-2710	208	11	sides	side	NOUN
iajs-2710	208	12	of	of	ADP
iajs-2710	208	13	the	the	DET
iajs-2710	208	14	image	image	NOUN
iajs-2710	208	15	,	,	PUNCT
iajs-2710	208	16	peaks	peak	NOUN
iajs-2710	208	17	are	be	AUX
iajs-2710	208	18	detected	detect	VERB
iajs-2710	208	19	.	.	PUNCT
iajs-2710	209	1	a	a	DET
iajs-2710	209	2	peak	peak	NOUN
iajs-2710	209	3	is	be	AUX
iajs-2710	209	4	reported	report	VERB
iajs-2710	209	5	if	if	SCONJ
iajs-2710	209	6	70	70	NUM
iajs-2710	209	7	%	%	NOUN
iajs-2710	209	8	of	of	ADP
iajs-2710	209	9	all	all	DET
iajs-2710	209	10	pixels	pixel	NOUN
iajs-2710	209	11	in	in	ADP
iajs-2710	209	12	a	a	DET
iajs-2710	209	13	column	column	NOUN
iajs-2710	209	14	are	be	AUX
iajs-2710	209	15	black	black	ADJ
iajs-2710	209	16	.	.	PUNCT
iajs-2710	210	1	since	since	SCONJ
iajs-2710	210	2	we	we	PRON
iajs-2710	210	3	assume	assume	VERB
iajs-2710	210	4	that	that	SCONJ
iajs-2710	210	5	the	the	DET
iajs-2710	210	6	text	text	NOUN
iajs-2710	210	7	is	be	AUX
iajs-2710	210	8	roughly	roughly	ADV
iajs-2710	210	9	centered	center	VERB
iajs-2710	210	10	,	,	PUNCT
iajs-2710	210	11	the	the	DET
iajs-2710	210	12	distance	distance	NOUN
iajs-2710	210	13	of	of	ADP
iajs-2710	210	14	the	the	DET
iajs-2710	210	15	first	first	ADJ
iajs-2710	210	16	detected	detect	VERB
iajs-2710	210	17	peak	peak	NOUN
iajs-2710	210	18	on	on	ADP
iajs-2710	210	19	either	either	DET
iajs-2710	210	20	side	side	NOUN
iajs-2710	210	21	to	to	ADP
iajs-2710	210	22	the	the	DET
iajs-2710	210	23	image	image	NOUN
iajs-2710	210	24	border	border	NOUN
iajs-2710	210	25	should	should	AUX
iajs-2710	210	26	also	also	ADV
iajs-2710	210	27	be	be	AUX
iajs-2710	210	28	approximately	approximately	ADV
iajs-2710	210	29	the	the	DET
iajs-2710	210	30	same	same	ADJ
iajs-2710	210	31	.	.	PUNCT
iajs-2710	211	1	again	again	ADV
iajs-2710	211	2	,	,	PUNCT
iajs-2710	211	3	the	the	DET
iajs-2710	211	4	ibn	ibn	PROPN
iajs-2710	211	5	al	al	PROPN
iajs-2710	211	6	-	-	PUNCT
iajs-2710	211	7	haitham	haitham	PROPN
iajs-2710	211	8	jour	jour	X
iajs-2710	211	9	.	.	PROPN
iajs-2710	212	1	for	for	ADP
iajs-2710	212	2	pure	pure	ADJ
iajs-2710	212	3	&	&	CCONJ
iajs-2710	212	4	appl	appl	PROPN
iajs-2710	212	5	.	.	PUNCT
iajs-2710	213	1	sci	sci	PROPN
iajs-2710	213	2	.	.	PROPN
iajs-2710	214	1	34(4)2021	34(4)2021	NUM
iajs-2710	214	2	139	139	NUM
iajs-2710	214	3	opening	opening	NOUN
iajs-2710	214	4	result	result	NOUN
iajs-2710	214	5	is	be	AUX
iajs-2710	214	6	subtracted	subtract	VERB
iajs-2710	214	7	pixel	pixel	ADJ
iajs-2710	214	8	-	-	ADJ
iajs-2710	214	9	wise	wise	ADJ
iajs-2710	214	10	from	from	ADP
iajs-2710	214	11	the	the	DET
iajs-2710	214	12	original	original	ADJ
iajs-2710	214	13	image	image	NOUN
iajs-2710	214	14	.	.	PUNCT
iajs-2710	215	1	since	since	SCONJ
iajs-2710	215	2	the	the	DET
iajs-2710	215	3	removed	removed	ADJ
iajs-2710	215	4	lines	line	NOUN
iajs-2710	215	5	usually	usually	ADV
iajs-2710	215	6	are	be	AUX
iajs-2710	215	7	not	not	PART
iajs-2710	215	8	perfectly	perfectly	ADV
iajs-2710	215	9	horizontal	horizontal	ADJ
iajs-2710	215	10	or	or	CCONJ
iajs-2710	215	11	vertical	vertical	ADJ
iajs-2710	215	12	,	,	PUNCT
iajs-2710	215	13	some	some	DET
iajs-2710	215	14	debris	debris	NOUN
iajs-2710	215	15	remains	remain	VERB
iajs-2710	215	16	.	.	PUNCT
iajs-2710	216	1	we	we	PRON
iajs-2710	216	2	show	show	VERB
iajs-2710	216	3	table	table	NOUN
iajs-2710	216	4	2	2	NUM
iajs-2710	216	5	results	result	NOUN
iajs-2710	216	6	comparing	compare	VERB
iajs-2710	216	7	the	the	DET
iajs-2710	216	8	neural	neural	ADJ
iajs-2710	216	9	network	network	NOUN
iajs-2710	216	10	and	and	CCONJ
iajs-2710	216	11	empirical	empirical	ADJ
iajs-2710	216	12	residual	residual	ADJ
iajs-2710	216	13	models	model	NOUN
iajs-2710	216	14	.	.	PUNCT
iajs-2710	217	1	cleaning	clean	VERB
iajs-2710	217	2	and	and	CCONJ
iajs-2710	217	3	testing	testing	NOUN
iajs-2710	217	4	values	value	NOUN
iajs-2710	217	5	are	be	AUX
iajs-2710	217	6	computed	compute	VERB
iajs-2710	217	7	by	by	ADP
iajs-2710	217	8	comparing	compare	VERB
iajs-2710	217	9	the	the	DET
iajs-2710	217	10	predicted	predict	VERB
iajs-2710	217	11	values	value	NOUN
iajs-2710	217	12	to	to	ADP
iajs-2710	217	13	the	the	DET
iajs-2710	217	14	mri	mri	NOUN
iajs-2710	217	15	scans	scan	NOUN
iajs-2710	217	16	found	find	VERB
iajs-2710	217	17	using	use	VERB
iajs-2710	217	18	the	the	DET
iajs-2710	217	19	baseline	baseline	ADJ
iajs-2710	217	20	dictionary	dictionary	ADJ
iajs-2710	217	21	neural	neural	ADJ
iajs-2710	217	22	network	network	NOUN
iajs-2710	217	23	method	method	NOUN
iajs-2710	217	24	.	.	PUNCT
iajs-2710	218	1	also	also	ADV
iajs-2710	218	2	,	,	PUNCT
iajs-2710	218	3	we	we	PRON
iajs-2710	218	4	show	show	VERB
iajs-2710	218	5	table	table	NOUN
iajs-2710	218	6	3	3	NUM
iajs-2710	218	7	improvements	improvement	NOUN
iajs-2710	218	8	at	at	ADP
iajs-2710	218	9	all	all	DET
iajs-2710	218	10	neural	neural	ADJ
iajs-2710	218	11	network	network	NOUN
iajs-2710	218	12	levels	level	NOUN
iajs-2710	218	13	when	when	SCONJ
iajs-2710	218	14	the	the	DET
iajs-2710	218	15	mri	mri	NOUN
iajs-2710	218	16	rotation	rotation	NOUN
iajs-2710	218	17	is	be	AUX
iajs-2710	218	18	included	include	VERB
iajs-2710	218	19	with	with	ADP
iajs-2710	218	20	and	and	CCONJ
iajs-2710	218	21	without	without	ADP
iajs-2710	218	22	clean	clean	ADJ
iajs-2710	218	23	/	/	SYM
iajs-2710	218	24	test	test	NOUN
iajs-2710	218	25	.	.	PUNCT
iajs-2710	219	1	in	in	ADP
iajs-2710	219	2	fact	fact	NOUN
iajs-2710	219	3	,	,	PUNCT
iajs-2710	219	4	the	the	PRON
iajs-2710	219	5	mri	mri	NOUN
iajs-2710	219	6	scan	scan	AUX
iajs-2710	219	7	map	map	VERB
iajs-2710	219	8	image	image	NOUN
iajs-2710	219	9	quality	quality	NOUN
iajs-2710	219	10	for	for	ADP
iajs-2710	219	11	the	the	DET
iajs-2710	219	12	neural	neural	ADJ
iajs-2710	219	13	network	network	NOUN
iajs-2710	219	14	psnr	psnr	NOUN
iajs-2710	219	15	level	level	NOUN
iajs-2710	219	16	2.5	2.5	NUM
iajs-2710	219	17	is	be	AUX
iajs-2710	219	18	relatively	relatively	ADV
iajs-2710	219	19	close	close	ADJ
iajs-2710	219	20	to	to	ADP
iajs-2710	219	21	both	both	DET
iajs-2710	219	22	the	the	DET
iajs-2710	219	23	empirical	empirical	ADJ
iajs-2710	219	24	.	.	PUNCT
iajs-2710	220	1	table	table	NOUN
iajs-2710	220	2	2	2	NUM
iajs-2710	220	3	:	:	PUNCT
iajs-2710	220	4	results	result	NOUN
iajs-2710	220	5	comparing	compare	VERB
iajs-2710	220	6	the	the	DET
iajs-2710	220	7	neural	neural	ADJ
iajs-2710	220	8	network	network	NOUN
iajs-2710	220	9	and	and	CCONJ
iajs-2710	220	10	empirical	empirical	ADJ
iajs-2710	220	11	residual	residual	ADJ
iajs-2710	220	12	models	model	NOUN
iajs-2710	220	13	.	.	PUNCT
iajs-2710	221	1	cleaning	clean	VERB
iajs-2710	221	2	and	and	CCONJ
iajs-2710	221	3	testing	testing	NOUN
iajs-2710	221	4	values	value	NOUN
iajs-2710	221	5	are	be	AUX
iajs-2710	221	6	computed	compute	VERB
iajs-2710	221	7	by	by	ADP
iajs-2710	221	8	comparing	compare	VERB
iajs-2710	221	9	the	the	DET
iajs-2710	221	10	predicted	predict	VERB
iajs-2710	221	11	values	value	NOUN
iajs-2710	221	12	to	to	ADP
iajs-2710	221	13	the	the	DET
iajs-2710	221	14	mri	mri	NOUN
iajs-2710	221	15	scans	scan	NOUN
iajs-2710	221	16	found	find	VERB
iajs-2710	221	17	using	use	VERB
iajs-2710	221	18	the	the	DET
iajs-2710	221	19	baseline	baseline	ADJ
iajs-2710	221	20	dictionary	dictionary	ADJ
iajs-2710	221	21	neural	neural	ADJ
iajs-2710	221	22	network	network	NOUN
iajs-2710	221	23	method	method	NOUN
iajs-2710	221	24	.	.	PUNCT
iajs-2710	222	1	synthetic	synthetic	ADJ
iajs-2710	222	2	model	model	NOUN
iajs-2710	222	3	clean	clean	PROPN
iajs-2710	222	4	test	test	PROPN
iajs-2710	222	5	clean	clean	PROPN
iajs-2710	222	6	test	test	NOUN
iajs-2710	222	7	clean	clean	PROPN
iajs-2710	222	8	signal	signal	VERB
iajs-2710	222	9	0.002	0.002	NUM
iajs-2710	222	10	0.805	0.805	NUM
iajs-2710	222	11	0.002	0.002	NUM
iajs-2710	222	12	0.148	0.148	NUM
iajs-2710	222	13	neural	neural	ADJ
iajs-2710	222	14	network	network	NOUN
iajs-2710	222	15	psnr	psnr	NOUN
iajs-2710	222	16	60	60	NUM
iajs-2710	222	17	0.009	0.009	NUM
iajs-2710	222	18	0.896	0.896	NUM
iajs-2710	222	19	0.004	0.004	NUM
iajs-2710	222	20	0.157	0.157	NUM
iajs-2710	222	21	neural	neural	ADJ
iajs-2710	222	22	network	network	NOUN
iajs-2710	222	23	psnr	psnr	NOUN
iajs-2710	222	24	40	40	NUM
iajs-2710	222	25	0.003	0.003	NUM
iajs-2710	222	26	0.937	0.937	NUM
iajs-2710	222	27	0.006	0.006	NUM
iajs-2710	222	28	0.161	0.161	NUM
iajs-2710	222	29	neural	neural	ADJ
iajs-2710	222	30	network	network	NOUN
iajs-2710	222	31	psnr	psnr	NOUN
iajs-2710	222	32	20	20	NUM
iajs-2710	222	33	0.005	0.005	NUM
iajs-2710	222	34	1.039	1.039	NUM
iajs-2710	222	35	0.013	0.013	NUM
iajs-2710	222	36	0.215	0.215	NUM
iajs-2710	222	37	neural	neural	ADJ
iajs-2710	222	38	network	network	NOUN
iajs-2710	222	39	psnr	psnr	NOUN
iajs-2710	222	40	10	10	NUM
iajs-2710	222	41	0.013	0.013	NUM
iajs-2710	222	42	1.109	1.109	NUM
iajs-2710	222	43	0.026	0.026	NUM
iajs-2710	222	44	0.270	0.270	NUM
iajs-2710	222	45	neural	neural	ADJ
iajs-2710	222	46	network	network	NOUN
iajs-2710	222	47	psnr	psnr	NOUN
iajs-2710	222	48	5	5	NUM
iajs-2710	222	49	0.027	0.027	NUM
iajs-2710	222	50	1.143	1.143	NUM
iajs-2710	222	51	0.050	0.050	NUM
iajs-2710	222	52	0.317	0.317	NUM
iajs-2710	222	53	neural	neural	ADJ
iajs-2710	222	54	network	network	NOUN
iajs-2710	222	55	psnr	psnr	NOUN
iajs-2710	222	56	2.5	2.5	NUM
iajs-2710	222	57	0.077	0.077	NUM
iajs-2710	222	58	0.923	0.923	NUM
iajs-2710	222	59	0.093	0.093	NUM
iajs-2710	222	60	0.378	0.378	NUM
iajs-2710	222	61	neural	neural	ADJ
iajs-2710	222	62	network	network	NOUN
iajs-2710	222	63	psnr	psnr	NOUN
iajs-2710	222	64	1.25	1.25	NUM
iajs-2710	222	65	0.223	0.223	NUM
iajs-2710	222	66	0.731	0.731	NUM
iajs-2710	222	67	0.165	0.165	NUM
iajs-2710	222	68	0.186	0.186	NUM
iajs-2710	222	69	neural	neural	ADJ
iajs-2710	222	70	network	network	NOUN
iajs-2710	222	71	psnr	psnr	NOUN
iajs-2710	222	72	0.625	0.625	NUM
iajs-2710	222	73	0.492	0.492	NUM
iajs-2710	222	74	0.642	0.642	NUM
iajs-2710	222	75	0.266	0.266	NUM
iajs-2710	222	76	0.209	0.209	NUM
iajs-2710	222	77	empirical	empirical	ADJ
iajs-2710	222	78	residual	residual	ADJ
iajs-2710	222	79	model	model	NOUN
iajs-2710	222	80	[	[	X
iajs-2710	222	81	7	7	NUM
iajs-2710	222	82	]	]	SYM
iajs-2710	222	83	0.058	0.058	NUM
iajs-2710	222	84	0.126	0.126	NUM
iajs-2710	222	85	0.026	0.026	NUM
iajs-2710	222	86	0.071	0.071	NUM
iajs-2710	222	87	table	table	NOUN
iajs-2710	222	88	3	3	NUM
iajs-2710	222	89	:	:	PUNCT
iajs-2710	222	90	we	we	PRON
iajs-2710	222	91	show	show	VERB
iajs-2710	222	92	improvements	improvement	NOUN
iajs-2710	222	93	at	at	ADP
iajs-2710	222	94	all	all	DET
iajs-2710	222	95	neural	neural	ADJ
iajs-2710	222	96	network	network	NOUN
iajs-2710	222	97	levels	level	NOUN
iajs-2710	222	98	when	when	SCONJ
iajs-2710	222	99	the	the	DET
iajs-2710	222	100	mri	mri	NOUN
iajs-2710	222	101	rotation	rotation	NOUN
iajs-2710	222	102	is	be	AUX
iajs-2710	222	103	included	include	VERB
iajs-2710	222	104	with	with	ADP
iajs-2710	222	105	and	and	CCONJ
iajs-2710	222	106	without	without	ADP
iajs-2710	222	107	clean	clean	ADJ
iajs-2710	222	108	/	/	SYM
iajs-2710	222	109	test	test	NOUN
iajs-2710	222	110	.	.	PUNCT
iajs-2710	223	1	in	in	ADP
iajs-2710	223	2	fact	fact	NOUN
iajs-2710	223	3	,	,	PUNCT
iajs-2710	223	4	the	the	PRON
iajs-2710	223	5	mri	mri	NOUN
iajs-2710	223	6	scan	scan	AUX
iajs-2710	223	7	map	map	VERB
iajs-2710	223	8	image	image	NOUN
iajs-2710	223	9	quality	quality	NOUN
iajs-2710	223	10	for	for	ADP
iajs-2710	223	11	the	the	DET
iajs-2710	223	12	neural	neural	ADJ
iajs-2710	223	13	network	network	NOUN
iajs-2710	223	14	psnr	psnr	NOUN
iajs-2710	223	15	level	level	NOUN
iajs-2710	223	16	2.5	2.5	NUM
iajs-2710	223	17	is	be	AUX
iajs-2710	223	18	relatively	relatively	ADV
iajs-2710	223	19	close	close	ADJ
iajs-2710	223	20	to	to	ADP
iajs-2710	223	21	both	both	DET
iajs-2710	223	22	the	the	DET
iajs-2710	223	23	empirical	empirical	ADJ
iajs-2710	223	24	.	.	PUNCT
iajs-2710	224	1	synthetic	synthetic	ADJ
iajs-2710	224	2	model	model	NOUN
iajs-2710	224	3	without	without	ADP
iajs-2710	224	4	clean	clean	ADJ
iajs-2710	224	5	with	with	ADP
iajs-2710	224	6	clean	clean	ADJ
iajs-2710	224	7	without	without	ADP
iajs-2710	224	8	test	test	NOUN
iajs-2710	224	9	with	with	ADP
iajs-2710	224	10	test	test	NOUN
iajs-2710	224	11	clean	clean	VERB
iajs-2710	224	12	0.805	0.805	NUM
iajs-2710	224	13	0.556	0.556	NUM
iajs-2710	224	14	0.148	0.148	NUM
iajs-2710	224	15	0.322	0.322	NUM
iajs-2710	224	16	neural	neural	ADJ
iajs-2710	224	17	network	network	NOUN
iajs-2710	224	18	psnr	psnr	NOUN
iajs-2710	224	19	20	20	NUM
iajs-2710	224	20	1.039	1.039	NUM
iajs-2710	224	21	0.554	0.554	NUM
iajs-2710	224	22	0.215	0.215	NUM
iajs-2710	224	23	0.181	0.181	NUM
iajs-2710	224	24	neural	neural	ADJ
iajs-2710	224	25	network	network	NOUN
iajs-2710	224	26	psnr	psnr	NOUN
iajs-2710	224	27	10	10	NUM
iajs-2710	224	28	1.109	1.109	NUM
iajs-2710	224	29	0.427	0.427	NUM
iajs-2710	224	30	0.270	0.270	NUM
iajs-2710	224	31	0.201	0.201	NUM
iajs-2710	224	32	neural	neural	ADJ
iajs-2710	224	33	network	network	NOUN
iajs-2710	224	34	psnr	psnr	NOUN
iajs-2710	224	35	5	5	NUM
iajs-2710	224	36	1.143	1.143	NUM
iajs-2710	224	37	0.272	0.272	NUM
iajs-2710	224	38	0.317	0.317	NUM
iajs-2710	224	39	0.161	0.161	NUM
iajs-2710	224	40	neural	neural	ADJ
iajs-2710	224	41	network	network	NOUN
iajs-2710	224	42	psnr	psnr	NOUN
iajs-2710	224	43	2.5	2.5	NUM
iajs-2710	224	44	0.923	0.923	NUM
iajs-2710	224	45	0.168	0.168	NUM
iajs-2710	224	46	0.378	0.378	NUM
iajs-2710	224	47	0.119	0.119	NUM
iajs-2710	224	48	neural	neural	ADJ
iajs-2710	224	49	network	network	NOUN
iajs-2710	224	50	psnr	psnr	NOUN
iajs-2710	224	51	1.25	1.25	NUM
iajs-2710	224	52	0.731	0.731	NUM
iajs-2710	224	53	0.191	0.191	NUM
iajs-2710	224	54	0.186	0.186	NUM
iajs-2710	224	55	0.069	0.069	NUM
iajs-2710	224	56	neural	neural	ADJ
iajs-2710	224	57	network	network	NOUN
iajs-2710	224	58	psnr	psnr	NOUN
iajs-2710	224	59	0.625	0.625	NUM
iajs-2710	224	60	0.642	0.642	NUM
iajs-2710	224	61	0.243	0.243	NUM
iajs-2710	224	62	0.209	0.209	NUM
iajs-2710	224	63	0.113	0.113	NUM
iajs-2710	224	64	empirical	empirical	ADJ
iajs-2710	224	65	residual	residual	ADJ
iajs-2710	224	66	model	model	NOUN
iajs-2710	224	67	[	[	X
iajs-2710	224	68	3	3	NUM
iajs-2710	224	69	]	]	PUNCT
iajs-2710	224	70	0.902	0.902	NUM
iajs-2710	224	71	0.126	0.126	NUM
iajs-2710	224	72	0.148	0.148	NUM
iajs-2710	224	73	0.071	0.071	NUM
iajs-2710	224	74	5	5	NUM
iajs-2710	224	75	.	.	PUNCT
iajs-2710	224	76	discussion	discussion	NOUN
iajs-2710	224	77	the	the	DET
iajs-2710	224	78	detection	detection	NOUN
iajs-2710	224	79	of	of	ADP
iajs-2710	224	80	the	the	DET
iajs-2710	224	81	first	first	ADJ
iajs-2710	224	82	and	and	CCONJ
iajs-2710	224	83	last	last	ADJ
iajs-2710	224	84	brains	brain	NOUN
iajs-2710	224	85	of	of	ADP
iajs-2710	224	86	the	the	DET
iajs-2710	224	87	line	line	NOUN
iajs-2710	224	88	is	be	AUX
iajs-2710	224	89	checked	check	VERB
iajs-2710	224	90	against	against	ADP
iajs-2710	224	91	the	the	DET
iajs-2710	224	92	median	median	ADJ
iajs-2710	224	93	bounding	bounding	NOUN
iajs-2710	224	94	box	box	NOUN
iajs-2710	224	95	contour	contour	NOUN
iajs-2710	224	96	height	height	NOUN
iajs-2710	224	97	.	.	PUNCT
iajs-2710	225	1	if	if	SCONJ
iajs-2710	225	2	the	the	DET
iajs-2710	225	3	height	height	NOUN
iajs-2710	225	4	difference	difference	NOUN
iajs-2710	225	5	to	to	ADP
iajs-2710	225	6	the	the	DET
iajs-2710	225	7	median	median	ADJ
iajs-2710	225	8	contour	contour	NOUN
iajs-2710	225	9	height	height	NOUN
iajs-2710	225	10	is	be	AUX
iajs-2710	225	11	larger	large	ADJ
iajs-2710	225	12	than	than	ADP
iajs-2710	225	13	25	25	NUM
iajs-2710	225	14	%	%	NOUN
iajs-2710	225	15	,	,	PUNCT
iajs-2710	225	16	the	the	DET
iajs-2710	225	17	bounding	bounding	NOUN
iajs-2710	225	18	box	box	NOUN
iajs-2710	225	19	does	do	AUX
iajs-2710	225	20	not	not	PART
iajs-2710	225	21	overlap	overlap	VERB
iajs-2710	225	22	with	with	ADP
iajs-2710	225	23	the	the	DET
iajs-2710	225	24	bounding	bounding	NOUN
iajs-2710	225	25	box	box	NOUN
iajs-2710	225	26	of	of	ADP
iajs-2710	225	27	the	the	DET
iajs-2710	225	28	neighboring	neighboring	NOUN
iajs-2710	225	29	contour	contour	NOUN
iajs-2710	225	30	,	,	PUNCT
iajs-2710	225	31	and	and	CCONJ
iajs-2710	225	32	the	the	DET
iajs-2710	225	33	bounding	bounding	NOUN
iajs-2710	225	34	box	box	NOUN
iajs-2710	225	35	width	width	NOUN
iajs-2710	225	36	is	be	AUX
iajs-2710	225	37	smaller	small	ADJ
iajs-2710	225	38	than	than	ADP
iajs-2710	225	39	33	33	NUM
iajs-2710	225	40	%	%	NOUN
iajs-2710	225	41	of	of	ADP
iajs-2710	225	42	the	the	DET
iajs-2710	225	43	text	text	NOUN
iajs-2710	225	44	region	region	NOUN
iajs-2710	225	45	width	width	NOUN
iajs-2710	225	46	,	,	PUNCT
iajs-2710	225	47	the	the	DET
iajs-2710	225	48	contour	contour	NOUN
iajs-2710	225	49	is	be	AUX
iajs-2710	225	50	removed	remove	VERB
iajs-2710	225	51	.	.	PUNCT
iajs-2710	226	1	at	at	ADP
iajs-2710	226	2	this	this	DET
iajs-2710	226	3	point	point	NOUN
iajs-2710	226	4	,	,	PUNCT
iajs-2710	226	5	the	the	DET
iajs-2710	226	6	preprocessing	preprocessing	NOUN
iajs-2710	226	7	is	be	AUX
iajs-2710	226	8	complete	complete	ADJ
iajs-2710	226	9	.	.	PUNCT
iajs-2710	227	1	however	however	ADV
iajs-2710	227	2	,	,	PUNCT
iajs-2710	227	3	the	the	DET
iajs-2710	227	4	brains	brain	NOUN
iajs-2710	227	5	only	only	ADV
iajs-2710	227	6	consist	consist	VERB
iajs-2710	227	7	of	of	ADP
iajs-2710	227	8	borders	border	NOUN
iajs-2710	227	9	,	,	PUNCT
iajs-2710	227	10	as	as	SCONJ
iajs-2710	227	11	all	all	DET
iajs-2710	227	12	processing	processing	NOUN
iajs-2710	227	13	was	be	AUX
iajs-2710	227	14	done	do	VERB
iajs-2710	227	15	on	on	ADP
iajs-2710	227	16	an	an	DET
iajs-2710	227	17	image	image	NOUN
iajs-2710	227	18	created	create	VERB
iajs-2710	227	19	by	by	ADP
iajs-2710	227	20	mri	mri	NOUN
iajs-2710	227	21	the	the	DET
iajs-2710	227	22	gradient	gradient	ADJ
iajs-2710	227	23	magnitude	magnitude	NOUN
iajs-2710	227	24	.	.	PUNCT
iajs-2710	228	1	such	such	ADJ
iajs-2710	228	2	images	image	NOUN
iajs-2710	228	3	can	can	AUX
iajs-2710	228	4	not	not	PART
iajs-2710	228	5	be	be	AUX
iajs-2710	228	6	processed	process	VERB
iajs-2710	228	7	by	by	ADP
iajs-2710	228	8	the	the	DET
iajs-2710	228	9	tesseract	tesseract	ADJ
iajs-2710	228	10	mri	mri	NOUN
iajs-2710	228	11	.	.	PUNCT
iajs-2710	229	1	to	to	PART
iajs-2710	229	2	retrieve	retrieve	VERB
iajs-2710	229	3	filled	fill	VERB
iajs-2710	229	4	brains	brain	NOUN
iajs-2710	229	5	,	,	PUNCT
iajs-2710	229	6	the	the	DET
iajs-2710	229	7	original	original	ADJ
iajs-2710	229	8	unmodified	unmodified	ADJ
iajs-2710	229	9	input	input	NOUN
iajs-2710	229	10	image	image	NOUN
iajs-2710	229	11	is	be	AUX
iajs-2710	229	12	adaptively	adaptively	ADV
iajs-2710	229	13	mri	mri	NOUN
iajs-2710	229	14	with	with	ADP
iajs-2710	229	15	block	block	NOUN
iajs-2710	229	16	size	size	NOUN
iajs-2710	229	17	and	and	CCONJ
iajs-2710	229	18	the	the	DET
iajs-2710	229	19	filtered	filter	VERB
iajs-2710	229	20	image	image	NOUN
iajs-2710	229	21	ibn	ibn	PROPN
iajs-2710	229	22	al	al	PROPN
iajs-2710	229	23	-	-	PUNCT
iajs-2710	229	24	haitham	haitham	PROPN
iajs-2710	229	25	jour	jour	X
iajs-2710	229	26	.	.	PROPN
iajs-2710	230	1	for	for	ADP
iajs-2710	230	2	pure	pure	ADJ
iajs-2710	230	3	&	&	CCONJ
iajs-2710	230	4	appl	appl	PROPN
iajs-2710	230	5	.	.	PUNCT
iajs-2710	231	1	sci	sci	PROPN
iajs-2710	231	2	.	.	PROPN
iajs-2710	232	1	34(4)2021	34(4)2021	NUM
iajs-2710	232	2	140	140	NUM
iajs-2710	232	3	is	be	AUX
iajs-2710	232	4	morphologically	morphologically	ADV
iajs-2710	232	5	opened	open	VERB
iajs-2710	232	6	with	with	ADP
iajs-2710	232	7	a	a	DET
iajs-2710	232	8	20×15	20×15	ADV
iajs-2710	232	9	ellipsoidal	ellipsoidal	ADJ
iajs-2710	232	10	structuring	structuring	NOUN
iajs-2710	232	11	element	element	NOUN
iajs-2710	232	12	.	.	PUNCT
iajs-2710	233	1	the	the	DET
iajs-2710	233	2	large	large	ADJ
iajs-2710	233	3	black	black	ADJ
iajs-2710	233	4	region	region	NOUN
iajs-2710	233	5	is	be	AUX
iajs-2710	233	6	caused	cause	VERB
iajs-2710	233	7	by	by	ADP
iajs-2710	233	8	the	the	DET
iajs-2710	233	9	rust	rust	NOUN
iajs-2710	233	10	stain	stain	NOUN
iajs-2710	233	11	.	.	PUNCT
iajs-2710	234	1	the	the	DET
iajs-2710	234	2	mri	mri	NOUN
iajs-2710	234	3	result	result	NOUN
iajs-2710	234	4	for	for	ADP
iajs-2710	234	5	the	the	DET
iajs-2710	234	6	second	second	ADJ
iajs-2710	234	7	regions	region	NOUN
iajs-2710	234	8	,	,	PUNCT
iajs-2710	234	9	also	also	ADV
iajs-2710	234	10	contains	contain	VERB
iajs-2710	234	11	some	some	DET
iajs-2710	234	12	clutter	clutter	NOUN
iajs-2710	234	13	.	.	PUNCT
iajs-2710	235	1	when	when	SCONJ
iajs-2710	235	2	copying	copy	VERB
iajs-2710	235	3	from	from	ADP
iajs-2710	235	4	the	the	DET
iajs-2710	235	5	adaptively	adaptively	ADV
iajs-2710	235	6	mri	mri	NOUN
iajs-2710	235	7	image	image	NOUN
iajs-2710	235	8	,	,	PUNCT
iajs-2710	235	9	the	the	DET
iajs-2710	235	10	opened	open	VERB
iajs-2710	235	11	image	image	NOUN
iajs-2710	235	12	is	be	AUX
iajs-2710	235	13	used	use	VERB
iajs-2710	235	14	as	as	ADP
iajs-2710	235	15	a	a	DET
iajs-2710	235	16	mask	mask	NOUN
iajs-2710	235	17	,	,	PUNCT
iajs-2710	235	18	as	as	SCONJ
iajs-2710	235	19	mentioned	mention	VERB
iajs-2710	235	20	in	in	ADP
iajs-2710	235	21	[	[	X
iajs-2710	235	22	12	12	NUM
iajs-2710	235	23	]	]	PUNCT
iajs-2710	235	24	.	.	PUNCT
iajs-2710	236	1	the	the	DET
iajs-2710	236	2	results	result	NOUN
iajs-2710	236	3	for	for	ADP
iajs-2710	236	4	both	both	DET
iajs-2710	236	5	regions	region	NOUN
iajs-2710	236	6	that	that	PRON
iajs-2710	236	7	are	be	AUX
iajs-2710	236	8	passed	pass	VERB
iajs-2710	236	9	to	to	ADP
iajs-2710	236	10	tesseract	tesseract	NOUN
iajs-2710	236	11	are	be	AUX
iajs-2710	236	12	everything	everything	PRON
iajs-2710	236	13	that	that	PRON
iajs-2710	236	14	does	do	AUX
iajs-2710	236	15	not	not	PART
iajs-2710	236	16	belong	belong	VERB
iajs-2710	236	17	to	to	ADP
iajs-2710	236	18	a	a	DET
iajs-2710	236	19	removed	removed	ADJ
iajs-2710	236	20	brain	brain	NOUN
iajs-2710	236	21	.	.	PUNCT
iajs-2710	237	1	sample	sample	NOUN
iajs-2710	237	2	of	of	ADP
iajs-2710	237	3	the	the	DET
iajs-2710	237	4	brain	brain	NOUN
iajs-2710	237	5	image	image	NOUN
iajs-2710	237	6	at	at	ADP
iajs-2710	237	7	the	the	DET
iajs-2710	237	8	top	top	ADJ
iajs-2710	237	9	right	right	NOUN
iajs-2710	237	10	,	,	PUNCT
iajs-2710	237	11	and	and	CCONJ
iajs-2710	237	12	a	a	DET
iajs-2710	237	13	new	new	ADJ
iajs-2710	237	14	input	input	NOUN
iajs-2710	237	15	image	image	NOUN
iajs-2710	237	16	containing	contain	VERB
iajs-2710	237	17	the	the	DET
iajs-2710	237	18	right	right	ADJ
iajs-2710	237	19	part	part	NOUN
iajs-2710	237	20	of	of	ADP
iajs-2710	237	21	the	the	DET
iajs-2710	237	22	brain	brain	NOUN
iajs-2710	237	23	at	at	ADP
iajs-2710	237	24	a	a	DET
iajs-2710	237	25	larger	large	ADJ
iajs-2710	237	26	magnification	magnification	NOUN
iajs-2710	237	27	further	far	ADV
iajs-2710	237	28	,	,	PUNCT
iajs-2710	237	29	the	the	DET
iajs-2710	237	30	extracted	extract	VERB
iajs-2710	237	31	key	key	ADJ
iajs-2710	237	32	points	point	NOUN
iajs-2710	237	33	,	,	PUNCT
iajs-2710	237	34	the	the	DET
iajs-2710	237	35	calculated	calculate	VERB
iajs-2710	237	36	matches	match	NOUN
iajs-2710	237	37	between	between	ADP
iajs-2710	237	38	the	the	DET
iajs-2710	237	39	images	image	NOUN
iajs-2710	237	40	,	,	PUNCT
iajs-2710	237	41	and	and	CCONJ
iajs-2710	237	42	the	the	DET
iajs-2710	237	43	location	location	NOUN
iajs-2710	237	44	of	of	ADP
iajs-2710	237	45	the	the	DET
iajs-2710	237	46	new	new	ADJ
iajs-2710	237	47	image	image	NOUN
iajs-2710	237	48	in	in	ADP
iajs-2710	237	49	relation	relation	NOUN
iajs-2710	237	50	to	to	ADP
iajs-2710	237	51	the	the	DET
iajs-2710	237	52	reference	reference	NOUN
iajs-2710	237	53	brain	brain	NOUN
iajs-2710	237	54	are	be	AUX
iajs-2710	237	55	displayed	display	VERB
iajs-2710	237	56	.	.	PUNCT
iajs-2710	238	1	each	each	DET
iajs-2710	238	2	completely	completely	ADV
iajs-2710	238	3	visible	visible	ADJ
iajs-2710	238	4	region	region	NOUN
iajs-2710	238	5	is	be	AUX
iajs-2710	238	6	warped	warp	VERB
iajs-2710	238	7	into	into	ADP
iajs-2710	238	8	its	its	PRON
iajs-2710	238	9	upright	upright	ADJ
iajs-2710	238	10	position	position	NOUN
iajs-2710	238	11	,	,	PUNCT
iajs-2710	238	12	where	where	SCONJ
iajs-2710	238	13	the	the	DET
iajs-2710	238	14	size	size	NOUN
iajs-2710	238	15	is	be	AUX
iajs-2710	238	16	approximately	approximately	ADV
iajs-2710	238	17	the	the	DET
iajs-2710	238	18	same	same	ADJ
iajs-2710	238	19	as	as	ADP
iajs-2710	238	20	in	in	ADP
iajs-2710	238	21	the	the	DET
iajs-2710	238	22	new	new	ADJ
iajs-2710	238	23	input	input	NOUN
iajs-2710	238	24	image	image	NOUN
iajs-2710	238	25	.	.	PUNCT
iajs-2710	239	1	since	since	SCONJ
iajs-2710	239	2	each	each	DET
iajs-2710	239	3	region	region	NOUN
iajs-2710	239	4	is	be	AUX
iajs-2710	239	5	processed	process	VERB
iajs-2710	239	6	and	and	CCONJ
iajs-2710	239	7	warped	warp	VERB
iajs-2710	239	8	separately	separately	ADV
iajs-2710	239	9	,	,	PUNCT
iajs-2710	239	10	the	the	DET
iajs-2710	239	11	process	process	NOUN
iajs-2710	239	12	can	can	AUX
iajs-2710	239	13	be	be	AUX
iajs-2710	239	14	executed	execute	VERB
iajs-2710	239	15	in	in	ADP
iajs-2710	239	16	parallel	parallel	NOUN
iajs-2710	239	17	,	,	PUNCT
iajs-2710	239	18	and	and	CCONJ
iajs-2710	239	19	fewer	few	ADJ
iajs-2710	239	20	resources	resource	NOUN
iajs-2710	239	21	are	be	AUX
iajs-2710	239	22	needed	need	VERB
iajs-2710	239	23	since	since	SCONJ
iajs-2710	239	24	not	not	PART
iajs-2710	239	25	the	the	DET
iajs-2710	239	26	entire	entire	ADJ
iajs-2710	239	27	image	image	NOUN
iajs-2710	239	28	must	must	AUX
iajs-2710	239	29	be	be	AUX
iajs-2710	239	30	processed	process	VERB
iajs-2710	239	31	.	.	PUNCT
iajs-2710	240	1	the	the	DET
iajs-2710	240	2	preprocessing	preprocessing	NOUN
iajs-2710	240	3	and	and	CCONJ
iajs-2710	240	4	mri	mri	NOUN
iajs-2710	240	5	steps	step	NOUN
iajs-2710	240	6	,	,	PUNCT
iajs-2710	240	7	as	as	SCONJ
iajs-2710	240	8	described	describe	VERB
iajs-2710	240	9	earlier	early	ADV
iajs-2710	240	10	,	,	PUNCT
iajs-2710	240	11	are	be	AUX
iajs-2710	240	12	executed	execute	VERB
iajs-2710	240	13	for	for	ADP
iajs-2710	240	14	each	each	DET
iajs-2710	240	15	new	new	ADJ
iajs-2710	240	16	region	region	NOUN
iajs-2710	240	17	.	.	PUNCT
iajs-2710	241	1	the	the	DET
iajs-2710	241	2	results	result	NOUN
iajs-2710	241	3	are	be	AUX
iajs-2710	241	4	merged	merge	VERB
iajs-2710	241	5	with	with	ADP
iajs-2710	241	6	the	the	DET
iajs-2710	241	7	existing	exist	VERB
iajs-2710	241	8	ones	one	NOUN
iajs-2710	241	9	,	,	PUNCT
iajs-2710	241	10	where	where	SCONJ
iajs-2710	241	11	for	for	ADP
iajs-2710	241	12	each	each	DET
iajs-2710	241	13	region	region	NOUN
iajs-2710	241	14	only	only	ADV
iajs-2710	241	15	the	the	DET
iajs-2710	241	16	one	one	NOUN
iajs-2710	241	17	with	with	ADP
iajs-2710	241	18	the	the	DET
iajs-2710	241	19	highest	high	ADJ
iajs-2710	241	20	mri	mri	NOUN
iajs-2710	241	21	confidence	confidence	NOUN
iajs-2710	241	22	is	be	AUX
iajs-2710	241	23	kept	keep	VERB
iajs-2710	241	24	.	.	PUNCT
iajs-2710	242	1	6	6	X
iajs-2710	242	2	.	.	X
iajs-2710	242	3	conclusion	conclusion	NOUN
iajs-2710	242	4	in	in	ADP
iajs-2710	242	5	this	this	DET
iajs-2710	242	6	novel	novel	ADJ
iajs-2710	242	7	research	research	NOUN
iajs-2710	242	8	work	work	NOUN
iajs-2710	242	9	,	,	PUNCT
iajs-2710	242	10	we	we	PRON
iajs-2710	242	11	have	have	AUX
iajs-2710	242	12	developed	develop	VERB
iajs-2710	242	13	an	an	DET
iajs-2710	242	14	intelligence	intelligence	NOUN
iajs-2710	242	15	expert	expert	NOUN
iajs-2710	242	16	system	system	NOUN
iajs-2710	242	17	for	for	ADP
iajs-2710	242	18	the	the	DET
iajs-2710	242	19	detection	detection	NOUN
iajs-2710	242	20	of	of	ADP
iajs-2710	242	21	brain	brain	NOUN
iajs-2710	242	22	mr	mr	PROPN
iajs-2710	242	23	using	use	VERB
iajs-2710	242	24	convolutional	convolutional	ADJ
iajs-2710	242	25	neural	neural	ADJ
iajs-2710	242	26	network	network	NOUN
iajs-2710	242	27	.	.	PUNCT
iajs-2710	243	1	deep	deep	ADJ
iajs-2710	243	2	learning	learning	NOUN
iajs-2710	243	3	methods	method	NOUN
iajs-2710	243	4	demonstrated	demonstrate	VERB
iajs-2710	243	5	good	good	ADJ
iajs-2710	243	6	detection	detection	NOUN
iajs-2710	243	7	and	and	CCONJ
iajs-2710	243	8	accuracy	accuracy	NOUN
iajs-2710	243	9	.	.	PUNCT
iajs-2710	244	1	for	for	ADP
iajs-2710	244	2	the	the	DET
iajs-2710	244	3	training	training	NOUN
iajs-2710	244	4	,	,	PUNCT
iajs-2710	244	5	testing	testing	NOUN
iajs-2710	244	6	,	,	PUNCT
iajs-2710	244	7	and	and	CCONJ
iajs-2710	244	8	validation	validation	NOUN
iajs-2710	244	9	of	of	ADP
iajs-2710	244	10	an	an	DET
iajs-2710	244	11	open	open	ADJ
iajs-2710	244	12	-	-	PUNCT
iajs-2710	244	13	mri	mri	NOUN
iajs-2710	244	14	-	-	PUNCT
iajs-2710	244	15	based	base	VERB
iajs-2710	244	16	dataset	dataset	NOUN
iajs-2710	244	17	for	for	ADP
iajs-2710	244	18	brain	brain	NOUN
iajs-2710	244	19	diseases	disease	NOUN
iajs-2710	244	20	;	;	PUNCT
iajs-2710	244	21	well	well	ADV
iajs-2710	244	22	-	-	PUNCT
iajs-2710	244	23	known	know	VERB
iajs-2710	244	24	matlab	matlab	PROPN
iajs-2710	244	25	r2018b	r2018b	NOUN
iajs-2710	244	26	software	software	NOUN
iajs-2710	244	27	was	be	AUX
iajs-2710	244	28	used	use	VERB
iajs-2710	244	29	for	for	ADP
iajs-2710	244	30	this	this	DET
iajs-2710	244	31	purpose	purpose	NOUN
iajs-2710	244	32	.	.	PUNCT
iajs-2710	245	1	a	a	DET
iajs-2710	245	2	convolutional	convolutional	ADJ
iajs-2710	245	3	neural	neural	ADJ
iajs-2710	245	4	network	network	NOUN
iajs-2710	245	5	is	be	AUX
iajs-2710	245	6	written	write	VERB
iajs-2710	245	7	with	with	ADP
iajs-2710	245	8	one	one	NUM
iajs-2710	245	9	hidden	hide	VERB
iajs-2710	245	10	layer	layer	NOUN
iajs-2710	245	11	,	,	PUNCT
iajs-2710	245	12	16	16	NUM
iajs-2710	245	13	input	input	NOUN
iajs-2710	245	14	neurons	neuron	NOUN
iajs-2710	245	15	and	and	CCONJ
iajs-2710	245	16	two	two	NUM
iajs-2710	245	17	outputs	output	NOUN
iajs-2710	245	18	either	either	CCONJ
iajs-2710	245	19	healthy	healthy	ADJ
iajs-2710	245	20	or	or	CCONJ
iajs-2710	245	21	not	not	PART
iajs-2710	245	22	.	.	PUNCT
iajs-2710	246	1	the	the	DET
iajs-2710	246	2	data	datum	NOUN
iajs-2710	246	3	are	be	AUX
iajs-2710	246	4	split	split	VERB
iajs-2710	246	5	into	into	ADP
iajs-2710	246	6	train	train	NOUN
iajs-2710	246	7	and	and	CCONJ
iajs-2710	246	8	test	test	NOUN
iajs-2710	246	9	datasets	dataset	NOUN
iajs-2710	246	10	with	with	ADP
iajs-2710	246	11	70	70	NUM
iajs-2710	246	12	%	%	NOUN
iajs-2710	246	13	for	for	ADP
iajs-2710	246	14	training,15	training,15	NOUN
iajs-2710	246	15	%	%	NOUN
iajs-2710	246	16	validation	validation	NOUN
iajs-2710	246	17	,	,	PUNCT
iajs-2710	246	18	and	and	CCONJ
iajs-2710	246	19	15	15	NUM
iajs-2710	246	20	%	%	NOUN
iajs-2710	246	21	for	for	ADP
iajs-2710	246	22	testing	testing	NOUN
iajs-2710	246	23	.	.	PUNCT
iajs-2710	247	1	accuracy	accuracy	NOUN
iajs-2710	247	2	is	be	AUX
iajs-2710	247	3	found	find	VERB
iajs-2710	247	4	to	to	PART
iajs-2710	247	5	vary	vary	VERB
iajs-2710	247	6	between	between	ADP
iajs-2710	247	7	91	91	NUM
iajs-2710	247	8	-	-	SYM
iajs-2710	247	9	92	92	NUM
iajs-2710	247	10	%	%	NOUN
iajs-2710	247	11	depending	depend	VERB
iajs-2710	247	12	on	on	ADP
iajs-2710	247	13	the	the	DET
iajs-2710	247	14	number	number	NOUN
iajs-2710	247	15	of	of	ADP
iajs-2710	247	16	iteration	iteration	NOUN
iajs-2710	247	17	or	or	CCONJ
iajs-2710	247	18	epochs	epoch	NOUN
iajs-2710	247	19	.	.	PUNCT
iajs-2710	248	1	moreover	moreover	ADV
iajs-2710	248	2	,	,	PUNCT
iajs-2710	248	3	the	the	DET
iajs-2710	248	4	cnn	cnn	PROPN
iajs-2710	248	5	method	method	NOUN
iajs-2710	248	6	can	can	AUX
iajs-2710	248	7	work	work	VERB
iajs-2710	248	8	well	well	ADV
iajs-2710	248	9	with	with	ADP
iajs-2710	248	10	,	,	PUNCT
iajs-2710	248	11	varying	vary	VERB
iajs-2710	248	12	number	number	NOUN
iajs-2710	248	13	of	of	ADP
iajs-2710	248	14	features	feature	NOUN
iajs-2710	248	15	.	.	PUNCT
iajs-2710	249	1	generally	generally	ADV
iajs-2710	249	2	,	,	PUNCT
iajs-2710	249	3	its	its	PRON
iajs-2710	249	4	performance	performance	NOUN
iajs-2710	249	5	for	for	ADP
iajs-2710	249	6	detection	detection	NOUN
iajs-2710	249	7	purposes	purpose	NOUN
iajs-2710	249	8	does	do	AUX
iajs-2710	249	9	not	not	PART
iajs-2710	249	10	suffer	suffer	VERB
iajs-2710	249	11	from	from	ADP
iajs-2710	249	12	extra	extra	ADJ
iajs-2710	249	13	features	feature	NOUN
iajs-2710	249	14	,	,	PUNCT
iajs-2710	249	15	meaning	mean	VERB
iajs-2710	249	16	that	that	SCONJ
iajs-2710	249	17	in	in	ADP
iajs-2710	249	18	,	,	PUNCT
iajs-2710	249	19	real	real	ADJ
iajs-2710	249	20	-	-	PUNCT
iajs-2710	249	21	world	world	NOUN
iajs-2710	249	22	environment	environment	NOUN
iajs-2710	249	23	they	they	PRON
iajs-2710	249	24	offer	offer	VERB
iajs-2710	249	25	the	the	DET
iajs-2710	249	26	possibility	possibility	NOUN
iajs-2710	249	27	of	of	ADP
iajs-2710	249	28	using	use	VERB
iajs-2710	249	29	all	all	DET
iajs-2710	249	30	existing	exist	VERB
iajs-2710	249	31	data	datum	NOUN
iajs-2710	249	32	features	feature	NOUN
iajs-2710	249	33	.	.	PUNCT
iajs-2710	250	1	it	it	PRON
iajs-2710	250	2	was	be	AUX
iajs-2710	250	3	also	also	ADV
iajs-2710	250	4	shown	show	VERB
iajs-2710	250	5	that	that	SCONJ
iajs-2710	250	6	there	there	PRON
iajs-2710	250	7	may	may	AUX
iajs-2710	250	8	not	not	PART
iajs-2710	250	9	be	be	AUX
iajs-2710	250	10	a	a	DET
iajs-2710	250	11	need	need	NOUN
iajs-2710	250	12	to	to	PART
iajs-2710	250	13	create	create	VERB
iajs-2710	250	14	different	different	ADJ
iajs-2710	250	15	models	model	NOUN
iajs-2710	250	16	for	for	ADP
iajs-2710	250	17	brain	brain	NOUN
iajs-2710	250	18	disease	disease	NOUN
iajs-2710	250	19	detection	detection	NOUN
iajs-2710	250	20	and	and	CCONJ
iajs-2710	250	21	that	that	SCONJ
iajs-2710	250	22	one	one	NUM
iajs-2710	250	23	model	model	NOUN
iajs-2710	250	24	trained	train	VERB
iajs-2710	250	25	on	on	ADP
iajs-2710	250	26	data	datum	NOUN
iajs-2710	250	27	can	can	AUX
iajs-2710	250	28	detect	detect	VERB
iajs-2710	250	29	brain	brain	NOUN
iajs-2710	250	30	disease	disease	NOUN
iajs-2710	250	31	based	base	VERB
iajs-2710	250	32	on	on	ADP
iajs-2710	250	33	mr	mr	PROPN
iajs-2710	250	34	samples	sample	NOUN
iajs-2710	250	35	efficiently	efficiently	ADV
iajs-2710	250	36	.	.	PUNCT
iajs-2710	251	1	the	the	DET
iajs-2710	251	2	cnn	cnn	PROPN
iajs-2710	251	3	inception	inception	PROPN
iajs-2710	251	4	network	network	PROPN
iajs-2710	251	5	seems	seem	VERB
iajs-2710	251	6	to	to	PART
iajs-2710	251	7	be	be	AUX
iajs-2710	251	8	a	a	DET
iajs-2710	251	9	suitable	suitable	ADJ
iajs-2710	251	10	choice	choice	NOUN
iajs-2710	251	11	for	for	ADP
iajs-2710	251	12	the	the	DET
iajs-2710	251	13	evaluation	evaluation	NOUN
iajs-2710	251	14	of	of	ADP
iajs-2710	251	15	the	the	DET
iajs-2710	251	16	synthetic	synthetic	ADJ
iajs-2710	251	17	mri	mri	NOUN
iajs-2710	251	18	samples	sample	NOUN
iajs-2710	251	19	with	with	ADP
iajs-2710	251	20	3000	3000	NUM
iajs-2710	251	21	features	feature	NOUN
iajs-2710	251	22	and	and	CCONJ
iajs-2710	251	23	12000	12000	NUM
iajs-2710	251	24	samples	sample	NOUN
iajs-2710	251	25	of	of	ADP
iajs-2710	251	26	images	image	NOUN
iajs-2710	251	27	as	as	SCONJ
iajs-2710	251	28	data	data	NOUN
iajs-2710	251	29	augmentation	augmentation	NOUN
iajs-2710	251	30	capacities	capacity	NOUN
iajs-2710	251	31	favor	favor	VERB
iajs-2710	251	32	data	datum	NOUN
iajs-2710	251	33	that	that	PRON
iajs-2710	251	34	is	be	AUX
iajs-2710	251	35	similar	similar	ADJ
iajs-2710	251	36	to	to	ADP
iajs-2710	251	37	the	the	DET
iajs-2710	251	38	original	original	ADJ
iajs-2710	251	39	training	training	NOUN
iajs-2710	251	40	set	set	NOUN
iajs-2710	251	41	and	and	CCONJ
iajs-2710	251	42	thus	thus	ADV
iajs-2710	251	43	unlikely	unlikely	ADJ
iajs-2710	251	44	to	to	PART
iajs-2710	251	45	contain	contain	VERB
iajs-2710	251	46	new	new	ADJ
iajs-2710	251	47	information	information	NOUN
iajs-2710	251	48	content	content	NOUN
iajs-2710	251	49	with	with	ADP
iajs-2710	251	50	an	an	DET
iajs-2710	251	51	accuracy	accuracy	NOUN
iajs-2710	251	52	of	of	ADP
iajs-2710	251	53	98.68	98.68	NUM
iajs-2710	251	54	%	%	NOUN
iajs-2710	251	55	.	.	PUNCT
iajs-2710	252	1	the	the	DET
iajs-2710	252	2	error	error	NOUN
iajs-2710	252	3	is	be	AUX
iajs-2710	252	4	only	only	ADV
iajs-2710	252	5	1.32	1.32	NUM
iajs-2710	252	6	%	%	NOUN
iajs-2710	252	7	with	with	ADP
iajs-2710	252	8	the	the	DET
iajs-2710	252	9	increasing	increase	VERB
iajs-2710	252	10	the	the	DET
iajs-2710	252	11	number	number	NOUN
iajs-2710	252	12	of	of	ADP
iajs-2710	252	13	training	training	NOUN
iajs-2710	252	14	samples	sample	NOUN
iajs-2710	252	15	,	,	PUNCT
iajs-2710	252	16	but	but	CCONJ
iajs-2710	252	17	the	the	DET
iajs-2710	252	18	most	most	ADV
iajs-2710	252	19	significant	significant	ADJ
iajs-2710	252	20	impact	impact	NOUN
iajs-2710	252	21	in	in	ADP
iajs-2710	252	22	reducing	reduce	VERB
iajs-2710	252	23	the	the	DET
iajs-2710	252	24	error	error	NOUN
iajs-2710	252	25	can	can	AUX
iajs-2710	252	26	be	be	AUX
iajs-2710	252	27	made	make	VERB
iajs-2710	252	28	by	by	ADP
iajs-2710	252	29	increasing	increase	VERB
iajs-2710	252	30	the	the	DET
iajs-2710	252	31	number	number	NOUN
iajs-2710	252	32	of	of	ADP
iajs-2710	252	33	samples	sample	NOUN
iajs-2710	252	34	.	.	PUNCT
iajs-2710	253	1	references	reference	NOUN
iajs-2710	253	2	1	1	NUM
iajs-2710	253	3	.	.	PUNCT
iajs-2710	253	4	yan	yan	PROPN
iajs-2710	253	5	,	,	PUNCT
iajs-2710	253	6	j.	j.	PROPN
iajs-2710	253	7	;	;	PUNCT
iajs-2710	253	8	lim	lim	PROPN
iajs-2710	253	9	,	,	PUNCT
iajs-2710	253	10	j.	j.	PROPN
iajs-2710	253	11	c.-s	c.-s	PROPN
iajs-2710	253	12	.	.	PUNCT
iajs-2710	253	13	;	;	PUNCT
iajs-2710	253	14	townsend	townsend	PROPN
iajs-2710	253	15	,	,	PUNCT
iajs-2710	253	16	d.	d.	PROPN
iajs-2710	253	17	w.	w.	PROPN
iajs-2710	253	18	mri	mri	PROPN
iajs-2710	253	19	-	-	PUNCT
iajs-2710	253	20	guided	guide	VERB
iajs-2710	253	21	brain	brain	NOUN
iajs-2710	253	22	pet	pet	NOUN
iajs-2710	253	23	image	image	NOUN
iajs-2710	253	24	filtering	filtering	NOUN
iajs-2710	253	25	and	and	CCONJ
iajs-2710	253	26	partial	partial	ADJ
iajs-2710	253	27	volume	volume	NOUN
iajs-2710	253	28	correction	correction	NOUN
iajs-2710	253	29	,	,	PUNCT
iajs-2710	253	30	physics	physics	NOUN
iajs-2710	253	31	in	in	ADP
iajs-2710	253	32	medicine	medicine	NOUN
iajs-2710	253	33	and	and	CCONJ
iajs-2710	253	34	biology	biology	NOUN
iajs-2710	253	35	,	,	PUNCT
iajs-2710	253	36	2015	2015	NUM
iajs-2710	253	37	,	,	PUNCT
iajs-2710	253	38	60	60	NUM
iajs-2710	253	39	,	,	PUNCT
iajs-2710	253	40	3	3	NUM
iajs-2710	253	41	,	,	PUNCT
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iajs-2710	253	43	,	,	PUNCT
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iajs-2710	253	45	.	.	X
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iajs-2710	253	47	,	,	PUNCT
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iajs-2710	253	51	,	,	PUNCT
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iajs-2710	253	59	:	:	PUNCT
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iajs-2710	253	61	networks	network	NOUN
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iajs-2710	253	64	image	image	NOUN
iajs-2710	253	65	segmentation	segmentation	NOUN
iajs-2710	253	66	,	,	PUNCT
iajs-2710	253	67	in	in	ADP
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iajs-2710	253	70	on	on	ADP
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iajs-2710	253	72	image	image	NOUN
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iajs-2710	253	74	and	and	CCONJ
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iajs-2710	253	76	-	-	PUNCT
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iajs-2710	253	79	.	.	PUNCT
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iajs-2710	254	4	,	,	PUNCT
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iajs-2710	255	1	3	3	X
iajs-2710	255	2	.	.	X
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iajs-2710	256	3	-	-	PUNCT
iajs-2710	256	4	cnn	cnn	NOUN
iajs-2710	256	5	:	:	PUNCT
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iajs-2710	256	8	-	-	PUNCT
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iajs-2710	256	19	in	in	ADP
iajs-2710	256	20	neural	neural	ADJ
iajs-2710	256	21	information	information	NOUN
iajs-2710	256	22	processing	process	VERB
iajs-2710	256	23	ibn	ibn	PROPN
iajs-2710	256	24	al	al	PROPN
iajs-2710	256	25	-	-	PUNCT
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iajs-2710	257	1	for	for	ADP
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iajs-2710	257	5	.	.	PUNCT
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iajs-2710	260	2	.	.	NOUN
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iajs-2710	261	2	.	.	X
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iajs-2710	261	12	k.	k.	PROPN
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iajs-2710	262	13	networks	network	NOUN
iajs-2710	262	14	,	,	PUNCT
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iajs-2710	262	29	2	2	NUM
iajs-2710	262	30	,	,	PUNCT
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iajs-2710	262	32	.	.	PUNCT
iajs-2710	263	1	5	5	NUM
iajs-2710	263	2	.	.	X
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iajs-2710	263	27	(	(	PUNCT
iajs-2710	263	28	isbi	isbi	NOUN
iajs-2710	263	29	)	)	PUNCT
iajs-2710	263	30	,	,	PUNCT
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iajs-2710	264	1	ieee	ieee	PROPN
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iajs-2710	264	4	,	,	PUNCT
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iajs-2710	265	2	.	.	X
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iajs-2710	265	10	;	;	PUNCT
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iajs-2710	265	13	j.	j.	PROPN
iajs-2710	265	14	c.	c.	PROPN
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iajs-2710	265	18	neural	neural	ADJ
iajs-2710	265	19	network	network	NOUN
iajs-2710	265	20	using	use	VERB
iajs-2710	265	21	directional	directional	ADJ
iajs-2710	265	22	wavelets	wavelet	NOUN
iajs-2710	265	23	for	for	ADP
iajs-2710	265	24	low	low	ADV
iajs-2710	265	25	-	-	PUNCT
iajs-2710	265	26	dose	dose	NOUN
iajs-2710	265	27	x	x	NOUN
iajs-2710	265	28	-	-	NOUN
iajs-2710	265	29	ray	ray	NOUN
iajs-2710	265	30	ct	ct	PROPN
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iajs-2710	265	32	,	,	PUNCT
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iajs-2710	265	36	,	,	PUNCT
iajs-2710	265	37	2016	2016	NUM
iajs-2710	265	38	.	.	PUNCT
iajs-2710	266	1	7	7	X
iajs-2710	266	2	.	.	X
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iajs-2710	266	5	j.	j.	PROPN
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iajs-2710	266	9	,	,	PUNCT
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iajs-2710	266	11	;	;	PUNCT
iajs-2710	267	1	viergever	viergever	ADJ
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iajs-2710	267	13	in	in	ADP
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iajs-2710	267	20	transactions	transaction	NOUN
iajs-2710	267	21	on	on	ADP
iajs-2710	267	22	medical	medical	ADJ
iajs-2710	267	23	imaging	imaging	NOUN
iajs-2710	267	24	,	,	PUNCT
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iajs-2710	268	1	johnson	johnson	PROPN
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iajs-2710	268	7	a.	a.	NOUN
iajs-2710	268	8	;	;	PUNCT
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iajs-2710	268	18	style	style	NOUN
iajs-2710	268	19	transfer	transfer	NOUN
iajs-2710	268	20	and	and	CCONJ
iajs-2710	268	21	super	super	NOUN
iajs-2710	268	22	-	-	NOUN
iajs-2710	268	23	resolution	resolution	NOUN
iajs-2710	268	24	,	,	PUNCT
iajs-2710	268	25	in	in	ADP
iajs-2710	268	26	european	european	ADJ
iajs-2710	268	27	conference	conference	NOUN
iajs-2710	268	28	on	on	ADP
iajs-2710	268	29	computer	computer	NOUN
iajs-2710	268	30	vision	vision	NOUN
iajs-2710	268	31	.	.	PUNCT
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iajs-2710	269	2	,	,	PUNCT
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iajs-2710	270	1	9	9	NUM
iajs-2710	270	2	.	.	X
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iajs-2710	270	5	c.	c.	PROPN
iajs-2710	270	6	;	;	PUNCT
iajs-2710	270	7	theis	theis	PROPN
iajs-2710	270	8	,	,	PUNCT
iajs-2710	270	9	l.	l.	PROPN
iajs-2710	270	10	;	;	PUNCT
iajs-2710	270	11	huszar	huszar	PROPN
iajs-2710	270	12	,	,	PUNCT
iajs-2710	270	13	f.	f.	PROPN
iajs-2710	270	14	et	et	PROPN
iajs-2710	270	15	al	al	PROPN
iajs-2710	270	16	.	.	PROPN
iajs-2710	270	17	,	,	PUNCT
iajs-2710	270	18	photo	photo	NOUN
iajs-2710	270	19	-	-	PUNCT
iajs-2710	270	20	realistic	realistic	ADJ
iajs-2710	270	21	single	single	ADJ
iajs-2710	270	22	image	image	NOUN
iajs-2710	270	23	superresolution	superresolution	NOUN
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iajs-2710	270	25	a	a	DET
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iajs-2710	270	27	adversarial	adversarial	ADJ
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iajs-2710	270	29	,	,	PUNCT
iajs-2710	270	30	arxiv	arxiv	PROPN
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iajs-2710	270	32	,	,	PUNCT
iajs-2710	270	33	2016	2016	NUM
iajs-2710	270	34	.	.	PUNCT
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iajs-2710	271	2	.	.	X
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iajs-2710	272	2	,	,	PUNCT
iajs-2710	272	3	q.	q.	PROPN
iajs-2710	272	4	;	;	PUNCT
iajs-2710	272	5	yan	yan	PROPN
iajs-2710	272	6	,	,	PUNCT
iajs-2710	272	7	p.	p.	NOUN
iajs-2710	272	8	;	;	PUNCT
iajs-2710	272	9	kalra	kalra	NOUN
iajs-2710	272	10	,	,	PUNCT
iajs-2710	272	11	m.	m.	PROPN
iajs-2710	272	12	k.	k.	PROPN
iajs-2710	272	13	et	et	PROPN
iajs-2710	273	1	al	al	PROPN
iajs-2710	273	2	.	.	PROPN
iajs-2710	273	3	,	,	PUNCT
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iajs-2710	273	7	with	with	ADP
iajs-2710	273	8	perceptive	perceptive	ADJ
iajs-2710	273	9	deep	deep	ADJ
iajs-2710	273	10	neural	neural	ADJ
iajs-2710	273	11	networks	network	NOUN
iajs-2710	273	12	,	,	PUNCT
iajs-2710	273	13	”	"	PUNCT
iajs-2710	273	14	arxiv	arxiv	PROPN
iajs-2710	273	15	preprint	preprint	NOUN
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iajs-2710	273	17	,	,	PUNCT
iajs-2710	273	18	2017	2017	NUM
iajs-2710	273	19	.	.	PUNCT
iajs-2710	274	1	11	11	NUM
iajs-2710	274	2	.	.	X
iajs-2710	275	1	han	han	PROPN
iajs-2710	275	2	,	,	PUNCT
iajs-2710	275	3	y.	y.	PROPN
iajs-2710	275	4	s.	s.	PROPN
iajs-2710	275	5	;	;	PUNCT
iajs-2710	275	6	yoo	yoo	PROPN
iajs-2710	275	7	,	,	PUNCT
iajs-2710	275	8	j.	j.	PROPN
iajs-2710	275	9	;	;	PUNCT
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iajs-2710	275	11	,	,	PUNCT
iajs-2710	275	12	j.	j.	PROPN
iajs-2710	275	13	c.	c.	PROPN
iajs-2710	275	14	deep	deep	PROPN
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iajs-2710	275	16	with	with	ADP
iajs-2710	275	17	domain	domain	NOUN
iajs-2710	275	18	adaptation	adaptation	NOUN
iajs-2710	275	19	for	for	ADP
iajs-2710	275	20	accelerated	accelerate	VERB
iajs-2710	275	21	projection	projection	NOUN
iajs-2710	275	22	reconstruction	reconstruction	NOUN
iajs-2710	275	23	mr	mr	PROPN
iajs-2710	275	24	,	,	PUNCT
iajs-2710	275	25	arxiv	arxiv	PROPN
iajs-2710	275	26	preprint	preprint	VERB
iajs-2710	275	27	arxiv:1703.01135	arxiv:1703.01135	NOUN
iajs-2710	275	28	,	,	PUNCT
iajs-2710	275	29	2017	2017	NUM
iajs-2710	275	30	.	.	PUNCT
iajs-2710	276	1	12	12	NUM
iajs-2710	276	2	.	.	PUNCT
iajs-2710	277	1	oktay	oktay	PROPN
iajs-2710	277	2	,	,	PUNCT
iajs-2710	277	3	o.	o.	PROPN
iajs-2710	277	4	;	;	PUNCT
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iajs-2710	277	6	,	,	PUNCT
iajs-2710	277	7	e.	e.	PROPN
iajs-2710	277	8	;	;	PUNCT
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iajs-2710	277	10	,	,	PUNCT
iajs-2710	277	11	k.	k.	PROPN
iajs-2710	277	12	et	et	PROPN
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iajs-2710	278	2	.	.	PROPN
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iajs-2710	278	4	constrained	constrain	VERB
iajs-2710	278	5	neural	neural	ADJ
iajs-2710	278	6	networks	network	NOUN
iajs-2710	278	7	(	(	PUNCT
iajs-2710	278	8	acnn	acnn	NOUN
iajs-2710	278	9	):	):	PUNCT
iajs-2710	278	10	application	application	NOUN
iajs-2710	278	11	to	to	ADP
iajs-2710	278	12	cardiac	cardiac	ADJ
iajs-2710	278	13	image	image	NOUN
iajs-2710	278	14	enhancement	enhancement	NOUN
iajs-2710	278	15	and	and	CCONJ
iajs-2710	278	16	segmentation	segmentation	NOUN
iajs-2710	278	17	,	,	PUNCT
iajs-2710	278	18	ieee	ieee	NOUN
iajs-2710	278	19	transactions	transaction	NOUN
iajs-2710	278	20	on	on	ADP
iajs-2710	278	21	medical	medical	ADJ
iajs-2710	278	22	imaging	imaging	NOUN
iajs-2710	278	23	,	,	PUNCT
iajs-2710	278	24	2017	2017	NUM
iajs-2710	278	25	.	.	PUNCT