id	sid	tid	token	lemma	pos
fcis-15107	1	1	frontiers	frontier	NOUN
fcis-15107	1	2	in	in	ADP
fcis-15107	1	3	computing	computing	NOUN
fcis-15107	1	4	and	and	CCONJ
fcis-15107	1	5	intelligent	intelligent	ADJ
fcis-15107	1	6	systems	system	NOUN
fcis-15107	1	7	issn	issn	VERB
fcis-15107	1	8	:	:	PUNCT
fcis-15107	1	9	2832	2832	NUM
fcis-15107	1	10	-	-	SYM
fcis-15107	1	11	6024	6024	NUM
fcis-15107	1	12	|	|	NOUN
fcis-15107	1	13	vol	vol	NOUN
fcis-15107	1	14	.	.	PROPN
fcis-15107	2	1	6	6	NUM
fcis-15107	2	2	,	,	PUNCT
fcis-15107	2	3	no	no	INTJ
fcis-15107	2	4	.	.	NOUN
fcis-15107	2	5	2	2	NUM
fcis-15107	2	6	,	,	PUNCT
fcis-15107	2	7	2023	2023	NUM
fcis-15107	2	8	30	30	NUM
fcis-15107	2	9	sc‐unext	sc‐unext	NOUN
fcis-15107	2	10	:	:	PUNCT
fcis-15107	2	11	nested	nest	VERB
fcis-15107	2	12	unext	unext	ADJ
fcis-15107	2	13	architecture	architecture	NOUN
fcis-15107	2	14	based	base	VERB
fcis-15107	2	15	on	on	ADP
fcis-15107	2	16	medical	medical	ADJ
fcis-15107	2	17	image	image	NOUN
fcis-15107	2	18	segmentation	segmentation	NOUN
fcis-15107	2	19	lei	lei	PROPN
fcis-15107	2	20	wen	wen	PROPN
fcis-15107	2	21	southwest	southwest	PROPN
fcis-15107	2	22	minzu	minzu	PROPN
fcis-15107	2	23	university	university	PROPN
fcis-15107	2	24	,	,	PUNCT
fcis-15107	2	25	chengdu	chengdu	PROPN
fcis-15107	2	26	,	,	PUNCT
fcis-15107	2	27	china	china	PROPN
fcis-15107	2	28	abstract	abstract	NOUN
fcis-15107	2	29	:	:	PUNCT
fcis-15107	2	30	unet	unet	NOUN
fcis-15107	2	31	and	and	CCONJ
fcis-15107	2	32	its	its	PRON
fcis-15107	2	33	various	various	ADJ
fcis-15107	2	34	variants	variant	NOUN
fcis-15107	2	35	are	be	AUX
fcis-15107	2	36	commonly	commonly	ADV
fcis-15107	2	37	used	use	VERB
fcis-15107	2	38	methods	method	NOUN
fcis-15107	2	39	in	in	ADP
fcis-15107	2	40	medical	medical	ADJ
fcis-15107	2	41	image	image	NOUN
fcis-15107	2	42	segmentation	segmentation	NOUN
fcis-15107	2	43	tasks	task	NOUN
fcis-15107	2	44	;	;	PUNCT
fcis-15107	2	45	however	however	ADV
fcis-15107	2	46	,	,	PUNCT
fcis-15107	2	47	many	many	ADJ
fcis-15107	2	48	network	network	NOUN
fcis-15107	2	49	parameters	parameter	NOUN
fcis-15107	2	50	,	,	PUNCT
fcis-15107	2	51	complex	complex	ADJ
fcis-15107	2	52	calculations	calculation	NOUN
fcis-15107	2	53	,	,	PUNCT
fcis-15107	2	54	and	and	CCONJ
fcis-15107	2	55	slow	slow	ADJ
fcis-15107	2	56	usage	usage	NOUN
fcis-15107	2	57	are	be	AUX
fcis-15107	2	58	problems	problem	NOUN
fcis-15107	2	59	that	that	PRON
fcis-15107	2	60	need	need	VERB
fcis-15107	2	61	to	to	PART
fcis-15107	2	62	be	be	AUX
fcis-15107	2	63	overcome	overcome	VERB
fcis-15107	2	64	.	.	PUNCT
fcis-15107	3	1	these	these	DET
fcis-15107	3	2	problems	problem	NOUN
fcis-15107	3	3	hinder	hinder	VERB
fcis-15107	3	4	the	the	DET
fcis-15107	3	5	specific	specific	ADJ
fcis-15107	3	6	application	application	NOUN
fcis-15107	3	7	of	of	ADP
fcis-15107	3	8	fast	fast	ADJ
fcis-15107	3	9	image	image	NOUN
fcis-15107	3	10	segmentation	segmentation	NOUN
fcis-15107	3	11	in	in	ADP
fcis-15107	3	12	real	real	ADJ
fcis-15107	3	13	-	-	PUNCT
fcis-15107	3	14	time	time	NOUN
fcis-15107	3	15	tasks	task	NOUN
fcis-15107	3	16	.	.	PUNCT
fcis-15107	4	1	at	at	ADP
fcis-15107	4	2	the	the	DET
fcis-15107	4	3	same	same	ADJ
fcis-15107	4	4	time	time	NOUN
fcis-15107	4	5	,	,	PUNCT
fcis-15107	4	6	the	the	DET
fcis-15107	4	7	lesion	lesion	NOUN
fcis-15107	4	8	area	area	NOUN
fcis-15107	4	9	has	have	VERB
fcis-15107	4	10	problems	problem	NOUN
fcis-15107	4	11	such	such	ADJ
fcis-15107	4	12	as	as	ADP
fcis-15107	4	13	small	small	ADJ
fcis-15107	4	14	size	size	NOUN
fcis-15107	4	15	,	,	PUNCT
fcis-15107	4	16	irregular	irregular	ADJ
fcis-15107	4	17	shape	shape	NOUN
fcis-15107	4	18	,	,	PUNCT
fcis-15107	4	19	and	and	CCONJ
fcis-15107	4	20	blurred	blurred	ADJ
fcis-15107	4	21	edges	edge	NOUN
fcis-15107	4	22	,	,	PUNCT
fcis-15107	4	23	which	which	PRON
fcis-15107	4	24	makes	make	VERB
fcis-15107	4	25	the	the	DET
fcis-15107	4	26	network	network	NOUN
fcis-15107	4	27	feature	feature	NOUN
fcis-15107	4	28	extraction	extraction	NOUN
fcis-15107	4	29	difficult	difficult	ADJ
fcis-15107	4	30	and	and	CCONJ
fcis-15107	4	31	the	the	DET
fcis-15107	4	32	segmentation	segmentation	NOUN
fcis-15107	4	33	accuracy	accuracy	NOUN
fcis-15107	4	34	needs	need	VERB
fcis-15107	4	35	to	to	PART
fcis-15107	4	36	be	be	AUX
fcis-15107	4	37	improved	improve	VERB
fcis-15107	4	38	.	.	PUNCT
fcis-15107	5	1	at	at	ADP
fcis-15107	5	2	the	the	DET
fcis-15107	5	3	same	same	ADJ
fcis-15107	5	4	time	time	NOUN
fcis-15107	5	5	,	,	PUNCT
fcis-15107	5	6	medical	medical	ADJ
fcis-15107	5	7	image	image	NOUN
fcis-15107	5	8	segmentation	segmentation	NOUN
fcis-15107	5	9	provides	provide	VERB
fcis-15107	5	10	a	a	DET
fcis-15107	5	11	variety	variety	NOUN
fcis-15107	5	12	of	of	ADP
fcis-15107	5	13	effective	effective	ADJ
fcis-15107	5	14	methods	method	NOUN
fcis-15107	5	15	for	for	ADP
fcis-15107	5	16	the	the	DET
fcis-15107	5	17	accuracy	accuracy	NOUN
fcis-15107	5	18	and	and	CCONJ
fcis-15107	5	19	robustness	robustness	NOUN
fcis-15107	5	20	of	of	ADP
fcis-15107	5	21	organ	organ	NOUN
fcis-15107	5	22	segmentation	segmentation	NOUN
fcis-15107	5	23	,	,	PUNCT
fcis-15107	5	24	lesion	lesion	NOUN
fcis-15107	5	25	detection	detection	NOUN
fcis-15107	5	26	,	,	PUNCT
fcis-15107	5	27	and	and	CCONJ
fcis-15107	5	28	classification	classification	NOUN
fcis-15107	5	29	.	.	PUNCT
fcis-15107	6	1	medical	medical	ADJ
fcis-15107	6	2	images	image	NOUN
fcis-15107	6	3	have	have	VERB
fcis-15107	6	4	fixed	fix	VERB
fcis-15107	6	5	structures	structure	NOUN
fcis-15107	6	6	,	,	PUNCT
fcis-15107	6	7	simple	simple	ADJ
fcis-15107	6	8	semantics	semantic	NOUN
fcis-15107	6	9	,	,	PUNCT
fcis-15107	6	10	and	and	CCONJ
fcis-15107	6	11	diverse	diverse	ADJ
fcis-15107	6	12	details	detail	NOUN
fcis-15107	6	13	,	,	PUNCT
fcis-15107	6	14	so	so	ADV
fcis-15107	6	15	integrating	integrate	VERB
fcis-15107	6	16	rich	rich	ADJ
fcis-15107	6	17	multi	multi	ADJ
fcis-15107	6	18	-	-	ADJ
fcis-15107	6	19	scale	scale	ADJ
fcis-15107	6	20	features	feature	NOUN
fcis-15107	6	21	can	can	AUX
fcis-15107	6	22	improve	improve	VERB
fcis-15107	6	23	segmentation	segmentation	NOUN
fcis-15107	6	24	accuracy	accuracy	NOUN
fcis-15107	6	25	.	.	PUNCT
fcis-15107	7	1	given	give	VERB
fcis-15107	7	2	that	that	SCONJ
fcis-15107	7	3	the	the	DET
fcis-15107	7	4	density	density	NOUN
fcis-15107	7	5	of	of	ADP
fcis-15107	7	6	diseased	diseased	ADJ
fcis-15107	7	7	tissue	tissue	NOUN
fcis-15107	7	8	may	may	AUX
fcis-15107	7	9	be	be	AUX
fcis-15107	7	10	comparable	comparable	ADJ
fcis-15107	7	11	to	to	ADP
fcis-15107	7	12	that	that	PRON
fcis-15107	7	13	of	of	ADP
fcis-15107	7	14	surrounding	surround	VERB
fcis-15107	7	15	normal	normal	ADJ
fcis-15107	7	16	tissue	tissue	NOUN
fcis-15107	7	17	,	,	PUNCT
fcis-15107	7	18	both	both	CCONJ
fcis-15107	7	19	global	global	ADJ
fcis-15107	7	20	and	and	CCONJ
fcis-15107	7	21	local	local	ADJ
fcis-15107	7	22	information	information	NOUN
fcis-15107	7	23	are	be	AUX
fcis-15107	7	24	crucial	crucial	ADJ
fcis-15107	7	25	to	to	ADP
fcis-15107	7	26	segmentation	segmentation	NOUN
fcis-15107	7	27	results	result	NOUN
fcis-15107	7	28	.	.	PUNCT
fcis-15107	8	1	to	to	ADP
fcis-15107	8	2	this	this	DET
fcis-15107	8	3	end	end	NOUN
fcis-15107	8	4	,	,	PUNCT
fcis-15107	8	5	we	we	PRON
fcis-15107	8	6	propose	propose	VERB
fcis-15107	8	7	an	an	DET
fcis-15107	8	8	image	image	NOUN
fcis-15107	8	9	segmentation	segmentation	NOUN
fcis-15107	8	10	method	method	NOUN
fcis-15107	8	11	(	(	PUNCT
fcis-15107	8	12	sc	sc	PROPN
fcis-15107	8	13	-une	-une	PUNCT
fcis-15107	8	14	x	x	SYM
fcis-15107	8	15	t	t	PROPN
fcis-15107	8	16	)	)	PUNCT
fcis-15107	8	17	based	base	VERB
fcis-15107	8	18	on	on	ADP
fcis-15107	8	19	edge	edge	NOUN
fcis-15107	8	20	feature	feature	NOUN
fcis-15107	8	21	extraction	extraction	NOUN
fcis-15107	8	22	and	and	CCONJ
fcis-15107	8	23	multi	multi	ADJ
fcis-15107	8	24	-	-	ADJ
fcis-15107	8	25	scale	scale	ADJ
fcis-15107	8	26	feature	feature	NOUN
fcis-15107	8	27	fusion	fusion	NOUN
fcis-15107	8	28	of	of	ADP
fcis-15107	8	29	convolutional	convolutional	ADJ
fcis-15107	8	30	multi	multi	ADJ
fcis-15107	8	31	-	-	ADJ
fcis-15107	8	32	layer	layer	ADJ
fcis-15107	8	33	perceptron	perceptron	NOUN
fcis-15107	8	34	(	(	PUNCT
fcis-15107	8	35	mlp	mlp	PROPN
fcis-15107	8	36	)	)	PUNCT
fcis-15107	8	37	.	.	PUNCT
fcis-15107	9	1	the	the	DET
fcis-15107	9	2	network	network	NOUN
fcis-15107	9	3	is	be	AUX
fcis-15107	9	4	a	a	DET
fcis-15107	9	5	deeply	deeply	ADV
fcis-15107	9	6	supervised	supervised	ADJ
fcis-15107	9	7	encoderdecoder	encoderdecoder	NOUN
fcis-15107	9	8	network	network	NOUN
fcis-15107	9	9	,	,	PUNCT
fcis-15107	9	10	in	in	ADP
fcis-15107	9	11	which	which	PRON
fcis-15107	9	12	the	the	DET
fcis-15107	9	13	encoder	encoder	NOUN
fcis-15107	9	14	and	and	CCONJ
fcis-15107	9	15	decoder	decoder	NOUN
fcis-15107	9	16	pass	pass	VERB
fcis-15107	9	17	through	through	ADP
fcis-15107	9	18	a	a	DET
fcis-15107	9	19	series	series	NOUN
fcis-15107	9	20	of	of	ADP
fcis-15107	9	21	nested	nested	ADJ
fcis-15107	9	22	,	,	PUNCT
fcis-15107	9	23	multiple	multiple	ADJ
fcis-15107	9	24	jump	jump	NOUN
fcis-15107	9	25	paths	path	NOUN
fcis-15107	9	26	to	to	PART
fcis-15107	9	27	reduce	reduce	VERB
fcis-15107	9	28	the	the	DET
fcis-15107	9	29	semantic	semantic	ADJ
fcis-15107	9	30	gap	gap	NOUN
fcis-15107	9	31	between	between	ADP
fcis-15107	9	32	the	the	DET
fcis-15107	9	33	feature	feature	NOUN
fcis-15107	9	34	maps	map	NOUN
fcis-15107	9	35	of	of	ADP
fcis-15107	9	36	the	the	DET
fcis-15107	9	37	encoder	encoder	NOUN
fcis-15107	9	38	and	and	CCONJ
fcis-15107	9	39	decoder	decoder	NOUN
fcis-15107	9	40	sub	sub	NOUN
fcis-15107	9	41	-	-	NOUN
fcis-15107	9	42	networks	network	NOUN
fcis-15107	9	43	.	.	PUNCT
fcis-15107	10	1	;	;	PUNCT
fcis-15107	10	2	multi	multi	ADJ
fcis-15107	10	3	scale	scale	NOUN
fcis-15107	10	4	feature	feature	NOUN
fcis-15107	10	5	fusion	fusion	NOUN
fcis-15107	10	6	is	be	AUX
fcis-15107	10	7	introduced	introduce	VERB
fcis-15107	10	8	based	base	VERB
fcis-15107	10	9	on	on	ADP
fcis-15107	10	10	the	the	DET
fcis-15107	10	11	une	une	PROPN
fcis-15107	10	12	finally	finally	ADV
fcis-15107	10	13	,	,	PUNCT
fcis-15107	10	14	we	we	PRON
fcis-15107	10	15	evaluate	evaluate	VERB
fcis-15107	10	16	our	our	PRON
fcis-15107	10	17	model	model	NOUN
fcis-15107	10	18	approach	approach	NOUN
fcis-15107	10	19	on	on	ADP
fcis-15107	10	20	the	the	DET
fcis-15107	10	21	lidc	lidc	ADJ
fcis-15107	10	22	dataset	dataset	VERB
fcis-15107	10	23	public	public	ADJ
fcis-15107	10	24	dataset	dataset	NOUN
fcis-15107	10	25	.	.	PUNCT
fcis-15107	11	1	experiments	experiment	NOUN
fcis-15107	11	2	have	have	AUX
fcis-15107	11	3	proven	prove	VERB
fcis-15107	11	4	the	the	DET
fcis-15107	11	5	effectiveness	effectiveness	NOUN
fcis-15107	11	6	of	of	ADP
fcis-15107	11	7	this	this	DET
fcis-15107	11	8	method	method	NOUN
fcis-15107	11	9	.	.	PUNCT
fcis-15107	12	1	our	our	PRON
fcis-15107	12	2	model	model	NOUN
fcis-15107	12	3	's	's	PART
fcis-15107	12	4	similarity	similarity	NOUN
fcis-15107	12	5	coefficient	coefficient	NOUN
fcis-15107	12	6	and	and	CCONJ
fcis-15107	12	7	intersection	intersection	NOUN
fcis-15107	12	8	ratio	ratio	NOUN
fcis-15107	12	9	reached	reach	VERB
fcis-15107	12	10	86.44	86.44	NUM
fcis-15107	12	11	%	%	NOUN
fcis-15107	12	12	and	and	CCONJ
fcis-15107	12	13	90.86	90.86	NUM
fcis-15107	12	14	%	%	NOUN
fcis-15107	12	15	respectively	respectively	ADV
fcis-15107	12	16	.	.	PUNCT
fcis-15107	13	1	compared	compare	VERB
fcis-15107	13	2	with	with	ADP
fcis-15107	13	3	unet	unet	NOUN
fcis-15107	13	4	and	and	CCONJ
fcis-15107	13	5	une	une	PROPN
fcis-15107	13	6	x	x	SYM
fcis-15107	13	7	t	t	PROPN
fcis-15107	13	8	,	,	PUNCT
fcis-15107	13	9	the	the	DET
fcis-15107	13	10	network	network	NOUN
fcis-15107	13	11	proposed	propose	VERB
fcis-15107	13	12	in	in	ADP
fcis-15107	13	13	this	this	DET
fcis-15107	13	14	article	article	NOUN
fcis-15107	13	15	has	have	AUX
fcis-15107	13	16	improved	improve	VERB
fcis-15107	13	17	in	in	ADP
fcis-15107	13	18	accuracy	accuracy	NOUN
fcis-15107	13	19	,	,	PUNCT
fcis-15107	13	20	intersection	intersection	NOUN
fcis-15107	13	21	ratio	ratio	NOUN
fcis-15107	13	22	of	of	ADP
fcis-15107	13	23	real	real	ADJ
fcis-15107	13	24	values	value	NOUN
fcis-15107	13	25	and	and	CCONJ
fcis-15107	13	26	predicted	predict	VERB
fcis-15107	13	27	values	value	NOUN
fcis-15107	13	28	,	,	PUNCT
fcis-15107	13	29	similarity	similarity	NOUN
fcis-15107	13	30	coefficient	coefficient	NOUN
fcis-15107	13	31	,	,	PUNCT
fcis-15107	13	32	and	and	CCONJ
fcis-15107	13	33	segmentation	segmentation	NOUN
fcis-15107	13	34	effect	effect	NOUN
fcis-15107	13	35	.	.	PUNCT
fcis-15107	14	1	keywords	keyword	NOUN
fcis-15107	14	2	:	:	PUNCT
fcis-15107	14	3	lightweight	lightweight	ADJ
fcis-15107	14	4	;	;	PUNCT
fcis-15107	14	5	edge	edge	NOUN
fcis-15107	14	6	feature	feature	NOUN
fcis-15107	14	7	fusion	fusion	NOUN
fcis-15107	14	8	;	;	PUNCT
fcis-15107	14	9	multi	multi	ADJ
fcis-15107	14	10	-	-	ADJ
fcis-15107	14	11	branch	branch	ADJ
fcis-15107	14	12	feature	feature	NOUN
fcis-15107	14	13	fusion	fusion	NOUN
fcis-15107	14	14	;	;	PUNCT
fcis-15107	14	15	medical	medical	ADJ
fcis-15107	14	16	image	image	NOUN
fcis-15107	14	17	segmentation	segmentation	NOUN
fcis-15107	14	18	.	.	PUNCT
fcis-15107	15	1	1	1	X
fcis-15107	15	2	.	.	X
fcis-15107	15	3	introduction	introduction	NOUN
fcis-15107	15	4	skin	skin	NOUN
fcis-15107	15	5	diseases	disease	NOUN
fcis-15107	15	6	often	often	ADV
fcis-15107	15	7	occur	occur	VERB
fcis-15107	15	8	in	in	ADP
fcis-15107	15	9	daily	daily	ADJ
fcis-15107	15	10	life	life	NOUN
fcis-15107	15	11	and	and	CCONJ
fcis-15107	15	12	cause	cause	VERB
fcis-15107	15	13	great	great	ADJ
fcis-15107	15	14	trouble	trouble	NOUN
fcis-15107	15	15	to	to	ADP
fcis-15107	15	16	patients	patient	NOUN
fcis-15107	15	17	.	.	PUNCT
fcis-15107	16	1	doctors	doctor	NOUN
fcis-15107	16	2	need	need	VERB
fcis-15107	16	3	to	to	PART
fcis-15107	16	4	diagnose	diagnose	VERB
fcis-15107	16	5	the	the	DET
fcis-15107	16	6	diseased	diseased	ADJ
fcis-15107	16	7	areas	area	NOUN
fcis-15107	16	8	during	during	ADP
fcis-15107	16	9	their	their	PRON
fcis-15107	16	10	work	work	NOUN
fcis-15107	16	11	to	to	PART
fcis-15107	16	12	help	help	VERB
fcis-15107	16	13	patients	patient	NOUN
fcis-15107	16	14	recover	recover	VERB
fcis-15107	16	15	as	as	ADV
fcis-15107	16	16	soon	soon	ADV
fcis-15107	16	17	as	as	ADP
fcis-15107	16	18	possible	possible	ADJ
fcis-15107	16	19	.	.	PUNCT
fcis-15107	17	1	at	at	ADP
fcis-15107	17	2	the	the	DET
fcis-15107	17	3	same	same	ADJ
fcis-15107	17	4	time	time	NOUN
fcis-15107	17	5	,	,	PUNCT
fcis-15107	17	6	lung	lung	NOUN
fcis-15107	17	7	inflammation	inflammation	NOUN
fcis-15107	17	8	is	be	AUX
fcis-15107	17	9	a	a	DET
fcis-15107	17	10	serious	serious	ADJ
fcis-15107	17	11	disease	disease	NOUN
fcis-15107	17	12	that	that	PRON
fcis-15107	17	13	may	may	AUX
fcis-15107	17	14	be	be	AUX
fcis-15107	17	15	caused	cause	VERB
fcis-15107	17	16	by	by	ADP
fcis-15107	17	17	long	long	ADJ
fcis-15107	17	18	-	-	PUNCT
fcis-15107	17	19	term	term	NOUN
fcis-15107	17	20	living	living	NOUN
fcis-15107	17	21	habits	habit	NOUN
fcis-15107	17	22	and	and	CCONJ
fcis-15107	17	23	genetic	genetic	ADJ
fcis-15107	17	24	mutations	mutation	NOUN
fcis-15107	17	25	.	.	PUNCT
fcis-15107	18	1	lung	lung	NOUN
fcis-15107	18	2	lesions	lesion	NOUN
fcis-15107	18	3	initially	initially	ADV
fcis-15107	18	4	manifest	manifest	VERB
fcis-15107	18	5	as	as	ADP
fcis-15107	18	6	inflammation	inflammation	NOUN
fcis-15107	18	7	,	,	PUNCT
fcis-15107	18	8	but	but	CCONJ
fcis-15107	18	9	over	over	ADP
fcis-15107	18	10	time	time	NOUN
fcis-15107	18	11	,	,	PUNCT
fcis-15107	18	12	the	the	DET
fcis-15107	18	13	accumulation	accumulation	NOUN
fcis-15107	18	14	of	of	ADP
fcis-15107	18	15	many	many	ADJ
fcis-15107	18	16	diseases	disease	NOUN
fcis-15107	18	17	in	in	ADP
fcis-15107	18	18	the	the	DET
fcis-15107	18	19	lungs	lung	NOUN
fcis-15107	18	20	may	may	AUX
fcis-15107	18	21	manifest	manifest	VERB
fcis-15107	18	22	as	as	ADP
fcis-15107	18	23	inflammation	inflammation	NOUN
fcis-15107	18	24	,	,	PUNCT
fcis-15107	18	25	so	so	CCONJ
fcis-15107	18	26	the	the	DET
fcis-15107	18	27	initial	initial	ADJ
fcis-15107	18	28	diagnosis	diagnosis	NOUN
fcis-15107	18	29	of	of	ADP
fcis-15107	18	30	pulmonary	pulmonary	ADJ
fcis-15107	18	31	nodules	nodule	NOUN
fcis-15107	18	32	is	be	AUX
fcis-15107	18	33	very	very	ADV
fcis-15107	18	34	important	important	ADJ
fcis-15107	18	35	.	.	PUNCT
fcis-15107	19	1	when	when	SCONJ
fcis-15107	19	2	diagnosing	diagnose	VERB
fcis-15107	19	3	pulmonary	pulmonary	ADJ
fcis-15107	19	4	nodules	nodule	NOUN
fcis-15107	19	5	in	in	ADP
fcis-15107	19	6	the	the	DET
fcis-15107	19	7	early	early	ADJ
fcis-15107	19	8	stage	stage	NOUN
fcis-15107	19	9	,	,	PUNCT
fcis-15107	19	10	the	the	DET
fcis-15107	19	11	large	large	ADJ
fcis-15107	19	12	number	number	NOUN
fcis-15107	19	13	of	of	ADP
fcis-15107	19	14	patients	patient	NOUN
fcis-15107	19	15	usually	usually	ADV
fcis-15107	19	16	leads	lead	VERB
fcis-15107	19	17	to	to	ADP
fcis-15107	19	18	excessive	excessive	ADJ
fcis-15107	19	19	fatigue	fatigue	NOUN
fcis-15107	19	20	of	of	ADP
fcis-15107	19	21	doctors	doctor	NOUN
fcis-15107	19	22	.	.	PUNCT
fcis-15107	20	1	therefore	therefore	ADV
fcis-15107	20	2	,	,	PUNCT
fcis-15107	20	3	doctors	doctor	NOUN
fcis-15107	20	4	are	be	AUX
fcis-15107	20	5	required	require	VERB
fcis-15107	20	6	to	to	PART
fcis-15107	20	7	repeatedly	repeatedly	ADV
fcis-15107	20	8	check	check	VERB
fcis-15107	20	9	ct	ct	NUM
fcis-15107	20	10	images	image	NOUN
fcis-15107	20	11	to	to	PART
fcis-15107	20	12	better	well	ADV
fcis-15107	20	13	determine	determine	VERB
fcis-15107	20	14	the	the	DET
fcis-15107	20	15	area	area	NOUN
fcis-15107	20	16	of	of	ADP
fcis-15107	20	17	pulmonary	pulmonary	ADJ
fcis-15107	20	18	nodules	nodule	NOUN
fcis-15107	20	19	and	and	CCONJ
fcis-15107	20	20	ensure	ensure	VERB
fcis-15107	20	21	that	that	SCONJ
fcis-15107	20	22	the	the	DET
fcis-15107	20	23	diagnosis	diagnosis	NOUN
fcis-15107	20	24	results	result	NOUN
fcis-15107	20	25	are	be	AUX
fcis-15107	20	26	correct	correct	ADJ
fcis-15107	20	27	.	.	PUNCT
fcis-15107	21	1	in	in	ADP
fcis-15107	21	2	recent	recent	ADJ
fcis-15107	21	3	years	year	NOUN
fcis-15107	21	4	,	,	PUNCT
fcis-15107	21	5	with	with	ADP
fcis-15107	21	6	the	the	DET
fcis-15107	21	7	continuous	continuous	ADJ
fcis-15107	21	8	development	development	NOUN
fcis-15107	21	9	of	of	ADP
fcis-15107	21	10	deep	deep	ADJ
fcis-15107	21	11	learning	learning	NOUN
fcis-15107	21	12	,	,	PUNCT
fcis-15107	21	13	this	this	DET
fcis-15107	21	14	technology	technology	NOUN
fcis-15107	21	15	has	have	AUX
fcis-15107	21	16	been	be	AUX
fcis-15107	21	17	widely	widely	ADV
fcis-15107	21	18	used	use	VERB
fcis-15107	21	19	in	in	ADP
fcis-15107	21	20	clinical	clinical	ADJ
fcis-15107	21	21	diagnosis	diagnosis	NOUN
fcis-15107	21	22	to	to	PART
fcis-15107	21	23	assist	assist	VERB
fcis-15107	21	24	doctors	doctor	NOUN
fcis-15107	21	25	in	in	ADP
fcis-15107	21	26	quickly	quickly	ADV
fcis-15107	21	27	detecting	detect	VERB
fcis-15107	21	28	ct	ct	NUM
fcis-15107	21	29	images	image	NOUN
fcis-15107	21	30	and	and	CCONJ
fcis-15107	21	31	reducing	reduce	VERB
fcis-15107	21	32	misdiagnosis	misdiagnosis	NOUN
fcis-15107	21	33	rates	rate	NOUN
fcis-15107	21	34	.	.	PUNCT
fcis-15107	22	1	however	however	ADV
fcis-15107	22	2	,	,	PUNCT
fcis-15107	22	3	due	due	ADP
fcis-15107	22	4	to	to	ADP
fcis-15107	22	5	the	the	DET
fcis-15107	22	6	small	small	ADJ
fcis-15107	22	7	size	size	NOUN
fcis-15107	22	8	and	and	CCONJ
fcis-15107	22	9	irregular	irregular	ADJ
fcis-15107	22	10	shape	shape	NOUN
fcis-15107	22	11	of	of	ADP
fcis-15107	22	12	the	the	DET
fcis-15107	22	13	lesion	lesion	NOUN
fcis-15107	22	14	area	area	NOUN
fcis-15107	22	15	,	,	PUNCT
fcis-15107	22	16	traditional	traditional	ADJ
fcis-15107	22	17	methods	method	NOUN
fcis-15107	22	18	have	have	VERB
fcis-15107	22	19	certain	certain	ADJ
fcis-15107	22	20	limitations	limitation	NOUN
fcis-15107	22	21	when	when	SCONJ
fcis-15107	22	22	segmenting	segment	VERB
fcis-15107	22	23	images	image	NOUN
fcis-15107	22	24	.	.	PUNCT
fcis-15107	23	1	they	they	PRON
fcis-15107	23	2	may	may	AUX
fcis-15107	23	3	not	not	PART
fcis-15107	23	4	be	be	AUX
fcis-15107	23	5	able	able	ADJ
fcis-15107	23	6	to	to	PART
fcis-15107	23	7	accurately	accurately	ADV
fcis-15107	23	8	locate	locate	VERB
fcis-15107	23	9	the	the	DET
fcis-15107	23	10	nodule	nodule	NOUN
fcis-15107	23	11	position	position	NOUN
fcis-15107	23	12	,	,	PUNCT
fcis-15107	23	13	resulting	result	VERB
fcis-15107	23	14	in	in	ADP
fcis-15107	23	15	low	low	ADJ
fcis-15107	23	16	model	model	NOUN
fcis-15107	23	17	segmentation	segmentation	NOUN
fcis-15107	23	18	accuracy	accuracy	NOUN
fcis-15107	23	19	,	,	PUNCT
fcis-15107	23	20	and	and	CCONJ
fcis-15107	23	21	may	may	AUX
fcis-15107	23	22	even	even	ADV
fcis-15107	23	23	increase	increase	VERB
fcis-15107	23	24	with	with	ADP
fcis-15107	23	25	the	the	DET
fcis-15107	23	26	network	network	NOUN
fcis-15107	23	27	model	model	NOUN
fcis-15107	23	28	layer	layer	NOUN
fcis-15107	23	29	.	.	PUNCT
fcis-15107	24	1	deepening	deepening	NOUN
fcis-15107	24	2	loses	lose	VERB
fcis-15107	24	3	some	some	DET
fcis-15107	24	4	information	information	NOUN
fcis-15107	24	5	,	,	PUNCT
fcis-15107	24	6	so	so	SCONJ
fcis-15107	24	7	that	that	SCONJ
fcis-15107	24	8	more	more	ADJ
fcis-15107	24	9	features	feature	NOUN
fcis-15107	24	10	can	can	AUX
fcis-15107	24	11	not	not	PART
fcis-15107	24	12	be	be	AUX
fcis-15107	24	13	effectively	effectively	ADV
fcis-15107	24	14	obtained	obtain	VERB
fcis-15107	24	15	.	.	PUNCT
fcis-15107	25	1	to	to	ADP
fcis-15107	25	2	this	this	DET
fcis-15107	25	3	end	end	NOUN
fcis-15107	25	4	,	,	PUNCT
fcis-15107	25	5	this	this	DET
fcis-15107	25	6	paper	paper	NOUN
fcis-15107	25	7	proposes	propose	VERB
fcis-15107	25	8	a	a	DET
fcis-15107	25	9	lesion	lesion	NOUN
fcis-15107	25	10	image	image	NOUN
fcis-15107	25	11	segmentation	segmentation	NOUN
fcis-15107	25	12	method	method	NOUN
fcis-15107	25	13	based	base	VERB
fcis-15107	25	14	on	on	ADP
fcis-15107	25	15	une	une	PROPN
fcis-15107	25	16	x	x	X
fcis-15107	25	17	t	t	NOUN
fcis-15107	25	18	combined	combine	VERB
fcis-15107	25	19	with	with	ADP
fcis-15107	25	20	multiscale	multiscale	ADJ
fcis-15107	25	21	feature	feature	NOUN
fcis-15107	25	22	fusion	fusion	NOUN
fcis-15107	25	23	and	and	CCONJ
fcis-15107	25	24	attention	attention	NOUN
fcis-15107	25	25	mechanism	mechanism	NOUN
fcis-15107	25	26	.	.	PUNCT
fcis-15107	26	1	first	first	ADV
fcis-15107	26	2	,	,	PUNCT
fcis-15107	26	3	we	we	PRON
fcis-15107	26	4	introduce	introduce	VERB
fcis-15107	26	5	a	a	DET
fcis-15107	26	6	multi	multi	ADJ
fcis-15107	26	7	scale	scale	NOUN
fcis-15107	26	8	feature	feature	NOUN
fcis-15107	26	9	fusion	fusion	NOUN
fcis-15107	26	10	mechanism	mechanism	NOUN
fcis-15107	26	11	based	base	VERB
fcis-15107	26	12	on	on	ADP
fcis-15107	26	13	the	the	DET
fcis-15107	26	14	une	une	PROPN
fcis-15107	26	15	an	an	DET
fcis-15107	26	16	attention	attention	NOUN
fcis-15107	26	17	mechanism	mechanism	NOUN
fcis-15107	26	18	is	be	AUX
fcis-15107	26	19	introduced	introduce	VERB
fcis-15107	26	20	based	base	VERB
fcis-15107	26	21	on	on	ADP
fcis-15107	26	22	x	x	PROPN
fcis-15107	26	23	t	t	PROPN
fcis-15107	26	24	;	;	PUNCT
fcis-15107	26	25	finally	finally	ADV
fcis-15107	26	26	,	,	PUNCT
fcis-15107	26	27	we	we	PRON
fcis-15107	26	28	use	use	VERB
fcis-15107	26	29	a	a	DET
fcis-15107	26	30	joint	joint	ADJ
fcis-15107	26	31	loss	loss	NOUN
fcis-15107	26	32	function	function	NOUN
fcis-15107	26	33	to	to	PART
fcis-15107	26	34	improve	improve	VERB
fcis-15107	26	35	the	the	DET
fcis-15107	26	36	sensitivity	sensitivity	NOUN
fcis-15107	26	37	of	of	ADP
fcis-15107	26	38	the	the	DET
fcis-15107	26	39	network	network	NOUN
fcis-15107	26	40	model	model	NOUN
fcis-15107	26	41	to	to	PART
fcis-15107	26	42	edge	edge	VERB
fcis-15107	26	43	features	feature	NOUN
fcis-15107	26	44	.	.	PUNCT
fcis-15107	27	1	2	2	X
fcis-15107	27	2	.	.	X
fcis-15107	27	3	related	relate	VERB
fcis-15107	27	4	work	work	NOUN
fcis-15107	27	5	previous	previous	ADJ
fcis-15107	27	6	researchers	researcher	NOUN
fcis-15107	27	7	have	have	AUX
fcis-15107	27	8	tried	try	VERB
fcis-15107	27	9	to	to	PART
fcis-15107	27	10	build	build	VERB
fcis-15107	27	11	an	an	DET
fcis-15107	27	12	extremely	extremely	ADV
fcis-15107	27	13	accurate	accurate	ADJ
fcis-15107	27	14	,	,	PUNCT
fcis-15107	27	15	effective	effective	ADJ
fcis-15107	27	16	,	,	PUNCT
fcis-15107	27	17	and	and	CCONJ
fcis-15107	27	18	automatic	automatic	ADJ
fcis-15107	27	19	lesion	lesion	NOUN
fcis-15107	27	20	area	area	NOUN
fcis-15107	27	21	segmentation	segmentation	NOUN
fcis-15107	27	22	system	system	NOUN
fcis-15107	27	23	that	that	PRON
fcis-15107	27	24	can	can	AUX
fcis-15107	27	25	help	help	VERB
fcis-15107	27	26	doctors	doctor	NOUN
fcis-15107	27	27	detect	detect	VERB
fcis-15107	27	28	lesion	lesion	NOUN
fcis-15107	27	29	areas	area	NOUN
fcis-15107	27	30	.	.	PUNCT
fcis-15107	28	1	these	these	DET
fcis-15107	28	2	attempts	attempt	NOUN
fcis-15107	28	3	are	be	AUX
fcis-15107	28	4	divided	divide	VERB
fcis-15107	28	5	into	into	ADP
fcis-15107	28	6	two	two	NUM
fcis-15107	28	7	broad	broad	ADJ
fcis-15107	28	8	categories	category	NOUN
fcis-15107	28	9	:	:	PUNCT
fcis-15107	28	10	image	image	NOUN
fcis-15107	28	11	processing	process	VERB
fcis-15107	28	12	-based	-based	ADJ
fcis-15107	28	13	models	model	NOUN
fcis-15107	28	14	and	and	CCONJ
fcis-15107	28	15	deep	deep	ADJ
fcis-15107	28	16	learning	learning	NOUN
fcis-15107	28	17	-	-	PUNCT
fcis-15107	28	18	based	base	VERB
fcis-15107	28	19	models	model	NOUN
fcis-15107	28	20	.	.	PUNCT
fcis-15107	29	1	image	image	NOUN
fcis-15107	29	2	processing	processing	NOUN
fcis-15107	29	3	models	model	NOUN
fcis-15107	29	4	including	include	VERB
fcis-15107	29	5	morphological	morphological	ADJ
fcis-15107	29	6	operations	operation	NOUN
fcis-15107	29	7	,	,	PUNCT
fcis-15107	29	8	region	region	NOUN
fcis-15107	29	9	growing	grow	VERB
fcis-15107	29	10	algorithms	algorithm	NOUN
fcis-15107	29	11	and	and	CCONJ
fcis-15107	29	12	energy	energy	NOUN
fcis-15107	29	13	optimization	optimization	NOUN
fcis-15107	29	14	techniques	technique	NOUN
fcis-15107	29	15	are	be	AUX
fcis-15107	29	16	the	the	DET
fcis-15107	29	17	most	most	ADV
fcis-15107	29	18	commonly	commonly	ADV
fcis-15107	29	19	used	use	VERB
fcis-15107	29	20	methods	method	NOUN
fcis-15107	29	21	.	.	PUNCT
fcis-15107	30	1	in	in	ADP
fcis-15107	30	2	the	the	DET
fcis-15107	30	3	morphology	morphology	NOUN
fcis-15107	30	4	-	-	PUNCT
fcis-15107	30	5	based	base	VERB
fcis-15107	30	6	approach	approach	NOUN
fcis-15107	30	7	,	,	PUNCT
fcis-15107	30	8	researchers	researcher	NOUN
fcis-15107	30	9	used	use	VERB
fcis-15107	30	10	morphological	morphological	ADJ
fcis-15107	30	11	opening	opening	NOUN
fcis-15107	30	12	operations	operation	NOUN
fcis-15107	30	13	and	and	CCONJ
fcis-15107	30	14	connection	connection	NOUN
fcis-15107	30	15	component	component	NOUN
fcis-15107	30	16	selection	selection	NOUN
fcis-15107	30	17	methods	method	NOUN
fcis-15107	30	18	to	to	PART
fcis-15107	30	19	remove	remove	VERB
fcis-15107	30	20	vessels	vessel	NOUN
fcis-15107	30	21	attached	attach	VERB
fcis-15107	30	22	to	to	ADP
fcis-15107	30	23	nodules	nodule	NOUN
fcis-15107	30	24	.	.	PUNCT
fcis-15107	31	1	however	however	ADV
fcis-15107	31	2	,	,	PUNCT
fcis-15107	31	3	it	it	PRON
fcis-15107	31	4	is	be	AUX
fcis-15107	31	5	challenging	challenge	VERB
fcis-15107	31	6	to	to	PART
fcis-15107	31	7	use	use	VERB
fcis-15107	31	8	fixed	fix	VERB
fcis-15107	31	9	-	-	PUNCT
fcis-15107	31	10	size	size	NOUN
fcis-15107	31	11	morphological	morphological	ADJ
fcis-15107	31	12	templates	template	NOUN
fcis-15107	31	13	to	to	PART
fcis-15107	31	14	isolate	isolate	VERB
fcis-15107	31	15	lesions	lesion	NOUN
fcis-15107	31	16	that	that	PRON
fcis-15107	31	17	have	have	VERB
fcis-15107	31	18	extensive	extensive	ADJ
fcis-15107	31	19	contact	contact	NOUN
fcis-15107	31	20	areas	area	NOUN
fcis-15107	31	21	with	with	ADP
fcis-15107	31	22	other	other	ADJ
fcis-15107	31	23	lesion	lesion	NOUN
fcis-15107	31	24	regions	region	NOUN
fcis-15107	31	25	.	.	PUNCT
fcis-15107	32	1	as	as	ADP
fcis-15107	32	2	a	a	DET
fcis-15107	32	3	result	result	NOUN
fcis-15107	32	4	,	,	PUNCT
fcis-15107	32	5	more	more	ADV
fcis-15107	32	6	complex	complex	ADJ
fcis-15107	32	7	morphological	morphological	ADJ
fcis-15107	32	8	processes	process	NOUN
fcis-15107	32	9	incorporating	incorporate	VERB
fcis-15107	32	10	shape	shape	NOUN
fcis-15107	32	11	assumptions	assumption	NOUN
fcis-15107	32	12	are	be	AUX
fcis-15107	32	13	introduced	introduce	VERB
fcis-15107	32	14	.	.	PUNCT
fcis-15107	33	1	kuhnigk	kuhnigk	PROPN
fcis-15107	33	2	et	et	PROPN
fcis-15107	33	3	al	al	PROPN
fcis-15107	33	4	.	.	PROPN
fcis-15107	33	5	8	8	NUM
fcis-15107	33	6	found	find	VERB
fcis-15107	33	7	that	that	SCONJ
fcis-15107	33	8	vessel	vessel	NOUN
fcis-15107	33	9	radius	radius	NOUN
fcis-15107	33	10	decreased	decrease	VERB
fcis-15107	33	11	as	as	SCONJ
fcis-15107	33	12	it	it	PRON
fcis-15107	33	13	evolved	evolve	VERB
fcis-15107	33	14	toward	toward	ADP
fcis-15107	33	15	the	the	DET
fcis-15107	33	16	lung	lung	NOUN
fcis-15107	33	17	periphery	periphery	NOUN
fcis-15107	33	18	.	.	PUNCT
fcis-15107	34	1	furthermore	furthermore	ADV
fcis-15107	34	2	,	,	PUNCT
fcis-15107	34	3	they	they	PRON
fcis-15107	34	4	recommended	recommend	VERB
fcis-15107	34	5	the	the	DET
fcis-15107	34	6	combined	combine	VERB
fcis-15107	34	7	use	use	NOUN
fcis-15107	34	8	of	of	ADP
fcis-15107	34	9	rolling	roll	VERB
fcis-15107	34	10	ball	ball	NOUN
fcis-15107	34	11	filters	filter	NOUN
fcis-15107	34	12	and	and	CCONJ
fcis-15107	34	13	rule	rule	NOUN
fcis-15107	34	14	-	-	PUNCT
fcis-15107	34	15	based	base	VERB
fcis-15107	34	16	pleural	pleural	ADJ
fcis-15107	34	17	nodule	nodule	ADJ
fcis-15107	34	18	analysis	analysis	NOUN
fcis-15107	34	19	.	.	PUNCT
fcis-15107	35	1	selection	selection	NOUN
fcis-15107	35	2	of	of	ADP
fcis-15107	35	3	morphological	morphological	ADJ
fcis-15107	35	4	template	template	NOUN
fcis-15107	35	5	size	size	NOUN
fcis-15107	35	6	is	be	AUX
fcis-15107	35	7	a	a	DET
fcis-15107	35	8	significant	significant	ADJ
fcis-15107	35	9	challenge	challenge	NOUN
fcis-15107	35	10	for	for	ADP
fcis-15107	35	11	morphological	morphological	ADJ
fcis-15107	35	12	methods	method	NOUN
fcis-15107	35	13	because	because	SCONJ
fcis-15107	35	14	it	it	PRON
fcis-15107	35	15	is	be	AUX
fcis-15107	35	16	difficult	difficult	ADJ
fcis-15107	35	17	to	to	PART
fcis-15107	35	18	identify	identify	VERB
fcis-15107	35	19	appropriate	appropriate	ADJ
fcis-15107	35	20	templates	template	NOUN
fcis-15107	35	21	for	for	ADP
fcis-15107	35	22	morphology	morphology	NOUN
fcis-15107	35	23	of	of	ADP
fcis-15107	35	24	different	different	ADJ
fcis-15107	35	25	nodule	nodule	NOUN
fcis-15107	35	26	sizes	size	NOUN
fcis-15107	35	27	.	.	PUNCT
fcis-15107	36	1	zhou	zhou	PROPN
fcis-15107	36	2	et	et	PROPN
fcis-15107	36	3	al12	al12	PROPN
fcis-15107	36	4	introduced	introduce	VERB
fcis-15107	36	5	a	a	DET
fcis-15107	36	6	fully	fully	ADV
fcis-15107	36	7	automated	automate	VERB
fcis-15107	36	8	lung	lung	NOUN
fcis-15107	36	9	segmentation	segmentation	NOUN
fcis-15107	36	10	method	method	NOUN
fcis-15107	36	11	for	for	ADP
fcis-15107	36	12	parapleural	parapleural	ADJ
fcis-15107	36	13	nodules	nodule	NOUN
fcis-15107	36	14	.	.	PUNCT
fcis-15107	37	1	nonlinear	nonlinear	ADJ
fcis-15107	37	2	anisotropic	anisotropic	NOUN
fcis-15107	37	3	diffusion	diffusion	NOUN
fcis-15107	37	4	filtering	filtering	NOUN
fcis-15107	37	5	method	method	NOUN
fcis-15107	37	6	is	be	AUX
fcis-15107	37	7	used	use	VERB
fcis-15107	37	8	to	to	PART
fcis-15107	37	9	reduce	reduce	VERB
fcis-15107	37	10	image	image	NOUN
fcis-15107	37	11	noise	noise	NOUN
fcis-15107	37	12	.	.	PUNCT
fcis-15107	38	1	the	the	DET
fcis-15107	38	2	chest	chest	NOUN
fcis-15107	38	3	region	region	NOUN
fcis-15107	38	4	is	be	AUX
fcis-15107	38	5	extracted	extract	VERB
fcis-15107	38	6	using	use	VERB
fcis-15107	38	7	thresholding	thresholding	NOUN
fcis-15107	38	8	,	,	PUNCT
fcis-15107	38	9	2d	2d	NUM
fcis-15107	38	10	hole	hole	NOUN
fcis-15107	38	11	filling	filling	NOUN
fcis-15107	38	12	and	and	CCONJ
fcis-15107	38	13	maximum	maximum	ADJ
fcis-15107	38	14	connected	connect	VERB
fcis-15107	38	15	component	component	NOUN
fcis-15107	38	16	search	search	NOUN
fcis-15107	38	17	methods	method	NOUN
fcis-15107	38	18	.	.	PUNCT
fcis-15107	39	1	lung	lung	NOUN
fcis-15107	39	2	parenchyma	parenchyma	NOUN
fcis-15107	39	3	was	be	AUX
fcis-15107	39	4	separated	separate	VERB
fcis-15107	39	5	using	use	VERB
fcis-15107	39	6	fuzzy	fuzzy	ADJ
fcis-15107	39	7	cmeans	cmean	NOUN
fcis-15107	39	8	algorithm	algorithm	NOUN
fcis-15107	39	9	,	,	PUNCT
fcis-15107	39	10	region	region	NOUN
fcis-15107	39	11	growing	grow	VERB
fcis-15107	39	12	algorithm	algorithm	NOUN
fcis-15107	39	13	and	and	CCONJ
fcis-15107	39	14	dynamic	dynamic	ADJ
fcis-15107	39	15	programming	programming	NOUN
fcis-15107	39	16	method	method	NOUN
fcis-15107	39	17	.	.	PUNCT
fcis-15107	40	1	abbas	abbas	PROPN
fcis-15107	40	2	et	et	PROPN
fcis-15107	41	1	al21	al21	PROPN
fcis-15107	41	2	proposed	propose	VERB
fcis-15107	41	3	a	a	DET
fcis-15107	41	4	method	method	NOUN
fcis-15107	41	5	to	to	PART
fcis-15107	41	6	segment	segment	VERB
fcis-15107	41	7	pulmonary	pulmonary	ADJ
fcis-15107	41	8	nodules	nodule	NOUN
fcis-15107	41	9	in	in	ADP
fcis-15107	41	10	ct	ct	NUM
fcis-15107	41	11	images	image	NOUN
fcis-15107	41	12	.	.	PUNCT
fcis-15107	42	1	preprocessing	preprocesse	VERB
fcis-15107	42	2	31	31	NUM
fcis-15107	42	3	techniques	technique	NOUN
fcis-15107	42	4	such	such	ADJ
fcis-15107	42	5	as	as	ADP
fcis-15107	42	6	unsharp	unsharp	ADJ
fcis-15107	42	7	energy	energy	NOUN
fcis-15107	42	8	masking	masking	NOUN
fcis-15107	42	9	and	and	CCONJ
fcis-15107	42	10	discrete	discrete	ADJ
fcis-15107	42	11	wavelet	wavelet	NOUN
fcis-15107	42	12	transform	transform	NOUN
fcis-15107	42	13	have	have	AUX
fcis-15107	42	14	been	be	AUX
fcis-15107	42	15	used	use	VERB
fcis-15107	42	16	to	to	PART
fcis-15107	42	17	enhance	enhance	VERB
fcis-15107	42	18	images	image	NOUN
fcis-15107	42	19	.	.	PUNCT
fcis-15107	43	1	the	the	DET
fcis-15107	43	2	proposed	propose	VERB
fcis-15107	43	3	system	system	NOUN
fcis-15107	43	4	has	have	VERB
fcis-15107	43	5	an	an	DET
fcis-15107	43	6	area	area	NOUN
fcis-15107	43	7	overlap	overlap	NOUN
fcis-15107	43	8	measure	measure	NOUN
fcis-15107	43	9	(	(	PUNCT
fcis-15107	43	10	aom	aom	NOUN
fcis-15107	43	11	)	)	PUNCT
fcis-15107	43	12	of	of	ADP
fcis-15107	43	13	95	95	NUM
fcis-15107	43	14	%	%	NOUN
fcis-15107	43	15	,	,	PUNCT
fcis-15107	43	16	a	a	DET
fcis-15107	43	17	combined	combine	VERB
fcis-15107	43	18	equal	equal	ADJ
fcis-15107	43	19	importance	importance	NOUN
fcis-15107	43	20	(	(	PUNCT
fcis-15107	43	21	cei	cei	NOUN
fcis-15107	43	22	)	)	PUNCT
fcis-15107	43	23	of	of	ADP
fcis-15107	43	24	92	92	NUM
fcis-15107	43	25	%	%	NOUN
fcis-15107	43	26	,	,	PUNCT
fcis-15107	43	27	a	a	DET
fcis-15107	43	28	hausdorff	hausdorff	NOUN
fcis-15107	43	29	distance	distance	NOUN
fcis-15107	43	30	(	(	PUNCT
fcis-15107	43	31	hdd	hdd	NOUN
fcis-15107	43	32	)	)	PUNCT
fcis-15107	43	33	of	of	ADP
fcis-15107	43	34	91	91	NUM
fcis-15107	43	35	%	%	NOUN
fcis-15107	43	36	,	,	PUNCT
fcis-15107	43	37	and	and	CCONJ
fcis-15107	43	38	a	a	DET
fcis-15107	43	39	hamoud	hamoud	ADJ
fcis-15107	43	40	distance	distance	NOUN
fcis-15107	43	41	(	(	PUNCT
fcis-15107	43	42	hmd	hmd	NOUN
fcis-15107	43	43	)	)	PUNCT
fcis-15107	43	44	of	of	ADP
fcis-15107	43	45	87	87	NUM
fcis-15107	43	46	%	%	NOUN
fcis-15107	43	47	.	.	PUNCT
fcis-15107	44	1	long	long	ADV
fcis-15107	44	2	et	et	PROPN
fcis-15107	44	3	al.22	al.22	PROPN
fcis-15107	44	4	)	)	PUNCT
fcis-15107	44	5	developed	develop	VERB
fcis-15107	44	6	a	a	DET
fcis-15107	44	7	fully	fully	ADV
fcis-15107	44	8	convolutional	convolutional	ADJ
fcis-15107	44	9	neural	neural	ADJ
fcis-15107	44	10	network	network	NOUN
fcis-15107	44	11	(	(	PUNCT
fcis-15107	44	12	fcn	fcn	PROPN
fcis-15107	44	13	)	)	PUNCT
fcis-15107	44	14	for	for	ADP
fcis-15107	44	15	semantic	semantic	ADJ
fcis-15107	44	16	segmentation	segmentation	NOUN
fcis-15107	44	17	.	.	PUNCT
fcis-15107	45	1	the	the	DET
fcis-15107	45	2	fully	fully	ADV
fcis-15107	45	3	connected	connected	ADJ
fcis-15107	45	4	layers	layer	NOUN
fcis-15107	45	5	of	of	ADP
fcis-15107	45	6	the	the	DET
fcis-15107	45	7	cnn	cnn	PROPN
fcis-15107	45	8	are	be	AUX
fcis-15107	45	9	removed	remove	VERB
fcis-15107	45	10	and	and	CCONJ
fcis-15107	45	11	deconvolutional	deconvolutional	ADJ
fcis-15107	45	12	layers	layer	NOUN
fcis-15107	45	13	are	be	AUX
fcis-15107	45	14	introduced	introduce	VERB
fcis-15107	45	15	to	to	PART
fcis-15107	45	16	make	make	VERB
fcis-15107	45	17	the	the	DET
fcis-15107	45	18	output	output	NOUN
fcis-15107	45	19	dimensions	dimension	NOUN
fcis-15107	45	20	the	the	DET
fcis-15107	45	21	same	same	ADJ
fcis-15107	45	22	as	as	ADP
fcis-15107	45	23	those	those	PRON
fcis-15107	45	24	of	of	ADP
fcis-15107	45	25	the	the	DET
fcis-15107	45	26	input	input	NOUN
fcis-15107	45	27	image	image	NOUN
fcis-15107	45	28	.	.	PUNCT
fcis-15107	46	1	skip	skip	ADJ
fcis-15107	46	2	connections	connection	NOUN
fcis-15107	46	3	are	be	AUX
fcis-15107	46	4	introduced	introduce	VERB
fcis-15107	46	5	,	,	PUNCT
fcis-15107	46	6	which	which	PRON
fcis-15107	46	7	combine	combine	VERB
fcis-15107	46	8	coarse	coarse	ADV
fcis-15107	46	9	and	and	CCONJ
fcis-15107	46	10	fine	fine	ADJ
fcis-15107	46	11	layers	layer	NOUN
fcis-15107	46	12	to	to	PART
fcis-15107	46	13	make	make	VERB
fcis-15107	46	14	dense	dense	ADJ
fcis-15107	46	15	predictions	prediction	NOUN
fcis-15107	46	16	possible	possible	ADJ
fcis-15107	46	17	.	.	PUNCT
fcis-15107	47	1	ronneberger	ronneberger	NOUN
fcis-15107	47	2	et	et	NOUN
fcis-15107	47	3	al.23	al.23	PROPN
fcis-15107	47	4	modified	modify	VERB
fcis-15107	47	5	and	and	CCONJ
fcis-15107	47	6	extended	extend	VERB
fcis-15107	47	7	fcn	fcn	NOUN
fcis-15107	47	8	and	and	CCONJ
fcis-15107	47	9	designed	design	VERB
fcis-15107	47	10	a	a	DET
fcis-15107	47	11	new	new	ADJ
fcis-15107	47	12	u	u	NOUN
fcis-15107	47	13	net	net	ADJ
fcis-15107	47	14	architecture	architecture	NOUN
fcis-15107	47	15	for	for	ADP
fcis-15107	47	16	biomedical	biomedical	ADJ
fcis-15107	47	17	segmentation	segmentation	NOUN
fcis-15107	47	18	-	-	PUNCT
fcis-15107	47	19	.	.	PUNCT
fcis-15107	47	20	unet	unet	NOUN
fcis-15107	47	21	is	be	AUX
fcis-15107	47	22	unique	unique	ADJ
fcis-15107	47	23	in	in	ADP
fcis-15107	47	24	that	that	SCONJ
fcis-15107	47	25	the	the	DET
fcis-15107	47	26	network	network	NOUN
fcis-15107	47	27	can	can	AUX
fcis-15107	47	28	perform	perform	VERB
fcis-15107	47	29	accurate	accurate	ADJ
fcis-15107	47	30	segmentation	segmentation	NOUN
fcis-15107	47	31	with	with	ADP
fcis-15107	47	32	fewer	few	ADJ
fcis-15107	47	33	training	training	NOUN
fcis-15107	47	34	images	image	NOUN
fcis-15107	47	35	.	.	PUNCT
fcis-15107	48	1	unext	unext	PROPN
fcis-15107	48	2	is	be	AUX
fcis-15107	48	3	a	a	DET
fcis-15107	48	4	paper	paper	NOUN
fcis-15107	48	5	released	release	VERB
fcis-15107	48	6	by	by	ADP
fcis-15107	48	7	johns	johns	PROPN
fcis-15107	48	8	hopkins	hopkins	PROPN
fcis-15107	48	9	university	university	PROPN
fcis-15107	48	10	in	in	ADP
fcis-15107	48	11	2022	2022	NUM
fcis-15107	48	12	.	.	PUNCT
fcis-15107	49	1	it	it	PRON
fcis-15107	49	2	uses	use	VERB
fcis-15107	49	3	convolutions	convolution	NOUN
fcis-15107	49	4	in	in	ADP
fcis-15107	49	5	the	the	DET
fcis-15107	49	6	early	early	ADJ
fcis-15107	49	7	stages	stage	NOUN
fcis-15107	49	8	and	and	CCONJ
fcis-15107	49	9	mlp	mlp	NOUN
fcis-15107	49	10	in	in	ADP
fcis-15107	49	11	the	the	DET
fcis-15107	49	12	latent	latent	NOUN
fcis-15107	49	13	space	space	NOUN
fcis-15107	49	14	stage	stage	NOUN
fcis-15107	49	15	.	.	PUNCT
fcis-15107	50	1	the	the	DET
fcis-15107	50	2	convolutional	convolutional	ADJ
fcis-15107	50	3	features	feature	NOUN
fcis-15107	50	4	are	be	AUX
fcis-15107	50	5	labeled	label	VERB
fcis-15107	50	6	and	and	CCONJ
fcis-15107	50	7	projected	project	VERB
fcis-15107	50	8	through	through	ADP
fcis-15107	50	9	a	a	DET
fcis-15107	50	10	tokenized	tokenized	ADJ
fcis-15107	50	11	mlp	mlp	NOUN
fcis-15107	50	12	block	block	NOUN
fcis-15107	50	13	,	,	PUNCT
fcis-15107	50	14	and	and	CCONJ
fcis-15107	50	15	the	the	DET
fcis-15107	50	16	representation	representation	NOUN
fcis-15107	50	17	is	be	AUX
fcis-15107	50	18	modeled	model	VERB
fcis-15107	50	19	using	use	VERB
fcis-15107	50	20	the	the	DET
fcis-15107	50	21	mlp	mlp	NOUN
fcis-15107	50	22	.	.	PUNCT
fcis-15107	51	1	unext	unext	PROPN
fcis-15107	51	2	is	be	AUX
fcis-15107	51	3	an	an	DET
fcis-15107	51	4	important	important	ADJ
fcis-15107	51	5	improvement	improvement	NOUN
fcis-15107	51	6	direction	direction	NOUN
fcis-15107	51	7	for	for	ADP
fcis-15107	51	8	lightweight	lightweight	ADJ
fcis-15107	51	9	segmentation	segmentation	NOUN
fcis-15107	51	10	.	.	PUNCT
fcis-15107	52	1	the	the	DET
fcis-15107	52	2	network	network	NOUN
fcis-15107	52	3	adopts	adopt	VERB
fcis-15107	52	4	overlap	overlap	NOUN
fcis-15107	52	5	-	-	PUNCT
fcis-15107	52	6	tile	tile	NOUN
fcis-15107	52	7	strategy	strategy	NOUN
fcis-15107	52	8	,	,	PUNCT
fcis-15107	52	9	data	data	NOUN
fcis-15107	52	10	enhancement	enhancement	NOUN
fcis-15107	52	11	,	,	PUNCT
fcis-15107	52	12	and	and	CCONJ
fcis-15107	52	13	weighted	weight	VERB
fcis-15107	52	14	loss	loss	NOUN
fcis-15107	52	15	technology	technology	NOUN
fcis-15107	52	16	,	,	PUNCT
fcis-15107	52	17	which	which	PRON
fcis-15107	52	18	can	can	AUX
fcis-15107	52	19	be	be	AUX
fcis-15107	52	20	applied	apply	VERB
fcis-15107	52	21	to	to	ADP
fcis-15107	52	22	real	real	ADJ
fcis-15107	52	23	-	-	PUNCT
fcis-15107	52	24	time	time	NOUN
fcis-15107	52	25	fast	fast	ADJ
fcis-15107	52	26	image	image	NOUN
fcis-15107	52	27	segmentation	segmentation	NOUN
fcis-15107	52	28	with	with	ADP
fcis-15107	52	29	simple	simple	ADJ
fcis-15107	52	30	calculation	calculation	NOUN
fcis-15107	52	31	and	and	CCONJ
fcis-15107	52	32	fast	fast	ADJ
fcis-15107	52	33	speed	speed	NOUN
fcis-15107	52	34	.	.	PUNCT
fcis-15107	53	1	the	the	DET
fcis-15107	53	2	most	most	ADV
fcis-15107	53	3	obvious	obvious	ADJ
fcis-15107	53	4	difference	difference	NOUN
fcis-15107	53	5	between	between	ADP
fcis-15107	53	6	unet	unet	NOUN
fcis-15107	53	7	and	and	CCONJ
fcis-15107	53	8	une	une	NOUN
fcis-15107	53	9	to	to	PART
fcis-15107	53	10	further	far	ADV
fcis-15107	53	11	improve	improve	VERB
fcis-15107	53	12	performance	performance	NOUN
fcis-15107	53	13	,	,	PUNCT
fcis-15107	53	14	we	we	PRON
fcis-15107	53	15	recommend	recommend	VERB
fcis-15107	53	16	shifting	shift	VERB
fcis-15107	53	17	the	the	DET
fcis-15107	53	18	input	input	NOUN
fcis-15107	53	19	channel	channel	NOUN
fcis-15107	53	20	when	when	SCONJ
fcis-15107	53	21	inputting	inputte	VERB
fcis-15107	53	22	mlp	mlp	NOUN
fcis-15107	53	23	in	in	ADP
fcis-15107	53	24	order	order	NOUN
fcis-15107	53	25	to	to	PART
fcis-15107	53	26	focus	focus	VERB
fcis-15107	53	27	on	on	ADP
fcis-15107	53	28	learning	learn	VERB
fcis-15107	53	29	local	local	ADJ
fcis-15107	53	30	dependencies	dependency	NOUN
fcis-15107	53	31	.	.	PUNCT
fcis-15107	54	1	using	use	VERB
fcis-15107	54	2	tokenized	tokenized	ADJ
fcis-15107	54	3	mlp	mlp	NOUN
fcis-15107	54	4	in	in	ADP
fcis-15107	54	5	the	the	DET
fcis-15107	54	6	latent	latent	NOUN
fcis-15107	54	7	space	space	NOUN
fcis-15107	54	8	reduces	reduce	VERB
fcis-15107	54	9	the	the	DET
fcis-15107	54	10	number	number	NOUN
fcis-15107	54	11	of	of	ADP
fcis-15107	54	12	parameters	parameter	NOUN
fcis-15107	54	13	and	and	CCONJ
fcis-15107	54	14	computational	computational	ADJ
fcis-15107	54	15	complexity	complexity	NOUN
fcis-15107	54	16	while	while	SCONJ
fcis-15107	54	17	producing	produce	VERB
fcis-15107	54	18	better	well	ADJ
fcis-15107	54	19	representations	representation	NOUN
fcis-15107	54	20	to	to	PART
fcis-15107	54	21	aid	aid	NOUN
fcis-15107	54	22	segmentation	segmentation	NOUN
fcis-15107	54	23	.	.	PUNCT
fcis-15107	55	1	the	the	DET
fcis-15107	55	2	network	network	NOUN
fcis-15107	55	3	also	also	ADV
fcis-15107	55	4	includes	include	VERB
fcis-15107	55	5	skip	skip	ADJ
fcis-15107	55	6	connections	connection	NOUN
fcis-15107	55	7	between	between	ADP
fcis-15107	55	8	encoders	encoder	NOUN
fcis-15107	55	9	and	and	CCONJ
fcis-15107	55	10	decoders	decoder	NOUN
fcis-15107	55	11	at	at	ADP
fcis-15107	55	12	all	all	DET
fcis-15107	55	13	levels	level	NOUN
fcis-15107	55	14	.	.	PUNCT
fcis-15107	56	1	test	test	NOUN
fcis-15107	56	2	results	result	NOUN
fcis-15107	56	3	show	show	VERB
fcis-15107	56	4	that	that	SCONJ
fcis-15107	56	5	compared	compare	VERB
fcis-15107	56	6	with	with	ADP
fcis-15107	56	7	the	the	DET
fcis-15107	56	8	current	current	ADJ
fcis-15107	56	9	state	state	NOUN
fcis-15107	56	10	-	-	PUNCT
fcis-15107	56	11	of	of	ADP
fcis-15107	56	12	-	-	PUNCT
fcis-15107	56	13	the	the	DET
fcis-15107	56	14	-	-	PUNCT
fcis-15107	56	15	art	art	NOUN
fcis-15107	56	16	medical	medical	ADJ
fcis-15107	56	17	image	image	NOUN
fcis-15107	56	18	segmentation	segmentation	NOUN
fcis-15107	56	19	architecture	architecture	NOUN
fcis-15107	56	20	,	,	PUNCT
fcis-15107	56	21	unext	unext	ADJ
fcis-15107	56	22	reduces	reduce	VERB
fcis-15107	56	23	the	the	DET
fcis-15107	56	24	number	number	NOUN
fcis-15107	56	25	of	of	ADP
fcis-15107	56	26	parameters	parameter	NOUN
fcis-15107	56	27	by	by	ADP
fcis-15107	56	28	72x	72x	NOUN
fcis-15107	56	29	,	,	PUNCT
fcis-15107	56	30	reduces	reduce	VERB
fcis-15107	56	31	computational	computational	ADJ
fcis-15107	56	32	complexity	complexity	NOUN
fcis-15107	56	33	by	by	ADP
fcis-15107	56	34	68x	68x	NOUN
fcis-15107	56	35	,	,	PUNCT
fcis-15107	56	36	increases	increase	VERB
fcis-15107	56	37	inference	inference	NOUN
fcis-15107	56	38	speed	speed	NOUN
fcis-15107	56	39	by	by	ADP
fcis-15107	56	40	10x	10x	NOUN
fcis-15107	56	41	,	,	PUNCT
fcis-15107	56	42	and	and	CCONJ
fcis-15107	56	43	also	also	ADV
fcis-15107	56	44	achieves	achieve	VERB
fcis-15107	56	45	better	well	ADJ
fcis-15107	56	46	segmentation	segmentation	NOUN
fcis-15107	56	47	performance	performance	NOUN
fcis-15107	56	48	.	.	PUNCT
fcis-15107	57	1	experiments	experiment	NOUN
fcis-15107	57	2	on	on	ADP
fcis-15107	57	3	different	different	ADJ
fcis-15107	57	4	data	datum	NOUN
fcis-15107	57	5	sets	set	NOUN
fcis-15107	57	6	have	have	AUX
fcis-15107	57	7	proven	prove	VERB
fcis-15107	57	8	that	that	SCONJ
fcis-15107	57	9	the	the	DET
fcis-15107	57	10	segmentation	segmentation	NOUN
fcis-15107	57	11	effect	effect	NOUN
fcis-15107	57	12	of	of	ADP
fcis-15107	57	13	the	the	DET
fcis-15107	57	14	unext	unext	PROPN
fcis-15107	57	15	network	network	NOUN
fcis-15107	57	16	needs	need	VERB
fcis-15107	57	17	to	to	PART
fcis-15107	57	18	be	be	AUX
fcis-15107	57	19	further	far	ADV
fcis-15107	57	20	improved	improve	VERB
fcis-15107	57	21	to	to	PART
fcis-15107	57	22	meet	meet	VERB
fcis-15107	57	23	the	the	DET
fcis-15107	57	24	requirements	requirement	NOUN
fcis-15107	57	25	of	of	ADP
fcis-15107	57	26	instant	instant	ADJ
fcis-15107	57	27	diagnosis	diagnosis	NOUN
fcis-15107	57	28	,	,	PUNCT
fcis-15107	57	29	accuracy	accuracy	NOUN
fcis-15107	57	30	and	and	CCONJ
fcis-15107	57	31	efficiency	efficiency	NOUN
fcis-15107	57	32	of	of	ADP
fcis-15107	57	33	medical	medical	ADJ
fcis-15107	57	34	pathology	pathology	NOUN
fcis-15107	57	35	images	image	NOUN
fcis-15107	57	36	.	.	PUNCT
fcis-15107	58	1	although	although	SCONJ
fcis-15107	58	2	the	the	DET
fcis-15107	58	3	above	above	ADJ
fcis-15107	58	4	methods	method	NOUN
fcis-15107	58	5	have	have	AUX
fcis-15107	58	6	improved	improve	VERB
fcis-15107	58	7	traditional	traditional	ADJ
fcis-15107	58	8	deep	deep	ADJ
fcis-15107	58	9	learning	learning	NOUN
fcis-15107	58	10	methods	method	NOUN
fcis-15107	58	11	,	,	PUNCT
fcis-15107	58	12	satisfactory	satisfactory	ADJ
fcis-15107	58	13	results	result	NOUN
fcis-15107	58	14	can	can	AUX
fcis-15107	58	15	not	not	PART
fcis-15107	58	16	be	be	AUX
fcis-15107	58	17	obtained	obtain	VERB
fcis-15107	58	18	by	by	ADP
fcis-15107	58	19	improving	improve	VERB
fcis-15107	58	20	only	only	ADV
fcis-15107	58	21	one	one	NUM
fcis-15107	58	22	method	method	NOUN
fcis-15107	58	23	or	or	CCONJ
fcis-15107	58	24	targeting	target	VERB
fcis-15107	58	25	a	a	DET
fcis-15107	58	26	certain	certain	ADJ
fcis-15107	58	27	structure	structure	NOUN
fcis-15107	58	28	of	of	ADP
fcis-15107	58	29	the	the	DET
fcis-15107	58	30	model	model	NOUN
fcis-15107	58	31	.	.	PUNCT
fcis-15107	59	1	to	to	ADP
fcis-15107	59	2	this	this	DET
fcis-15107	59	3	end	end	NOUN
fcis-15107	59	4	,	,	PUNCT
fcis-15107	59	5	this	this	DET
fcis-15107	59	6	paper	paper	NOUN
fcis-15107	59	7	proposes	propose	VERB
fcis-15107	59	8	an	an	DET
fcis-15107	59	9	image	image	NOUN
fcis-15107	59	10	segmentation	segmentation	NOUN
fcis-15107	59	11	method	method	NOUN
fcis-15107	59	12	(	(	PUNCT
fcis-15107	59	13	sc	sc	PROPN
fcis-15107	59	14	-	-	NOUN
fcis-15107	59	15	unext	unext	NOUN
fcis-15107	59	16	)	)	PUNCT
fcis-15107	59	17	based	base	VERB
fcis-15107	59	18	on	on	ADP
fcis-15107	59	19	unext	unext	PROPN
fcis-15107	59	20	that	that	PRON
fcis-15107	59	21	combines	combine	VERB
fcis-15107	59	22	edge	edge	NOUN
fcis-15107	59	23	detection	detection	NOUN
fcis-15107	59	24	,	,	PUNCT
fcis-15107	59	25	feature	feature	NOUN
fcis-15107	59	26	fusion	fusion	NOUN
fcis-15107	59	27	and	and	CCONJ
fcis-15107	59	28	attention	attention	NOUN
fcis-15107	59	29	mechanisms	mechanism	NOUN
fcis-15107	59	30	to	to	PART
fcis-15107	59	31	improve	improve	VERB
fcis-15107	59	32	the	the	DET
fcis-15107	59	33	segmentation	segmentation	NOUN
fcis-15107	59	34	of	of	ADP
fcis-15107	59	35	lesion	lesion	NOUN
fcis-15107	59	36	areas	area	NOUN
fcis-15107	59	37	.	.	PUNCT
fcis-15107	60	1	3	3	X
fcis-15107	60	2	.	.	X
fcis-15107	60	3	method	method	PROPN
fcis-15107	60	4	3.1	3.1	NUM
fcis-15107	60	5	.	.	PUNCT
fcis-15107	61	1	sc	sc	PROPN
fcis-15107	61	2	-	-	PUNCT
fcis-15107	61	3	unext	unext	ADJ
fcis-15107	61	4	network	network	NOUN
fcis-15107	61	5	architecture	architecture	NOUN
fcis-15107	61	6	in	in	ADP
fcis-15107	61	7	the	the	DET
fcis-15107	61	8	research	research	NOUN
fcis-15107	61	9	,	,	PUNCT
fcis-15107	61	10	in	in	ADP
fcis-15107	61	11	order	order	NOUN
fcis-15107	61	12	to	to	PART
fcis-15107	61	13	better	well	ADV
fcis-15107	61	14	realize	realize	VERB
fcis-15107	61	15	the	the	DET
fcis-15107	61	16	accurate	accurate	ADJ
fcis-15107	61	17	realtime	realtime	NOUN
fcis-15107	61	18	segmentation	segmentation	NOUN
fcis-15107	61	19	task	task	NOUN
fcis-15107	61	20	and	and	CCONJ
fcis-15107	61	21	avoid	avoid	VERB
fcis-15107	61	22	the	the	DET
fcis-15107	61	23	problem	problem	NOUN
fcis-15107	61	24	of	of	ADP
fcis-15107	61	25	losing	lose	VERB
fcis-15107	61	26	local	local	ADJ
fcis-15107	61	27	low	low	ADJ
fcis-15107	61	28	-	-	PUNCT
fcis-15107	61	29	dimensional	dimensional	ADJ
fcis-15107	61	30	features	feature	NOUN
fcis-15107	61	31	through	through	ADP
fcis-15107	61	32	direct	direct	ADJ
fcis-15107	61	33	large	large	ADJ
fcis-15107	61	34	-	-	PUNCT
fcis-15107	61	35	area	area	NOUN
fcis-15107	61	36	upsampling	upsampling	NOUN
fcis-15107	61	37	,	,	PUNCT
fcis-15107	61	38	which	which	PRON
fcis-15107	61	39	leads	lead	VERB
fcis-15107	61	40	to	to	ADP
fcis-15107	61	41	the	the	DET
fcis-15107	61	42	loss	loss	NOUN
fcis-15107	61	43	of	of	ADP
fcis-15107	61	44	too	too	ADV
fcis-15107	61	45	many	many	ADJ
fcis-15107	61	46	features	feature	NOUN
fcis-15107	61	47	on	on	ADP
fcis-15107	61	48	the	the	DET
fcis-15107	61	49	segmentation	segmentation	NOUN
fcis-15107	61	50	boundary	boundary	ADJ
fcis-15107	61	51	and	and	CCONJ
fcis-15107	61	52	the	the	DET
fcis-15107	61	53	inability	inability	NOUN
fcis-15107	61	54	to	to	PART
fcis-15107	61	55	restore	restore	VERB
fcis-15107	61	56	complete	complete	ADJ
fcis-15107	61	57	edge	edge	NOUN
fcis-15107	61	58	information	information	NOUN
fcis-15107	61	59	,	,	PUNCT
fcis-15107	61	60	only	only	ADV
fcis-15107	61	61	through	through	ADP
fcis-15107	61	62	features	feature	NOUN
fcis-15107	61	63	the	the	DET
fcis-15107	61	64	graph	graph	NOUN
fcis-15107	61	65	superimposes	superimpose	NOUN
fcis-15107	61	66	feature	feature	VERB
fcis-15107	61	67	information	information	NOUN
fcis-15107	61	68	in	in	ADP
fcis-15107	61	69	the	the	DET
fcis-15107	61	70	channel	channel	NOUN
fcis-15107	61	71	dimension	dimension	NOUN
fcis-15107	61	72	to	to	PART
fcis-15107	61	73	retain	retain	VERB
fcis-15107	61	74	feature	feature	NOUN
fcis-15107	61	75	information	information	NOUN
fcis-15107	61	76	.	.	PUNCT
fcis-15107	62	1	this	this	PRON
fcis-15107	62	2	will	will	AUX
fcis-15107	62	3	cause	cause	VERB
fcis-15107	62	4	the	the	DET
fcis-15107	62	5	last	last	ADJ
fcis-15107	62	6	few	few	ADJ
fcis-15107	62	7	layers	layer	NOUN
fcis-15107	62	8	of	of	ADP
fcis-15107	62	9	feature	feature	NOUN
fcis-15107	62	10	maps	map	NOUN
fcis-15107	62	11	to	to	PART
fcis-15107	62	12	be	be	AUX
fcis-15107	62	13	too	too	ADV
fcis-15107	62	14	bloated	bloated	ADJ
fcis-15107	62	15	,	,	PUNCT
fcis-15107	62	16	causing	cause	VERB
fcis-15107	62	17	the	the	DET
fcis-15107	62	18	model	model	NOUN
fcis-15107	62	19	to	to	PART
fcis-15107	62	20	require	require	VERB
fcis-15107	62	21	a	a	DET
fcis-15107	62	22	large	large	ADJ
fcis-15107	62	23	amount	amount	NOUN
fcis-15107	62	24	of	of	ADP
fcis-15107	62	25	calculations	calculation	NOUN
fcis-15107	62	26	.	.	PUNCT
fcis-15107	63	1	based	base	VERB
fcis-15107	63	2	on	on	ADP
fcis-15107	63	3	these	these	DET
fcis-15107	63	4	problems	problem	NOUN
fcis-15107	63	5	,	,	PUNCT
fcis-15107	63	6	we	we	PRON
fcis-15107	63	7	adopt	adopt	VERB
fcis-15107	63	8	a	a	DET
fcis-15107	63	9	multi	multi	ADJ
fcis-15107	63	10	-	-	ADJ
fcis-15107	63	11	branch	branch	ADJ
fcis-15107	63	12	feature	feature	NOUN
fcis-15107	63	13	fusion	fusion	NOUN
fcis-15107	63	14	network	network	NOUN
fcis-15107	63	15	for	for	ADP
fcis-15107	63	16	medical	medical	ADJ
fcis-15107	63	17	image	image	NOUN
fcis-15107	63	18	segmentation	segmentation	NOUN
fcis-15107	63	19	.	.	PUNCT
fcis-15107	64	1	we	we	PRON
fcis-15107	64	2	first	first	ADV
fcis-15107	64	3	propagate	propagate	VERB
fcis-15107	64	4	contextual	contextual	ADJ
fcis-15107	64	5	information	information	NOUN
fcis-15107	64	6	to	to	ADP
fcis-15107	64	7	higher	high	ADJ
fcis-15107	64	8	-	-	PUNCT
fcis-15107	64	9	resolution	resolution	NOUN
fcis-15107	64	10	layers	layer	NOUN
fcis-15107	64	11	through	through	ADP
fcis-15107	64	12	progressive	progressive	ADJ
fcis-15107	64	13	upsampling	upsample	VERB
fcis-15107	64	14	to	to	PART
fcis-15107	64	15	obtain	obtain	VERB
fcis-15107	64	16	preliminary	preliminary	ADJ
fcis-15107	64	17	low	low	ADJ
fcis-15107	64	18	-	-	PUNCT
fcis-15107	64	19	level	level	NOUN
fcis-15107	64	20	semantic	semantic	ADJ
fcis-15107	64	21	features	feature	NOUN
fcis-15107	64	22	.	.	PUNCT
fcis-15107	65	1	we	we	PRON
fcis-15107	65	2	avoid	avoid	VERB
fcis-15107	65	3	superimposing	superimpose	VERB
fcis-15107	65	4	feature	feature	NOUN
fcis-15107	65	5	information	information	NOUN
fcis-15107	65	6	in	in	ADP
fcis-15107	65	7	the	the	DET
fcis-15107	65	8	channel	channel	NOUN
fcis-15107	65	9	dimension	dimension	NOUN
fcis-15107	65	10	of	of	ADP
fcis-15107	65	11	unet	unet	NOUN
fcis-15107	65	12	's	's	PART
fcis-15107	65	13	series	series	NOUN
fcis-15107	65	14	of	of	ADP
fcis-15107	65	15	related	related	ADJ
fcis-15107	65	16	models	model	NOUN
fcis-15107	65	17	,	,	PUNCT
fcis-15107	65	18	and	and	CCONJ
fcis-15107	65	19	choose	choose	VERB
fcis-15107	65	20	the	the	DET
fcis-15107	65	21	method	method	NOUN
fcis-15107	65	22	of	of	ADP
fcis-15107	65	23	feature	feature	NOUN
fcis-15107	65	24	map	map	NOUN
fcis-15107	65	25	multiplication	multiplication	NOUN
fcis-15107	65	26	to	to	PART
fcis-15107	65	27	fuse	fuse	NOUN
fcis-15107	65	28	features	feature	NOUN
fcis-15107	65	29	;	;	PUNCT
fcis-15107	65	30	therefore	therefore	ADV
fcis-15107	65	31	,	,	PUNCT
fcis-15107	65	32	most	most	ADJ
fcis-15107	65	33	of	of	ADP
fcis-15107	65	34	the	the	DET
fcis-15107	65	35	feature	feature	NOUN
fcis-15107	65	36	information	information	NOUN
fcis-15107	65	37	is	be	AUX
fcis-15107	65	38	well	well	ADV
fcis-15107	65	39	preserved	preserve	VERB
fcis-15107	65	40	,	,	PUNCT
fcis-15107	65	41	and	and	CCONJ
fcis-15107	65	42	boundary	boundary	ADJ
fcis-15107	65	43	information	information	NOUN
fcis-15107	65	44	can	can	AUX
fcis-15107	65	45	be	be	AUX
fcis-15107	65	46	effectively	effectively	ADV
fcis-15107	65	47	obtained	obtain	VERB
fcis-15107	65	48	,	,	PUNCT
fcis-15107	65	49	effectively	effectively	ADV
fcis-15107	65	50	reducing	reduce	VERB
fcis-15107	65	51	the	the	DET
fcis-15107	65	52	number	number	NOUN
fcis-15107	65	53	of	of	ADP
fcis-15107	65	54	failures	failure	NOUN
fcis-15107	65	55	.	.	PUNCT
fcis-15107	66	1	the	the	DET
fcis-15107	66	2	designed	design	VERB
fcis-15107	66	3	skip	skip	NOUN
fcis-15107	66	4	link	link	NOUN
fcis-15107	66	5	uses	use	VERB
fcis-15107	66	6	more	more	ADV
fcis-15107	66	7	detailed	detailed	ADJ
fcis-15107	66	8	low	low	ADJ
fcis-15107	66	9	-	-	PUNCT
fcis-15107	66	10	dimensional	dimensional	ADJ
fcis-15107	66	11	feature	feature	NOUN
fcis-15107	66	12	information	information	NOUN
fcis-15107	66	13	as	as	ADP
fcis-15107	66	14	a	a	DET
fcis-15107	66	15	supplement	supplement	NOUN
fcis-15107	66	16	to	to	PART
fcis-15107	66	17	feature	feature	VERB
fcis-15107	66	18	fusion	fusion	NOUN
fcis-15107	66	19	to	to	PART
fcis-15107	66	20	ensure	ensure	VERB
fcis-15107	66	21	that	that	SCONJ
fcis-15107	66	22	the	the	DET
fcis-15107	66	23	accuracy	accuracy	NOUN
fcis-15107	66	24	is	be	AUX
fcis-15107	66	25	slightly	slightly	ADV
fcis-15107	66	26	better	well	ADJ
fcis-15107	66	27	than	than	ADP
fcis-15107	66	28	unet	unet	NOUN
fcis-15107	66	29	(	(	PUNCT
fcis-15107	66	30	zhou	zhou	X
fcis-15107	66	31	et	et	PROPN
fcis-15107	66	32	al	al	PROPN
fcis-15107	66	33	.	.	PROPN
fcis-15107	66	34	,	,	PUNCT
fcis-15107	66	35	2018	2018	NUM
fcis-15107	66	36	,	,	PUNCT
fcis-15107	66	37	2020	2020	NUM
fcis-15107	66	38	)	)	PUNCT
fcis-15107	66	39	,	,	PUNCT
fcis-15107	66	40	resunet++	resunet++	NOUN
fcis-15107	66	41	(	(	PUNCT
fcis-15107	66	42	jha	jha	PROPN
fcis-15107	66	43	et	et	PROPN
fcis-15107	66	44	al	al	PROPN
fcis-15107	66	45	.	.	PROPN
fcis-15107	66	46	,	,	PUNCT
fcis-15107	66	47	2019	2019	NUM
fcis-15107	66	48	)	)	PUNCT
fcis-15107	66	49	and	and	CCONJ
fcis-15107	66	50	other	other	ADJ
fcis-15107	66	51	networks	network	NOUN
fcis-15107	66	52	run	run	VERB
fcis-15107	66	53	much	much	ADV
fcis-15107	66	54	faster	fast	ADV
fcis-15107	66	55	than	than	ADP
fcis-15107	66	56	other	other	ADJ
fcis-15107	66	57	models	model	NOUN
fcis-15107	66	58	;	;	PUNCT
fcis-15107	66	59	it	it	PRON
fcis-15107	66	60	also	also	ADV
fcis-15107	66	61	has	have	VERB
fcis-15107	66	62	the	the	DET
fcis-15107	66	63	advantages	advantage	NOUN
fcis-15107	66	64	of	of	ADP
fcis-15107	66	65	high	high	ADJ
fcis-15107	66	66	training	training	NOUN
fcis-15107	66	67	efficiency	efficiency	NOUN
fcis-15107	66	68	and	and	CCONJ
fcis-15107	66	69	strong	strong	ADJ
fcis-15107	66	70	generalization	generalization	NOUN
fcis-15107	66	71	ability	ability	NOUN
fcis-15107	66	72	.	.	PUNCT
fcis-15107	67	1	figure	figure	NOUN
fcis-15107	67	2	1	1	NUM
fcis-15107	67	3	.	.	X
fcis-15107	67	4	sc	sc	PROPN
fcis-15107	67	5	-	-	ADJ
fcis-15107	67	6	unext	unext	ADJ
fcis-15107	67	7	structure	structure	NOUN
fcis-15107	67	8	overall	overall	ADJ
fcis-15107	67	9	framework	framework	NOUN
fcis-15107	67	10	our	our	PRON
fcis-15107	67	11	network	network	NOUN
fcis-15107	67	12	consists	consist	VERB
fcis-15107	67	13	of	of	ADP
fcis-15107	67	14	three	three	NUM
fcis-15107	67	15	parts	part	NOUN
fcis-15107	67	16	:	:	PUNCT
fcis-15107	67	17	encoder	encoder	NOUN
fcis-15107	67	18	,	,	PUNCT
fcis-15107	67	19	multi	multi	ADJ
fcis-15107	67	20	-	-	ADJ
fcis-15107	67	21	scale	scale	ADJ
fcis-15107	67	22	cross	cross	ADJ
fcis-15107	67	23	-	-	ADJ
fcis-15107	67	24	skip	skip	ADJ
fcis-15107	67	25	connection	connection	NOUN
fcis-15107	67	26	and	and	CCONJ
fcis-15107	67	27	decoder	decoder	NOUN
fcis-15107	67	28	.	.	PUNCT
fcis-15107	68	1	in	in	ADP
fcis-15107	68	2	order	order	NOUN
fcis-15107	68	3	to	to	PART
fcis-15107	68	4	better	well	ADV
fcis-15107	68	5	integrate	integrate	VERB
fcis-15107	68	6	semantic	semantic	ADJ
fcis-15107	68	7	and	and	CCONJ
fcis-15107	68	8	scaleinconsistent	scaleinconsistent	NOUN
fcis-15107	68	9	features	feature	NOUN
fcis-15107	68	10	and	and	CCONJ
fcis-15107	68	11	further	far	ADV
fcis-15107	68	12	improve	improve	VERB
fcis-15107	68	13	the	the	DET
fcis-15107	68	14	segmentation	segmentation	NOUN
fcis-15107	68	15	effect	effect	NOUN
fcis-15107	68	16	,	,	PUNCT
fcis-15107	68	17	we	we	PRON
fcis-15107	68	18	propose	propose	VERB
fcis-15107	68	19	a	a	DET
fcis-15107	68	20	cross	cross	ADJ
fcis-15107	68	21	-	-	ADJ
fcis-15107	68	22	joint	joint	ADJ
fcis-15107	68	23	attention	attention	NOUN
fcis-15107	68	24	-	-	PUNCT
fcis-15107	68	25	guided	guide	VERB
fcis-15107	68	26	multi	multi	ADJ
fcis-15107	68	27	-	-	ADJ
fcis-15107	68	28	scale	scale	ADJ
fcis-15107	68	29	fusion	fusion	NOUN
fcis-15107	68	30	scheme	scheme	NOUN
fcis-15107	68	31	,	,	PUNCT
fcis-15107	68	32	which	which	PRON
fcis-15107	68	33	solves	solve	VERB
fcis-15107	68	34	the	the	DET
fcis-15107	68	35	problems	problem	NOUN
fcis-15107	68	36	that	that	PRON
fcis-15107	68	37	arise	arise	VERB
fcis-15107	68	38	when	when	SCONJ
fcis-15107	68	39	fusing	fuse	VERB
fcis-15107	68	40	features	feature	NOUN
fcis-15107	68	41	of	of	ADP
fcis-15107	68	42	different	different	ADJ
fcis-15107	68	43	scales	scale	NOUN
fcis-15107	68	44	.	.	PUNCT
fcis-15107	69	1	3.2	3.2	NUM
fcis-15107	69	2	.	.	PUNCT
fcis-15107	70	1	convolutional	convolutional	ADJ
fcis-15107	70	2	attention	attention	NOUN
fcis-15107	70	3	modules	module	NOUN
fcis-15107	70	4	convolutional	convolutional	ADJ
fcis-15107	70	5	block	block	NOUN
fcis-15107	70	6	attention	attention	NOUN
fcis-15107	70	7	module	module	NOUN
fcis-15107	70	8	(	(	PUNCT
fcis-15107	70	9	cbam	cbam	NOUN
fcis-15107	70	10	)	)	PUNCT
fcis-15107	70	11	consists	consist	VERB
fcis-15107	70	12	of	of	ADP
fcis-15107	70	13	channel	channel	NOUN
fcis-15107	70	14	attention	attention	NOUN
fcis-15107	70	15	and	and	CCONJ
fcis-15107	70	16	spatial	spatial	ADJ
fcis-15107	70	17	attention	attention	NOUN
fcis-15107	70	18	.	.	PUNCT
fcis-15107	71	1	among	among	ADP
fcis-15107	71	2	them	they	PRON
fcis-15107	71	3	,	,	PUNCT
fcis-15107	71	4	channel	channel	NOUN
fcis-15107	71	5	attention	attention	NOUN
fcis-15107	71	6	strengthens	strengthen	VERB
fcis-15107	71	7	the	the	DET
fcis-15107	71	8	connection	connection	NOUN
fcis-15107	71	9	between	between	ADP
fcis-15107	71	10	features	feature	NOUN
fcis-15107	71	11	in	in	ADP
fcis-15107	71	12	different	different	ADJ
fcis-15107	71	13	channels	channel	NOUN
fcis-15107	71	14	by	by	ADP
fcis-15107	71	15	using	use	VERB
fcis-15107	71	16	maximum	maximum	ADJ
fcis-15107	71	17	pooling	pooling	NOUN
fcis-15107	71	18	and	and	CCONJ
fcis-15107	71	19	average	average	ADJ
fcis-15107	71	20	pooling	pooling	NOUN
fcis-15107	71	21	to	to	PART
fcis-15107	71	22	pay	pay	VERB
fcis-15107	71	23	attention	attention	NOUN
fcis-15107	71	24	to	to	ADP
fcis-15107	71	25	the	the	DET
fcis-15107	71	26	information	information	NOUN
fcis-15107	71	27	between	between	ADP
fcis-15107	71	28	different	different	ADJ
fcis-15107	71	29	channels	channel	NOUN
fcis-15107	71	30	;	;	PUNCT
fcis-15107	71	31	spatial	spatial	ADJ
fcis-15107	71	32	attention	attention	NOUN
fcis-15107	71	33	improves	improve	VERB
fcis-15107	71	34	the	the	DET
fcis-15107	71	35	spatial	spatial	ADJ
fcis-15107	71	36	connection	connection	NOUN
fcis-15107	71	37	of	of	ADP
fcis-15107	71	38	the	the	DET
fcis-15107	71	39	network	network	NOUN
fcis-15107	71	40	by	by	ADP
fcis-15107	71	41	paying	pay	VERB
fcis-15107	71	42	attention	attention	NOUN
fcis-15107	71	43	to	to	ADP
fcis-15107	71	44	space	space	NOUN
fcis-15107	71	45	.	.	PUNCT
fcis-15107	72	1	combining	combine	VERB
fcis-15107	72	2	the	the	DET
fcis-15107	72	3	channel	channel	NOUN
fcis-15107	72	4	and	and	CCONJ
fcis-15107	72	5	spatial	spatial	ADJ
fcis-15107	72	6	attention	attention	NOUN
fcis-15107	72	7	mechanisms	mechanism	NOUN
fcis-15107	72	8	,	,	PUNCT
fcis-15107	72	9	adaptive	adaptive	ADJ
fcis-15107	72	10	feature	feature	NOUN
fcis-15107	72	11	extraction	extraction	NOUN
fcis-15107	72	12	can	can	AUX
fcis-15107	72	13	be	be	AUX
fcis-15107	72	14	achieved	achieve	VERB
fcis-15107	72	15	.	.	PUNCT
fcis-15107	73	1	the	the	DET
fcis-15107	73	2	cbam	cbam	NOUN
fcis-15107	73	3	model	model	NOUN
fcis-15107	73	4	structure	structure	NOUN
fcis-15107	73	5	is	be	AUX
fcis-15107	73	6	shown	show	VERB
fcis-15107	73	7	in	in	ADP
fcis-15107	73	8	figure	figure	NOUN
fcis-15107	73	9	2	2	NUM
fcis-15107	73	10	.	.	PUNCT
fcis-15107	73	11	figure	figure	NOUN
fcis-15107	73	12	2	2	NUM
fcis-15107	73	13	.	.	PUNCT
fcis-15107	73	14	cbam	cbam	NOUN
fcis-15107	73	15	module	module	NOUN
fcis-15107	73	16	cbam	cbam	NOUN
fcis-15107	73	17	can	can	AUX
fcis-15107	73	18	be	be	AUX
fcis-15107	73	19	expressed	express	VERB
fcis-15107	73	20	by	by	ADP
fcis-15107	73	21	the	the	DET
fcis-15107	73	22	following	follow	VERB
fcis-15107	73	23	formula	formula	NOUN
fcis-15107	73	24	:	:	PUNCT
fcis-15107	74	1	⊗	⊗	PROPN
fcis-15107	74	2	(	(	PUNCT
fcis-15107	74	3	1	1	X
fcis-15107	74	4	)	)	PUNCT
fcis-15107	74	5	⊗	⊗	NOUN
fcis-15107	74	6	(	(	PUNCT
fcis-15107	74	7	2	2	NUM
fcis-15107	74	8	)	)	PUNCT
fcis-15107	74	9	32	32	NUM
fcis-15107	74	10	among	among	ADP
fcis-15107	74	11	them	they	PRON
fcis-15107	74	12	,	,	PUNCT
fcis-15107	74	13	f	f	PROPN
fcis-15107	74	14	is	be	AUX
fcis-15107	74	15	the	the	DET
fcis-15107	74	16	feature	feature	NOUN
fcis-15107	74	17	map	map	NOUN
fcis-15107	74	18	,	,	PUNCT
fcis-15107	74	19	and	and	CCONJ
fcis-15107	74	20	represents	represent	VERB
fcis-15107	74	21	channel	channel	NOUN
fcis-15107	74	22	-	-	PUNCT
fcis-15107	74	23	based	base	VERB
fcis-15107	74	24	and	and	CCONJ
fcis-15107	74	25	spatial	spatial	ADV
fcis-15107	74	26	-	-	PUNCT
fcis-15107	74	27	based	base	VERB
fcis-15107	74	28	attention	attention	NOUN
fcis-15107	74	29	respectively	respectively	ADV
fcis-15107	74	30	,	,	PUNCT
fcis-15107	74	31	⊗	⊗	PROPN
fcis-15107	74	32	represents	represent	VERB
fcis-15107	74	33	element	element	ADJ
fcis-15107	74	34	-	-	ADJ
fcis-15107	74	35	wise	wise	ADJ
fcis-15107	74	36	multiplication	multiplication	NOUN
fcis-15107	74	37	,	,	PUNCT
fcis-15107	74	38	and	and	CCONJ
fcis-15107	74	39	represents	represent	VERB
fcis-15107	74	40	the	the	DET
fcis-15107	74	41	output	output	NOUN
fcis-15107	74	42	feature	feature	NOUN
fcis-15107	74	43	map	map	NOUN
fcis-15107	74	44	after	after	ADP
fcis-15107	74	45	channel	channel	NOUN
fcis-15107	74	46	attention	attention	NOUN
fcis-15107	74	47	and	and	CCONJ
fcis-15107	74	48	spatial	spatial	ADJ
fcis-15107	74	49	attention	attention	NOUN
fcis-15107	74	50	respectively	respectively	ADV
fcis-15107	74	51	.	.	PUNCT
fcis-15107	75	1	since	since	SCONJ
fcis-15107	75	2	the	the	DET
fcis-15107	75	3	input	input	NOUN
fcis-15107	75	4	and	and	CCONJ
fcis-15107	75	5	output	output	NOUN
fcis-15107	75	6	sizes	size	NOUN
fcis-15107	75	7	of	of	ADP
fcis-15107	75	8	the	the	DET
fcis-15107	75	9	cbam	cbam	NOUN
fcis-15107	75	10	module	module	NOUN
fcis-15107	75	11	are	be	AUX
fcis-15107	75	12	the	the	DET
fcis-15107	75	13	same	same	ADJ
fcis-15107	75	14	,	,	PUNCT
fcis-15107	75	15	it	it	PRON
fcis-15107	75	16	can	can	AUX
fcis-15107	75	17	be	be	AUX
fcis-15107	75	18	inserted	insert	VERB
fcis-15107	75	19	anywhere	anywhere	ADV
fcis-15107	75	20	in	in	ADP
fcis-15107	75	21	an	an	DET
fcis-15107	75	22	existing	exist	VERB
fcis-15107	75	23	model	model	NOUN
fcis-15107	75	24	.	.	PUNCT
fcis-15107	76	1	3.3	3.3	NUM
fcis-15107	76	2	.	.	PUNCT
fcis-15107	77	1	sc	sc	PROPN
fcis-15107	77	2	jump	jump	NOUN
fcis-15107	77	3	link	link	NOUN
fcis-15107	77	4	module	module	NOUN
fcis-15107	77	5	segmentation	segmentation	NOUN
fcis-15107	77	6	network	network	NOUN
fcis-15107	77	7	contain	contain	VERB
fcis-15107	77	8	more	more	ADV
fcis-15107	77	9	fine	fine	ADV
fcis-15107	77	10	-	-	PUNCT
fcis-15107	77	11	grained	grain	VERB
fcis-15107	77	12	information	information	NOUN
fcis-15107	77	13	,	,	PUNCT
fcis-15107	77	14	which	which	PRON
fcis-15107	77	15	facilitates	facilitate	VERB
fcis-15107	77	16	the	the	DET
fcis-15107	77	17	segmentation	segmentation	NOUN
fcis-15107	77	18	of	of	ADP
fcis-15107	77	19	small	small	ADJ
fcis-15107	77	20	lesions	lesion	NOUN
fcis-15107	77	21	.	.	PUNCT
fcis-15107	78	1	deep	deep	ADJ
fcis-15107	78	2	segmentation	segmentation	NOUN
fcis-15107	78	3	networks	network	NOUN
fcis-15107	78	4	can	can	AUX
fcis-15107	78	5	extract	extract	VERB
fcis-15107	78	6	more	more	ADV
fcis-15107	78	7	highlevel	highlevel	ADJ
fcis-15107	78	8	semantic	semantic	ADJ
fcis-15107	78	9	information	information	NOUN
fcis-15107	78	10	,	,	PUNCT
fcis-15107	78	11	thereby	thereby	ADV
fcis-15107	78	12	improving	improve	VERB
fcis-15107	78	13	segmentation	segmentation	NOUN
fcis-15107	78	14	accuracy	accuracy	NOUN
fcis-15107	78	15	.	.	PUNCT
fcis-15107	79	1	in	in	ADP
fcis-15107	79	2	addition	addition	NOUN
fcis-15107	79	3	,	,	PUNCT
fcis-15107	79	4	rich	rich	ADJ
fcis-15107	79	5	multi	multi	ADJ
fcis-15107	79	6	-	-	ADJ
fcis-15107	79	7	scale	scale	ADJ
fcis-15107	79	8	information	information	NOUN
fcis-15107	79	9	integrates	integrate	VERB
fcis-15107	79	10	the	the	DET
fcis-15107	79	11	characteristics	characteristic	NOUN
fcis-15107	79	12	of	of	ADP
fcis-15107	79	13	different	different	ADJ
fcis-15107	79	14	receptive	receptive	ADJ
fcis-15107	79	15	fields	field	NOUN
fcis-15107	79	16	,	,	PUNCT
fcis-15107	79	17	which	which	PRON
fcis-15107	79	18	is	be	AUX
fcis-15107	79	19	beneficial	beneficial	ADJ
fcis-15107	79	20	to	to	ADP
fcis-15107	79	21	the	the	DET
fcis-15107	79	22	segmentation	segmentation	NOUN
fcis-15107	79	23	of	of	ADP
fcis-15107	79	24	multi	multi	ADJ
fcis-15107	79	25	-	-	ADJ
fcis-15107	79	26	lesion	lesion	NOUN
fcis-15107	79	27	areas	area	NOUN
fcis-15107	79	28	.	.	PUNCT
fcis-15107	80	1	the	the	DET
fcis-15107	80	2	skip	skip	ADJ
fcis-15107	80	3	connection	connection	NOUN
fcis-15107	80	4	is	be	AUX
fcis-15107	80	5	redesigned	redesign	VERB
fcis-15107	80	6	to	to	PART
fcis-15107	80	7	aggregate	aggregate	VERB
fcis-15107	80	8	features	feature	NOUN
fcis-15107	80	9	of	of	ADP
fcis-15107	80	10	different	different	ADJ
fcis-15107	80	11	semantic	semantic	ADJ
fcis-15107	80	12	scales	scale	NOUN
fcis-15107	80	13	on	on	ADP
fcis-15107	80	14	the	the	DET
fcis-15107	80	15	decoder	decoder	NOUN
fcis-15107	80	16	subnetwork	subnetwork	NOUN
fcis-15107	80	17	to	to	PART
fcis-15107	80	18	form	form	VERB
fcis-15107	80	19	a	a	DET
fcis-15107	80	20	highly	highly	ADV
fcis-15107	80	21	flexible	flexible	ADJ
fcis-15107	80	22	feature	feature	NOUN
fcis-15107	80	23	fusion	fusion	NOUN
fcis-15107	80	24	scheme	scheme	NOUN
fcis-15107	80	25	.	.	PUNCT
fcis-15107	81	1	the	the	DET
fcis-15107	81	2	sc	sc	PROPN
fcis-15107	81	3	skip	skip	NOUN
fcis-15107	81	4	connection	connection	NOUN
fcis-15107	81	5	is	be	AUX
fcis-15107	81	6	an	an	DET
fcis-15107	81	7	operation	operation	NOUN
fcis-15107	81	8	that	that	PRON
fcis-15107	81	9	connects	connect	VERB
fcis-15107	81	10	simple	simple	ADJ
fcis-15107	81	11	and	and	CCONJ
fcis-15107	81	12	effective	effective	ADJ
fcis-15107	81	13	deep	deep	ADJ
fcis-15107	81	14	and	and	CCONJ
fcis-15107	81	15	shallow	shallow	ADJ
fcis-15107	81	16	information	information	NOUN
fcis-15107	81	17	fusion	fusion	NOUN
fcis-15107	81	18	.	.	PUNCT
fcis-15107	82	1	in	in	ADP
fcis-15107	82	2	sc	sc	PROPN
fcis-15107	82	3	unext	unext	NOUN
fcis-15107	82	4	;	;	PUNCT
fcis-15107	82	5	jump	jump	NOUN
fcis-15107	82	6	link	link	NOUN
fcis-15107	82	7	takes	take	VERB
fcis-15107	82	8	the	the	DET
fcis-15107	82	9	first	first	ADJ
fcis-15107	82	10	layer	layer	NOUN
fcis-15107	82	11	as	as	ADP
fcis-15107	82	12	an	an	DET
fcis-15107	82	13	example	example	NOUN
fcis-15107	82	14	:	:	PUNCT
fcis-15107	82	15	2	2	NUM
fcis-15107	82	16	,	,	PUNCT
fcis-15107	82	17	⊗	⊗	PROPN
fcis-15107	82	18	(	(	PUNCT
fcis-15107	82	19	3	3	NUM
fcis-15107	82	20	)	)	PUNCT
fcis-15107	82	21	z3	z3	NOUN
fcis-15107	82	22	feature	feature	NOUN
fcis-15107	82	23	information	information	NOUN
fcis-15107	82	24	fed	feed	VERB
fcis-15107	82	25	back	back	ADV
fcis-15107	82	26	by	by	ADP
fcis-15107	82	27	the	the	DET
fcis-15107	82	28	jump	jump	NOUN
fcis-15107	82	29	link	link	NOUN
fcis-15107	82	30	is	be	AUX
fcis-15107	82	31	fused	fuse	VERB
fcis-15107	82	32	with	with	ADP
fcis-15107	82	33	the	the	DET
fcis-15107	82	34	z4	z4	PROPN
fcis-15107	82	35	advanced	advanced	ADJ
fcis-15107	82	36	semantic	semantic	ADJ
fcis-15107	82	37	features	feature	NOUN
fcis-15107	82	38	obtained	obtain	VERB
fcis-15107	82	39	by	by	ADP
fcis-15107	82	40	the	the	DET
fcis-15107	82	41	convolution	convolution	NOUN
fcis-15107	82	42	operation	operation	NOUN
fcis-15107	82	43	and	and	CCONJ
fcis-15107	82	44	the	the	DET
fcis-15107	82	45	upsampling	upsample	VERB
fcis-15107	82	46	operation	operation	NOUN
fcis-15107	82	47	,	,	PUNCT
fcis-15107	82	48	and	and	CCONJ
fcis-15107	82	49	then	then	ADV
fcis-15107	82	50	the	the	DET
fcis-15107	82	51	upsampling	upsampling	NOUN
fcis-15107	82	52	operation	operation	NOUN
fcis-15107	82	53	is	be	AUX
fcis-15107	82	54	performed	perform	VERB
fcis-15107	82	55	.	.	PUNCT
fcis-15107	83	1	3.4	3.4	NUM
fcis-15107	83	2	.	.	PUNCT
fcis-15107	83	3	pfm	pfm	NOUN
fcis-15107	83	4	pyramid	pyramid	NOUN
fcis-15107	83	5	feature	feature	NOUN
fcis-15107	83	6	fusion	fusion	NOUN
fcis-15107	83	7	module	module	NOUN
fcis-15107	83	8	in	in	ADP
fcis-15107	83	9	order	order	NOUN
fcis-15107	83	10	to	to	PART
fcis-15107	83	11	make	make	VERB
fcis-15107	83	12	the	the	DET
fcis-15107	83	13	network	network	NOUN
fcis-15107	83	14	capable	capable	ADJ
fcis-15107	83	15	of	of	ADP
fcis-15107	83	16	multi	multi	ADJ
fcis-15107	83	17	-	-	ADJ
fcis-15107	83	18	scale	scale	ADJ
fcis-15107	83	19	detection	detection	NOUN
fcis-15107	84	1	,	,	PUNCT
fcis-15107	84	2	the	the	DET
fcis-15107	84	3	article	article	NOUN
fcis-15107	84	4	uses	use	VERB
fcis-15107	84	5	deconvolution	deconvolution	NOUN
fcis-15107	84	6	to	to	PART
fcis-15107	84	7	expand	expand	VERB
fcis-15107	84	8	feature	feature	NOUN
fcis-15107	84	9	layers	layer	NOUN
fcis-15107	84	10	at	at	ADP
fcis-15107	84	11	different	different	ADJ
fcis-15107	84	12	levels	level	NOUN
fcis-15107	84	13	to	to	ADP
fcis-15107	84	14	the	the	DET
fcis-15107	84	15	same	same	ADJ
fcis-15107	84	16	size	size	NOUN
fcis-15107	84	17	,	,	PUNCT
fcis-15107	84	18	and	and	CCONJ
fcis-15107	84	19	then	then	ADV
fcis-15107	84	20	adds	add	VERB
fcis-15107	84	21	them	they	PRON
fcis-15107	84	22	at	at	ADP
fcis-15107	84	23	the	the	DET
fcis-15107	84	24	element	element	ADJ
fcis-15107	84	25	level	level	NOUN
fcis-15107	84	26	.	.	PUNCT
fcis-15107	85	1	the	the	DET
fcis-15107	85	2	fused	fuse	VERB
fcis-15107	85	3	feature	feature	NOUN
fcis-15107	85	4	layer	layer	NOUN
fcis-15107	85	5	has	have	VERB
fcis-15107	85	6	richer	rich	ADJ
fcis-15107	85	7	multiscale	multiscale	ADJ
fcis-15107	85	8	features	feature	NOUN
fcis-15107	85	9	.	.	PUNCT
fcis-15107	86	1	3.5	3.5	NUM
fcis-15107	86	2	.	.	PUNCT
fcis-15107	87	1	joint	joint	ADJ
fcis-15107	87	2	loss	loss	NOUN
fcis-15107	87	3	function	function	VERB
fcis-15107	87	4	the	the	DET
fcis-15107	87	5	joint	joint	ADJ
fcis-15107	87	6	loss	loss	NOUN
fcis-15107	87	7	function	function	NOUN
fcis-15107	87	8	is	be	AUX
fcis-15107	87	9	composed	compose	VERB
fcis-15107	87	10	of	of	ADP
fcis-15107	87	11	a	a	DET
fcis-15107	87	12	mean	mean	ADJ
fcis-15107	87	13	square	square	ADJ
fcis-15107	87	14	error	error	NOUN
fcis-15107	87	15	loss	loss	NOUN
fcis-15107	87	16	function	function	NOUN
fcis-15107	87	17	and	and	CCONJ
fcis-15107	87	18	an	an	DET
fcis-15107	87	19	edge	edge	NOUN
fcis-15107	87	20	loss	loss	NOUN
fcis-15107	87	21	function	function	NOUN
fcis-15107	87	22	.	.	PUNCT
fcis-15107	88	1	the	the	DET
fcis-15107	88	2	complex	complex	ADJ
fcis-15107	88	3	,	,	PUNCT
fcis-15107	88	4	diverse	diverse	ADJ
fcis-15107	88	5	and	and	CCONJ
fcis-15107	88	6	unclear	unclear	ADJ
fcis-15107	88	7	edge	edge	NOUN
fcis-15107	88	8	contours	contours	NOUN
fcis-15107	88	9	of	of	ADP
fcis-15107	88	10	lesions	lesion	NOUN
fcis-15107	88	11	have	have	VERB
fcis-15107	88	12	a	a	DET
fcis-15107	88	13	great	great	ADJ
fcis-15107	88	14	impact	impact	NOUN
fcis-15107	88	15	on	on	ADP
fcis-15107	88	16	the	the	DET
fcis-15107	88	17	segmentation	segmentation	NOUN
fcis-15107	88	18	effect	effect	NOUN
fcis-15107	88	19	of	of	ADP
fcis-15107	88	20	the	the	DET
fcis-15107	88	21	lesion	lesion	NOUN
fcis-15107	88	22	area	area	NOUN
fcis-15107	88	23	.	.	PUNCT
fcis-15107	89	1	therefore	therefore	ADV
fcis-15107	89	2	,	,	PUNCT
fcis-15107	89	3	increasing	increase	VERB
fcis-15107	89	4	the	the	DET
fcis-15107	89	5	weight	weight	NOUN
fcis-15107	89	6	of	of	ADP
fcis-15107	89	7	edge	edge	NOUN
fcis-15107	89	8	feature	feature	NOUN
fcis-15107	89	9	information	information	NOUN
fcis-15107	89	10	samples	sample	NOUN
fcis-15107	89	11	is	be	AUX
fcis-15107	89	12	of	of	ADP
fcis-15107	89	13	great	great	ADJ
fcis-15107	89	14	significance	significance	NOUN
fcis-15107	89	15	to	to	ADP
fcis-15107	89	16	the	the	DET
fcis-15107	89	17	segmentation	segmentation	NOUN
fcis-15107	89	18	effect	effect	NOUN
fcis-15107	89	19	,	,	PUNCT
fcis-15107	89	20	for	for	ADP
fcis-15107	89	21	this	this	PRON
fcis-15107	89	22	we	we	PRON
fcis-15107	89	23	use	use	VERB
fcis-15107	89	24	the	the	DET
fcis-15107	89	25	edge	edge	NOUN
fcis-15107	89	26	loss	loss	NOUN
fcis-15107	89	27	function	function	NOUN
fcis-15107	89	28	.	.	PUNCT
fcis-15107	90	1	the	the	DET
fcis-15107	90	2	joint	joint	ADJ
fcis-15107	90	3	loss	loss	NOUN
fcis-15107	90	4	function	function	NOUN
fcis-15107	90	5	is	be	AUX
fcis-15107	90	6	defined	define	VERB
fcis-15107	90	7	as	as	ADP
fcis-15107	90	8	:	:	PUNCT
fcis-15107	90	9	mean	mean	VERB
fcis-15107	90	10	squared	square	VERB
fcis-15107	90	11	error	error	NOUN
fcis-15107	90	12	loss	loss	NOUN
fcis-15107	90	13	function	function	NOUN
fcis-15107	90	14	(	(	PUNCT
fcis-15107	90	15	mse	mse	NOUN
fcis-15107	90	16	):	):	PUNCT
fcis-15107	90	17	l	l	PROPN
fcis-15107	90	18	∑	∑	PUNCT
fcis-15107	90	19	y	y	PROPN
fcis-15107	90	20	f	f	PROPN
fcis-15107	90	21	x	x	X
fcis-15107	90	22	(	(	PUNCT
fcis-15107	90	23	4	4	NUM
fcis-15107	90	24	)	)	PUNCT
fcis-15107	90	25	edge	edge	NOUN
fcis-15107	90	26	feature	feature	NOUN
fcis-15107	90	27	loss	loss	NOUN
fcis-15107	90	28	function	function	NOUN
fcis-15107	90	29	edge	edge	NOUN
fcis-15107	90	30	loss	loss	NOUN
fcis-15107	90	31	:	:	PUNCT
fcis-15107	90	32	∑	∑	PUNCT
fcis-15107	90	33	∑	∑	INTJ
fcis-15107	90	34	,	,	PUNCT
fcis-15107	90	35	⋅	⋅	PROPN
fcis-15107	90	36	,	,	PUNCT
fcis-15107	90	37	,	,	PUNCT
fcis-15107	90	38	(	(	PUNCT
fcis-15107	90	39	5	5	X
fcis-15107	90	40	)	)	PUNCT
fcis-15107	90	41	joint	joint	ADJ
fcis-15107	90	42	loss	loss	NOUN
fcis-15107	90	43	function	function	NOUN
fcis-15107	90	44	loss	loss	NOUN
fcis-15107	90	45	(	(	PUNCT
fcis-15107	90	46	total	total	NOUN
fcis-15107	90	47	)	)	PUNCT
fcis-15107	90	48	:	:	PUNCT
fcis-15107	90	49	(	(	PUNCT
fcis-15107	90	50	6	6	X
fcis-15107	90	51	)	)	PUNCT
fcis-15107	90	52	increasing	increase	VERB
fcis-15107	90	53	the	the	DET
fcis-15107	90	54	edge	edge	NOUN
fcis-15107	90	55	feature	feature	NOUN
fcis-15107	90	56	semantics	semantic	NOUN
fcis-15107	90	57	in	in	ADP
fcis-15107	90	58	the	the	DET
fcis-15107	90	59	sample	sample	NOUN
fcis-15107	90	60	weight	weight	NOUN
fcis-15107	90	61	in	in	ADP
fcis-15107	90	62	the	the	DET
fcis-15107	90	63	joint	joint	ADJ
fcis-15107	90	64	loss	loss	NOUN
fcis-15107	90	65	function	function	NOUN
fcis-15107	90	66	can	can	AUX
fcis-15107	90	67	better	well	ADV
fcis-15107	90	68	optimize	optimize	VERB
fcis-15107	90	69	edge	edge	NOUN
fcis-15107	90	70	information	information	NOUN
fcis-15107	90	71	.	.	PUNCT
fcis-15107	91	1	4	4	X
fcis-15107	91	2	.	.	X
fcis-15107	91	3	experimental	experimental	ADJ
fcis-15107	91	4	settings	setting	NOUN
fcis-15107	91	5	4.1	4.1	NUM
fcis-15107	91	6	.	.	PUNCT
fcis-15107	92	1	dataset	dataset	VERB
fcis-15107	92	2	in	in	ADP
fcis-15107	92	3	the	the	DET
fcis-15107	92	4	experiment	experiment	NOUN
fcis-15107	92	5	.	.	PUNCT
fcis-15107	93	1	the	the	DET
fcis-15107	93	2	nih	nih	PROPN
fcis-15107	93	3	chest	chest	PROPN
fcis-15107	93	4	x	x	PROPN
fcis-15107	93	5	-	-	NOUN
fcis-15107	93	6	ray	ray	NOUN
fcis-15107	93	7	dataset	dataset	NOUN
fcis-15107	93	8	contains	contain	VERB
fcis-15107	93	9	112,120	112,120	NUM
fcis-15107	93	10	disease	disease	NOUN
fcis-15107	93	11	-	-	PUNCT
fcis-15107	93	12	labeled	label	VERB
fcis-15107	93	13	x	x	ADJ
fcis-15107	93	14	-	-	NOUN
fcis-15107	93	15	ray	ray	NOUN
fcis-15107	93	16	images	image	NOUN
fcis-15107	93	17	from	from	ADP
fcis-15107	93	18	30,805	30,805	NUM
fcis-15107	93	19	unique	unique	ADJ
fcis-15107	93	20	patients	patient	NOUN
fcis-15107	93	21	.	.	PUNCT
fcis-15107	94	1	there	there	PRON
fcis-15107	94	2	are	be	VERB
fcis-15107	94	3	15	15	NUM
fcis-15107	94	4	categories	category	NOUN
fcis-15107	94	5	(	(	PUNCT
fcis-15107	94	6	14	14	NUM
fcis-15107	94	7	diseases	disease	NOUN
fcis-15107	94	8	and	and	CCONJ
fcis-15107	94	9	"	"	PUNCT
fcis-15107	94	10	none	none	NOUN
fcis-15107	94	11	found	find	VERB
fcis-15107	94	12	"	"	PUNCT
fcis-15107	94	13	)	)	PUNCT
fcis-15107	94	14	.	.	PUNCT
fcis-15107	95	1	images	image	NOUN
fcis-15107	95	2	can	can	AUX
fcis-15107	95	3	be	be	AUX
fcis-15107	95	4	grouped	group	VERB
fcis-15107	95	5	into	into	ADP
fcis-15107	95	6	"	"	PUNCT
fcis-15107	95	7	no	no	DET
fcis-15107	95	8	findings	finding	NOUN
fcis-15107	95	9	"	"	PUNCT
fcis-15107	95	10	or	or	CCONJ
fcis-15107	95	11	one	one	NUM
fcis-15107	95	12	or	or	CCONJ
fcis-15107	95	13	more	more	ADJ
fcis-15107	95	14	disease	disease	NOUN
fcis-15107	95	15	categories	category	NOUN
fcis-15107	95	16	,	,	PUNCT
fcis-15107	95	17	showing	show	VERB
fcis-15107	95	18	14	14	NUM
fcis-15107	95	19	common	common	ADJ
fcis-15107	95	20	chest	chest	NOUN
fcis-15107	95	21	pathologies	pathology	NOUN
fcis-15107	95	22	.	.	PUNCT
fcis-15107	96	1	the	the	DET
fcis-15107	96	2	nih	nih	PROPN
fcis-15107	96	3	chest	chest	PROPN
fcis-15107	96	4	x	x	PROPN
fcis-15107	96	5	-	-	NOUN
fcis-15107	96	6	ray	ray	NOUN
fcis-15107	96	7	dataset	dataset	NOUN
fcis-15107	96	8	itself	itself	PRON
fcis-15107	96	9	does	do	AUX
fcis-15107	96	10	not	not	PART
fcis-15107	96	11	contain	contain	VERB
fcis-15107	96	12	lung	lung	NOUN
fcis-15107	96	13	field	field	NOUN
fcis-15107	96	14	labels	label	NOUN
fcis-15107	96	15	.	.	PUNCT
fcis-15107	97	1	we	we	PRON
fcis-15107	97	2	randomly	randomly	ADV
fcis-15107	97	3	selected	select	VERB
fcis-15107	97	4	2785	2785	NUM
fcis-15107	97	5	samples	sample	NOUN
fcis-15107	97	6	,	,	PUNCT
fcis-15107	97	7	and	and	CCONJ
fcis-15107	97	8	doctors	doctor	NOUN
fcis-15107	97	9	marked	mark	VERB
fcis-15107	97	10	the	the	DET
fcis-15107	97	11	lung	lung	NOUN
fcis-15107	97	12	fields	field	NOUN
fcis-15107	97	13	of	of	ADP
fcis-15107	97	14	the	the	DET
fcis-15107	97	15	images	image	NOUN
fcis-15107	97	16	.	.	PUNCT
fcis-15107	98	1	we	we	PRON
fcis-15107	98	2	call	call	VERB
fcis-15107	98	3	this	this	DET
fcis-15107	98	4	new	new	ADJ
fcis-15107	98	5	dataset	dataset	NOUN
fcis-15107	98	6	haut	haut	PROPN
fcis-15107	98	7	.	.	PUNCT
fcis-15107	99	1	the	the	DET
fcis-15107	99	2	tehaut	tehaut	PROPN
fcis-15107	99	3	dataset	dataset	PROPN
fcis-15107	99	4	contains	contain	VERB
fcis-15107	99	5	some	some	PRON
fcis-15107	99	6	severely	severely	ADV
fcis-15107	99	7	blurred	blurred	ADJ
fcis-15107	99	8	,	,	PUNCT
fcis-15107	99	9	occluded	occluded	ADJ
fcis-15107	99	10	,	,	PUNCT
fcis-15107	99	11	and	and	CCONJ
fcis-15107	99	12	distorted	distort	VERB
fcis-15107	99	13	chest	chest	NOUN
fcis-15107	99	14	xrays	xray	NOUN
fcis-15107	99	15	.	.	PUNCT
fcis-15107	100	1	the	the	DET
fcis-15107	100	2	haut	haut	PROPN
fcis-15107	100	3	data	data	PROPN
fcis-15107	100	4	set	set	NOUN
fcis-15107	100	5	contains	contain	VERB
fcis-15107	100	6	1647	1647	NUM
fcis-15107	100	7	normal	normal	ADJ
fcis-15107	100	8	people	people	NOUN
fcis-15107	100	9	and	and	CCONJ
fcis-15107	100	10	1138	1138	NUM
fcis-15107	100	11	cxr	cxr	NOUN
fcis-15107	100	12	lung	lung	NOUN
fcis-15107	100	13	field	field	NOUN
fcis-15107	100	14	mask	mask	NOUN
fcis-15107	100	15	patients	patient	NOUN
fcis-15107	100	16	,	,	PUNCT
fcis-15107	100	17	including	include	VERB
fcis-15107	100	18	193	193	NUM
fcis-15107	100	19	cases	case	NOUN
fcis-15107	100	20	of	of	ADP
fcis-15107	100	21	infiltration	infiltration	NOUN
fcis-15107	100	22	,	,	PUNCT
fcis-15107	100	23	111	111	NUM
fcis-15107	100	24	cases	case	NOUN
fcis-15107	100	25	of	of	ADP
fcis-15107	100	26	atelectasis	atelectasis	NOUN
fcis-15107	100	27	,	,	PUNCT
fcis-15107	100	28	78	78	NUM
fcis-15107	100	29	cases	case	NOUN
fcis-15107	100	30	of	of	ADP
fcis-15107	100	31	effusion	effusion	NOUN
fcis-15107	100	32	,	,	PUNCT
fcis-15107	100	33	65	65	NUM
fcis-15107	100	34	cases	case	NOUN
fcis-15107	100	35	of	of	ADP
fcis-15107	100	36	nodules	nodule	NOUN
fcis-15107	100	37	,	,	PUNCT
fcis-15107	100	38	54	54	NUM
fcis-15107	100	39	cases	case	NOUN
fcis-15107	100	40	of	of	ADP
fcis-15107	100	41	masses	masse	NOUN
fcis-15107	100	42	,	,	PUNCT
fcis-15107	100	43	43	43	NUM
fcis-15107	100	44	cases	case	NOUN
fcis-15107	100	45	of	of	ADP
fcis-15107	100	46	pneumothorax	pneumothorax	NOUN
fcis-15107	100	47	,	,	PUNCT
fcis-15107	100	48	and	and	CCONJ
fcis-15107	100	49	heart	heart	NOUN
fcis-15107	100	50	disease	disease	NOUN
fcis-15107	100	51	.	.	PUNCT
fcis-15107	101	1	there	there	PRON
fcis-15107	101	2	were	be	VERB
fcis-15107	101	3	37	37	NUM
fcis-15107	101	4	cases	case	NOUN
fcis-15107	101	5	of	of	ADP
fcis-15107	101	6	enlargement	enlargement	NOUN
fcis-15107	101	7	,	,	PUNCT
fcis-15107	101	8	37	37	NUM
fcis-15107	101	9	cases	case	NOUN
fcis-15107	101	10	of	of	ADP
fcis-15107	101	11	pleural	pleural	ADJ
fcis-15107	101	12	thickening	thickening	NOUN
fcis-15107	101	13	,	,	PUNCT
fcis-15107	101	14	34	34	NUM
fcis-15107	101	15	cases	case	NOUN
fcis-15107	101	16	of	of	ADP
fcis-15107	101	17	pleural	pleural	ADJ
fcis-15107	101	18	thickening	thickening	NOUN
fcis-15107	101	19	with	with	ADP
fcis-15107	101	20	fibrosis	fibrosis	NOUN
fcis-15107	101	21	,	,	PUNCT
fcis-15107	101	22	25	25	NUM
fcis-15107	101	23	with	with	ADP
fcis-15107	101	24	consolidation	consolidation	NOUN
fcis-15107	101	25	,	,	PUNCT
fcis-15107	101	26	21	21	NUM
fcis-15107	101	27	with	with	ADP
fcis-15107	101	28	emphysema	emphysema	ADJ
fcis-15107	101	29	,	,	PUNCT
fcis-15107	101	30	11	11	NUM
fcis-15107	101	31	with	with	ADP
fcis-15107	101	32	edema	edema	PROPN
fcis-15107	101	33	,	,	PUNCT
fcis-15107	101	34	10	10	NUM
fcis-15107	101	35	with	with	ADP
fcis-15107	101	36	pneumonia	pneumonia	NOUN
fcis-15107	101	37	,	,	PUNCT
fcis-15107	101	38	2	2	NUM
fcis-15107	101	39	417	417	NUM
fcis-15107	101	40	had	have	VERB
fcis-15107	101	41	a	a	DET
fcis-15107	101	42	hernia	hernia	NOUN
fcis-15107	101	43	and	and	CCONJ
fcis-15107	101	44	417	417	NUM
fcis-15107	101	45	suffered	suffer	VERB
fcis-15107	101	46	from	from	ADP
fcis-15107	101	47	multiple	multiple	ADJ
fcis-15107	101	48	medical	medical	ADJ
fcis-15107	101	49	conditions	condition	NOUN
fcis-15107	101	50	(	(	PUNCT
fcis-15107	101	51	including	include	VERB
fcis-15107	101	52	any	any	DET
fcis-15107	101	53	two	two	NUM
fcis-15107	101	54	or	or	CCONJ
fcis-15107	101	55	more	more	ADJ
fcis-15107	101	56	of	of	ADP
fcis-15107	101	57	the	the	DET
fcis-15107	101	58	above	above	ADJ
fcis-15107	101	59	)	)	PUNCT
fcis-15107	101	60	.	.	PUNCT
fcis-15107	102	1	to	to	PART
fcis-15107	102	2	use	use	VERB
fcis-15107	102	3	efcientnet	efcientnet	NOUN
fcis-15107	102	4	-	-	PUNCT
fcis-15107	102	5	b4	b4	NOUN
fcis-15107	102	6	,	,	PUNCT
fcis-15107	102	7	as	as	ADP
fcis-15107	102	8	a	a	DET
fcis-15107	102	9	preprocessing	preprocessing	NOUN
fcis-15107	102	10	step	step	NOUN
fcis-15107	102	11	,	,	PUNCT
fcis-15107	102	12	the	the	DET
fcis-15107	102	13	image	image	NOUN
fcis-15107	102	14	is	be	AUX
fcis-15107	102	15	downsized	downsize	VERB
fcis-15107	102	16	to	to	ADP
fcis-15107	102	17	256×256	256×256	NUM
fcis-15107	102	18	pixels	pixel	NOUN
fcis-15107	102	19	.	.	PUNCT
fcis-15107	103	1	to	to	PART
fcis-15107	103	2	bring	bring	VERB
fcis-15107	103	3	our	our	PRON
fcis-15107	103	4	experiments	experiment	NOUN
fcis-15107	103	5	as	as	ADV
fcis-15107	103	6	close	close	ADJ
fcis-15107	103	7	as	as	ADP
fcis-15107	103	8	possible	possible	ADJ
fcis-15107	103	9	to	to	ADP
fcis-15107	103	10	point	point	NOUN
fcis-15107	103	11	-	-	PUNCT
fcis-15107	103	12	ofcare	ofcare	NOUN
fcis-15107	103	13	imaging	imaging	NOUN
fcis-15107	103	14	,	,	PUNCT
fcis-15107	103	15	we	we	PRON
fcis-15107	103	16	chose	choose	VERB
fcis-15107	103	17	the	the	DET
fcis-15107	103	18	international	international	ADJ
fcis-15107	103	19	skin	skin	NOUN
fcis-15107	103	20	imaging	imaging	NOUN
fcis-15107	103	21	collaboration	collaboration	NOUN
fcis-15107	103	22	(	(	PUNCT
fcis-15107	103	23	isic	isic	PROPN
fcis-15107	103	24	2018	2018	NUM
fcis-15107	103	25	)	)	PUNCT
fcis-15107	103	26	to	to	PART
fcis-15107	103	27	benchmark	benchmark	VERB
fcis-15107	103	28	our	our	PRON
fcis-15107	103	29	results	result	NOUN
fcis-15107	103	30	.	.	PUNCT
fcis-15107	104	1	the	the	DET
fcis-15107	104	2	isic	isic	PROPN
fcis-15107	104	3	dataset	dataset	PROPN
fcis-15107	104	4	contains	contain	VERB
fcis-15107	104	5	camera	camera	NOUN
fcis-15107	104	6	-	-	PUNCT
fcis-15107	104	7	acquired	acquire	VERB
fcis-15107	104	8	skin	skin	NOUN
fcis-15107	104	9	images	image	NOUN
fcis-15107	104	10	and	and	CCONJ
fcis-15107	104	11	corresponding	correspond	VERB
fcis-15107	104	12	skin	skin	NOUN
fcis-15107	104	13	lesion	lesion	NOUN
fcis-15107	104	14	region	region	NOUN
fcis-15107	104	15	segmentation	segmentation	NOUN
fcis-15107	104	16	maps	map	NOUN
fcis-15107	104	17	.	.	PUNCT
fcis-15107	105	1	the	the	DET
fcis-15107	105	2	isic	isic	PROPN
fcis-15107	105	3	2018	2018	NUM
fcis-15107	105	4	dataset	dataset	VERB
fcis-15107	105	5	consists	consist	NOUN
fcis-15107	105	6	of	of	ADP
fcis-15107	105	7	2594	2594	NUM
fcis-15107	105	8	images	image	NOUN
fcis-15107	105	9	.	.	PUNCT
fcis-15107	106	1	we	we	PRON
fcis-15107	106	2	resized	resize	VERB
fcis-15107	106	3	all	all	DET
fcis-15107	106	4	images	image	NOUN
fcis-15107	106	5	to	to	ADP
fcis-15107	106	6	a	a	DET
fcis-15107	106	7	resolution	resolution	NOUN
fcis-15107	106	8	of	of	ADP
fcis-15107	106	9	512	512	NUM
fcis-15107	106	10	×	×	NOUN
fcis-15107	106	11	512	512	NUM
fcis-15107	106	12	.	.	PUNCT
fcis-15107	107	1	4.2	4.2	NUM
fcis-15107	107	2	.	.	PUNCT
fcis-15107	108	1	experimental	experimental	ADJ
fcis-15107	108	2	settings	setting	NOUN
fcis-15107	108	3	we	we	PRON
fcis-15107	108	4	use	use	VERB
fcis-15107	108	5	the	the	DET
fcis-15107	108	6	adam	adam	PROPN
fcis-15107	108	7	optimizer	optimizer	NOUN
fcis-15107	108	8	with	with	ADP
fcis-15107	108	9	a	a	DET
fcis-15107	108	10	learning	learn	VERB
fcis-15107	108	11	rate	rate	NOUN
fcis-15107	108	12	of	of	ADP
fcis-15107	108	13	0.0001	0.0001	NUM
fcis-15107	108	14	and	and	CCONJ
fcis-15107	108	15	a	a	DET
fcis-15107	108	16	momentum	momentum	NOUN
fcis-15107	108	17	of	of	ADP
fcis-15107	108	18	0.9	0.9	NUM
fcis-15107	108	19	.	.	PUNCT
fcis-15107	109	1	we	we	PRON
fcis-15107	109	2	also	also	ADV
fcis-15107	109	3	used	use	VERB
fcis-15107	109	4	a	a	DET
fcis-15107	109	5	cosine	cosine	NOUN
fcis-15107	109	6	annealing	anneal	VERB
fcis-15107	109	7	learning	learn	VERB
fcis-15107	109	8	rate	rate	NOUN
fcis-15107	109	9	scheduler	scheduler	NOUN
fcis-15107	109	10	with	with	ADP
fcis-15107	109	11	a	a	DET
fcis-15107	109	12	minimum	minimum	ADJ
fcis-15107	109	13	learning	learning	NOUN
fcis-15107	109	14	rate	rate	NOUN
fcis-15107	109	15	up	up	ADP
fcis-15107	109	16	to	to	ADP
fcis-15107	109	17	0.00001	0.00001	NUM
fcis-15107	109	18	.	.	PUNCT
fcis-15107	110	1	the	the	DET
fcis-15107	110	2	batch	batch	NOUN
fcis-15107	110	3	size	size	NOUN
fcis-15107	110	4	is	be	AUX
fcis-15107	110	5	set	set	VERB
fcis-15107	110	6	to	to	ADP
fcis-15107	110	7	8	8	NUM
fcis-15107	110	8	.	.	PUNCT
fcis-15107	111	1	we	we	PRON
fcis-15107	111	2	trained	train	VERB
fcis-15107	111	3	unext	unext	ADV
fcis-15107	111	4	for	for	ADP
fcis-15107	111	5	a	a	DET
fcis-15107	111	6	total	total	NOUN
fcis-15107	111	7	of	of	ADP
fcis-15107	111	8	400	400	NUM
fcis-15107	111	9	epochs	epoch	NOUN
fcis-15107	111	10	.	.	PUNCT
fcis-15107	112	1	we	we	PRON
fcis-15107	112	2	perform	perform	VERB
fcis-15107	112	3	an	an	DET
fcis-15107	112	4	80	80	NUM
fcis-15107	112	5	-	-	SYM
fcis-15107	112	6	20	20	NUM
fcis-15107	112	7	random	random	ADJ
fcis-15107	112	8	split	split	NOUN
fcis-15107	112	9	three	three	NUM
fcis-15107	112	10	times	time	NOUN
fcis-15107	112	11	on	on	ADP
fcis-15107	112	12	the	the	DET
fcis-15107	112	13	dataset	dataset	NOUN
fcis-15107	112	14	and	and	CCONJ
fcis-15107	112	15	report	report	VERB
fcis-15107	112	16	the	the	DET
fcis-15107	112	17	mean	mean	NOUN
fcis-15107	112	18	and	and	CCONJ
fcis-15107	112	19	variance	variance	NOUN
fcis-15107	112	20	.	.	PUNCT
fcis-15107	113	1	evaluation	evaluation	NOUN
fcis-15107	113	2	indicators	indicator	NOUN
fcis-15107	113	3	,	,	PUNCT
fcis-15107	113	4	we	we	PRON
fcis-15107	113	5	use	use	VERB
fcis-15107	113	6	iou	iou	NOUN
fcis-15107	113	7	,	,	PUNCT
fcis-15107	113	8	dice	dice	NOUN
fcis-15107	113	9	segmentation	segmentation	NOUN
fcis-15107	113	10	index	index	NOUN
fcis-15107	113	11	to	to	PART
fcis-15107	113	12	quantify	quantify	VERB
fcis-15107	113	13	the	the	DET
fcis-15107	113	14	segmentation	segmentation	NOUN
fcis-15107	113	15	ability	ability	NOUN
fcis-15107	113	16	of	of	ADP
fcis-15107	113	17	sc	sc	PROPN
fcis-15107	113	18	-	-	PROPN
fcis-15107	113	19	unext	unext	PROPN
fcis-15107	113	20	,	,	PUNCT
fcis-15107	113	21	dice	dice	NOUN
fcis-15107	113	22	similarity	similarity	NOUN
fcis-15107	113	23	coefficient	coefficient	NOUN
fcis-15107	113	24	(	(	PUNCT
fcis-15107	113	25	dsc	dsc	NOUN
fcis-15107	113	26	)	)	PUNCT
fcis-15107	113	27	,	,	PUNCT
fcis-15107	113	28	dice	dice	NOUN
fcis-15107	113	29	coefficient	coefficient	NOUN
fcis-15107	113	30	is	be	AUX
fcis-15107	113	31	a	a	DET
fcis-15107	113	32	set	set	ADJ
fcis-15107	113	33	similarity	similarity	NOUN
fcis-15107	113	34	measure	measure	NOUN
fcis-15107	113	35	,	,	PUNCT
fcis-15107	114	1	i	i	PRON
fcis-15107	114	2	o	o	VERB
fcis-15107	114	3	u	u	NOUN
fcis-15107	114	4	is	be	AUX
fcis-15107	114	5	used	use	VERB
fcis-15107	114	6	to	to	PART
fcis-15107	114	7	evaluate	evaluate	VERB
fcis-15107	114	8	the	the	DET
fcis-15107	114	9	degree	degree	NOUN
fcis-15107	114	10	of	of	ADP
fcis-15107	114	11	similarity	similarity	NOUN
fcis-15107	114	12	between	between	ADP
fcis-15107	114	13	predictions	prediction	NOUN
fcis-15107	114	14	and	and	CCONJ
fcis-15107	114	15	true	true	ADJ
fcis-15107	114	16	values	value	NOUN
fcis-15107	114	17	.	.	PUNCT
fcis-15107	115	1	semantic	semantic	ADJ
fcis-15107	115	2	segmentation	segmentation	NOUN
fcis-15107	115	3	can	can	AUX
fcis-15107	115	4	be	be	AUX
fcis-15107	115	5	viewed	view	VERB
fcis-15107	115	6	as	as	ADP
fcis-15107	115	7	pixel	pixel	ADJ
fcis-15107	115	8	-	-	PUNCT
fcis-15107	115	9	level	level	NOUN
fcis-15107	115	10	classification	classification	NOUN
fcis-15107	115	11	.	.	PUNCT
fcis-15107	116	1	true	true	ADJ
fcis-15107	116	2	positive	positive	ADJ
fcis-15107	116	3	(	(	PUNCT
fcis-15107	116	4	tp	tp	NOUN
fcis-15107	116	5	):	):	PUNCT
fcis-15107	116	6	the	the	DET
fcis-15107	116	7	model	model	NOUN
fcis-15107	116	8	prediction	prediction	NOUN
fcis-15107	116	9	is	be	AUX
fcis-15107	116	10	a	a	DET
fcis-15107	116	11	positive	positive	ADJ
fcis-15107	116	12	example	example	NOUN
fcis-15107	116	13	,	,	PUNCT
fcis-15107	116	14	that	that	ADV
fcis-15107	116	15	is	is	ADV
fcis-15107	116	16	,	,	PUNCT
fcis-15107	116	17	a	a	DET
fcis-15107	116	18	positive	positive	ADJ
fcis-15107	116	19	example	example	NOUN
fcis-15107	116	20	.	.	PUNCT
fcis-15107	117	1	false	false	ADJ
fcis-15107	117	2	positive	positive	ADJ
fcis-15107	117	3	(	(	PUNCT
fcis-15107	117	4	fp	fp	X
fcis-15107	117	5	):	):	PUNCT
fcis-15107	117	6	the	the	DET
fcis-15107	117	7	model	model	NOUN
fcis-15107	117	8	predicts	predict	VERB
fcis-15107	117	9	a	a	DET
fcis-15107	117	10	positive	positive	ADJ
fcis-15107	117	11	example	example	NOUN
fcis-15107	117	12	,	,	PUNCT
fcis-15107	117	13	but	but	CCONJ
fcis-15107	117	14	it	it	PRON
fcis-15107	117	15	is	be	AUX
fcis-15107	117	16	a	a	DET
fcis-15107	117	17	negative	negative	ADJ
fcis-15107	117	18	example	example	NOUN
fcis-15107	117	19	.	.	PUNCT
fcis-15107	118	1	false	false	ADJ
fcis-15107	118	2	negative	negative	ADJ
fcis-15107	118	3	(	(	PUNCT
fcis-15107	118	4	fn	fn	X
fcis-15107	118	5	):	):	PUNCT
fcis-15107	118	6	the	the	DET
fcis-15107	118	7	model	model	NOUN
fcis-15107	118	8	prediction	prediction	NOUN
fcis-15107	118	9	is	be	AUX
fcis-15107	118	10	a	a	DET
fcis-15107	118	11	negative	negative	ADJ
fcis-15107	118	12	example	example	NOUN
fcis-15107	118	13	,	,	PUNCT
fcis-15107	118	14	but	but	CCONJ
fcis-15107	118	15	it	it	PRON
fcis-15107	118	16	is	be	AUX
fcis-15107	118	17	a	a	DET
fcis-15107	118	18	positive	positive	ADJ
fcis-15107	118	19	example	example	NOUN
fcis-15107	118	20	.	.	PUNCT
fcis-15107	119	1	true	true	ADJ
fcis-15107	119	2	negative	negative	ADJ
fcis-15107	119	3	(	(	PUNCT
fcis-15107	119	4	tn	tn	NOUN
fcis-15107	119	5	):	):	PUNCT
fcis-15107	119	6	the	the	DET
fcis-15107	119	7	model	model	NOUN
fcis-15107	119	8	prediction	prediction	NOUN
fcis-15107	119	9	is	be	AUX
fcis-15107	119	10	a	a	DET
fcis-15107	119	11	counterexample	counterexample	NOUN
fcis-15107	119	12	,	,	PUNCT
fcis-15107	119	13	it	it	PRON
fcis-15107	119	14	is	be	AUX
fcis-15107	119	15	a	a	DET
fcis-15107	119	16	counterexample	counterexample	NOUN
fcis-15107	119	17	.	.	PUNCT
fcis-15107	120	1	(	(	PUNCT
fcis-15107	120	2	7	7	NUM
fcis-15107	120	3	)	)	PUNCT
fcis-15107	120	4	(	(	PUNCT
fcis-15107	120	5	8)	8)	NUM
fcis-15107	120	6	dice	dice	NOUN
fcis-15107	120	7	is	be	AUX
fcis-15107	120	8	usually	usually	ADV
fcis-15107	120	9	used	use	VERB
fcis-15107	120	10	to	to	PART
fcis-15107	120	11	calculate	calculate	VERB
fcis-15107	120	12	the	the	DET
fcis-15107	120	13	similarity	similarity	NOUN
fcis-15107	120	14	of	of	ADP
fcis-15107	120	15	two	two	NUM
fcis-15107	120	16	samples	sample	NOUN
fcis-15107	120	17	.	.	PUNCT
fcis-15107	121	1	the	the	DET
fcis-15107	121	2	value	value	NOUN
fcis-15107	121	3	range	range	NOUN
fcis-15107	121	4	is	be	AUX
fcis-15107	121	5	0	0	NUM
fcis-15107	121	6	1	1	NUM
fcis-15107	121	7	.	.	PUNCT
fcis-15107	122	1	the	the	DET
fcis-15107	122	2	best	good	ADJ
fcis-15107	122	3	segmentation	segmentation	NOUN
fcis-15107	122	4	result	result	NOUN
fcis-15107	122	5	is	be	AUX
fcis-15107	122	6	1	1	NUM
fcis-15107	122	7	and	and	CCONJ
fcis-15107	122	8	the	the	DET
fcis-15107	122	9	worst	bad	ADJ
fcis-15107	122	10	value	value	NOUN
fcis-15107	122	11	is	be	AUX
fcis-15107	122	12	0	0	NUM
fcis-15107	122	13	.	.	PUNCT
fcis-15107	123	1	i	i	PRON
fcis-15107	123	2	ou	ou	PROPN
fcis-15107	123	3	is	be	AUX
fcis-15107	123	4	calculated	calculate	VERB
fcis-15107	123	5	as	as	ADP
fcis-15107	123	6	the	the	DET
fcis-15107	123	7	ratio	ratio	NOUN
fcis-15107	123	8	of	of	ADP
fcis-15107	123	9	the	the	DET
fcis-15107	123	10	intersection	intersection	NOUN
fcis-15107	123	11	and	and	CCONJ
fcis-15107	123	12	union	union	NOUN
fcis-15107	123	13	of	of	ADP
fcis-15107	123	14	the	the	DET
fcis-15107	123	15	two	two	NUM
fcis-15107	123	16	sets	set	NOUN
fcis-15107	123	17	of	of	ADP
fcis-15107	123	18	real	real	ADJ
fcis-15107	123	19	values	value	NOUN
fcis-15107	123	20	and	and	CCONJ
fcis-15107	123	21	predicted	predict	VERB
fcis-15107	123	22	values	value	NOUN
fcis-15107	123	23	.	.	PUNCT
fcis-15107	124	1	the	the	PRON
fcis-15107	124	2	larger	large	ADJ
fcis-15107	124	3	the	the	DET
fcis-15107	124	4	ratio	ratio	NOUN
fcis-15107	124	5	,	,	PUNCT
fcis-15107	124	6	the	the	PRON
fcis-15107	124	7	higher	high	ADJ
fcis-15107	124	8	the	the	DET
fcis-15107	124	9	similarity	similarity	NOUN
fcis-15107	124	10	between	between	ADP
fcis-15107	124	11	the	the	DET
fcis-15107	124	12	real	real	ADJ
fcis-15107	124	13	value	value	NOUN
fcis-15107	124	14	and	and	CCONJ
fcis-15107	124	15	the	the	DET
fcis-15107	124	16	predicted	predict	VERB
fcis-15107	124	17	value	value	NOUN
fcis-15107	124	18	,	,	PUNCT
fcis-15107	124	19	the	the	PRON
fcis-15107	124	20	better	well	ADJ
fcis-15107	124	21	the	the	DET
fcis-15107	124	22	segmentation	segmentation	NOUN
fcis-15107	124	23	effect	effect	NOUN
fcis-15107	124	24	.	.	PUNCT
fcis-15107	125	1	5	5	X
fcis-15107	125	2	.	.	X
fcis-15107	125	3	experiment	experiment	NOUN
fcis-15107	125	4	5.1	5.1	NUM
fcis-15107	125	5	.	.	PUNCT
fcis-15107	126	1	experimental	experimental	ADJ
fcis-15107	126	2	results	result	NOUN
fcis-15107	126	3	the	the	DET
fcis-15107	126	4	network	network	NOUN
fcis-15107	126	5	frameworks	framework	NOUN
fcis-15107	126	6	used	use	VERB
fcis-15107	126	7	in	in	ADP
fcis-15107	126	8	our	our	PRON
fcis-15107	126	9	comparative	comparative	ADJ
fcis-15107	126	10	experiments	experiment	NOUN
fcis-15107	126	11	include	include	VERB
fcis-15107	126	12	the	the	DET
fcis-15107	126	13	most	most	ADV
fcis-15107	126	14	advanced	advanced	ADJ
fcis-15107	126	15	cnn	cnn	PROPN
fcis-15107	126	16	-	-	PUNCT
fcis-15107	126	17	based	base	VERB
fcis-15107	126	18	networks	network	NOUN
fcis-15107	126	19	,	,	PUNCT
fcis-15107	126	20	such	such	ADJ
fcis-15107	126	21	as	as	ADP
fcis-15107	126	22	u	u	NOUN
fcis-15107	126	23	-	-	NOUN
fcis-15107	126	24	net	net	ADJ
fcis-15107	126	25	,	,	PUNCT
fcis-15107	126	26	u	u	NOUN
fcis-15107	126	27	-	-	NOUN
fcis-15107	126	28	next	next	ADJ
fcis-15107	126	29	,	,	PUNCT
fcis-15107	126	30	and	and	CCONJ
fcis-15107	126	31	sc	sc	PROPN
fcis-15107	126	32	-	-	PROPN
fcis-15107	126	33	unext	unext	PROPN
fcis-15107	126	34	.	.	PUNCT
fcis-15107	127	1	below	below	ADP
fcis-15107	127	2	we	we	PRON
fcis-15107	127	3	will	will	AUX
fcis-15107	127	4	quantitatively	quantitatively	ADV
fcis-15107	127	5	and	and	CCONJ
fcis-15107	127	6	qualitatively	qualitatively	ADV
fcis-15107	127	7	compare	compare	VERB
fcis-15107	127	8	the	the	DET
fcis-15107	127	9	test	test	NOUN
fcis-15107	127	10	results	result	NOUN
fcis-15107	127	11	.	.	PUNCT
fcis-15107	128	1	analyze	analyze	VERB
fcis-15107	128	2	.	.	PUNCT
fcis-15107	129	1	furthermore	furthermore	ADV
fcis-15107	129	2	,	,	PUNCT
fcis-15107	129	3	the	the	DET
fcis-15107	129	4	number	number	NOUN
fcis-15107	129	5	of	of	ADP
fcis-15107	129	6	parameters	parameter	NOUN
fcis-15107	129	7	in	in	ADP
fcis-15107	129	8	each	each	DET
fcis-15107	129	9	network	network	NOUN
fcis-15107	129	10	is	be	AUX
fcis-15107	129	11	kept	keep	VERB
fcis-15107	129	12	to	to	ADP
fcis-15107	129	13	two	two	NUM
fcis-15107	129	14	decimal	decimal	ADJ
fcis-15107	129	15	places	place	NOUN
fcis-15107	129	16	.	.	PUNCT
fcis-15107	130	1	evaluation	evaluation	NOUN
fcis-15107	130	2	of	of	ADP
fcis-15107	130	3	dermatology	dermatology	NOUN
fcis-15107	130	4	datasets	dataset	NOUN
fcis-15107	130	5	.	.	PUNCT
fcis-15107	131	1	quantitative	quantitative	ADJ
fcis-15107	131	2	result	result	NOUN
fcis-15107	131	3	analysis	analysis	NOUN
fcis-15107	131	4	,	,	PUNCT
fcis-15107	131	5	the	the	DET
fcis-15107	131	6	quantitative	quantitative	ADJ
fcis-15107	131	7	comparison	comparison	NOUN
fcis-15107	131	8	results	result	NOUN
fcis-15107	131	9	of	of	ADP
fcis-15107	131	10	the	the	DET
fcis-15107	131	11	data	datum	NOUN
fcis-15107	131	12	set	set	VERB
fcis-15107	131	13	using	use	VERB
fcis-15107	131	14	different	different	ADJ
fcis-15107	131	15	methods	method	NOUN
fcis-15107	131	16	are	be	AUX
fcis-15107	131	17	shown	show	VERB
fcis-15107	131	18	in	in	ADP
fcis-15107	131	19	33	33	NUM
fcis-15107	131	20	figure	figure	NOUN
fcis-15107	131	21	3	3	NUM
fcis-15107	131	22	.	.	PUNCT
fcis-15107	131	23	skin	skin	NOUN
fcis-15107	131	24	disease	disease	NOUN
fcis-15107	131	25	segmentation	segmentation	NOUN
fcis-15107	131	26	effect	effect	VERB
fcis-15107	131	27	the	the	DET
fcis-15107	131	28	following	follow	VERB
fcis-15107	131	29	table	table	NOUN
fcis-15107	131	30	sc	sc	PROPN
fcis-15107	131	31	-	-	PROPN
fcis-15107	131	32	unext	unext	PROPN
fcis-15107	131	33	is	be	AUX
fcis-15107	131	34	the	the	DET
fcis-15107	131	35	segmentation	segmentation	NOUN
fcis-15107	131	36	evaluation	evaluation	NOUN
fcis-15107	131	37	indicators	indicator	NOUN
fcis-15107	131	38	dice	dice	VERB
fcis-15107	131	39	,	,	PUNCT
fcis-15107	131	40	iou	iou	NOUN
fcis-15107	131	41	,	,	PUNCT
fcis-15107	131	42	parameter	parameter	NOUN
fcis-15107	131	43	amount	amount	NOUN
fcis-15107	131	44	and	and	CCONJ
fcis-15107	131	45	computing	compute	VERB
fcis-15107	131	46	power	power	NOUN
fcis-15107	131	47	consumption	consumption	NOUN
fcis-15107	131	48	:	:	PUNCT
fcis-15107	131	49	table	table	NOUN
fcis-15107	131	50	1	1	NUM
fcis-15107	131	51	.	.	PUNCT
fcis-15107	131	52	segmentation	segmentation	NOUN
fcis-15107	131	53	evaluation	evaluation	NOUN
fcis-15107	131	54	index	index	NOUN
fcis-15107	131	55	method	method	NOUN
fcis-15107	131	56	flops	flop	VERB
fcis-15107	131	57	parameters	parameter	NOUN
fcis-15107	131	58	dice	dice	VERB
fcis-15107	131	59	iou	iou	PROPN
fcis-15107	131	60	u	u	PROPN
fcis-15107	131	61	-	-	PROPN
fcis-15107	131	62	net	net	ADJ
fcis-15107	131	63	25.06	25.06	NUM
fcis-15107	131	64	gflops	gflop	NOUN
fcis-15107	131	65	9.04	9.04	NUM
fcis-15107	131	66	mb	mb	ADP
fcis-15107	131	67	84.84	84.84	NUM
fcis-15107	131	68	%	%	NOUN
fcis-15107	131	69	76.37	76.37	NUM
fcis-15107	131	70	%	%	NOUN
fcis-15107	131	71	resunet++	resunet++	NOUN
fcis-15107	131	72	19.31gflops	19.31gflops	NUM
fcis-15107	131	73	7.67	7.67	NUM
fcis-15107	131	74	mb	mb	ADP
fcis-15107	131	75	85.73	85.73	NUM
fcis-15107	131	76	%	%	NOUN
fcis-15107	131	77	77.12	77.12	NUM
fcis-15107	131	78	%	%	NOUN
fcis-15107	131	79	unext	unext	ADJ
fcis-15107	131	80	0.10	0.10	NUM
fcis-15107	131	81	gflops	gflop	NOUN
fcis-15107	131	82	247.62	247.62	NUM
fcis-15107	131	83	kb	kb	PROPN
fcis-15107	131	84	86.64	86.64	NUM
fcis-15107	131	85	%	%	NOUN
fcis-15107	131	86	78.71	78.71	NUM
fcis-15107	131	87	%	%	NOUN
fcis-15107	131	88	sc	sc	PROPN
fcis-15107	131	89	-	-	PROPN
fcis-15107	131	90	unext	unext	ADJ
fcis-15107	131	91	0.13	0.13	NUM
fcis-15107	131	92	gflops	gflop	NOUN
fcis-15107	131	93	243.63	243.63	NUM
fcis-15107	131	94	kb	kb	NUM
fcis-15107	131	95	87.12	87.12	NUM
fcis-15107	131	96	%	%	NOUN
fcis-15107	131	97	79.13	79.13	NUM
fcis-15107	131	98	%	%	NOUN
fcis-15107	131	99	we	we	PRON
fcis-15107	131	100	noticed	notice	VERB
fcis-15107	131	101	that	that	SCONJ
fcis-15107	131	102	the	the	DET
fcis-15107	131	103	iou	iou	NOUN
fcis-15107	131	104	and	and	CCONJ
fcis-15107	131	105	dice	dice	NOUN
fcis-15107	131	106	of	of	ADP
fcis-15107	131	107	sc	sc	PROPN
fcis-15107	131	108	-unext	-unext	PROPN
fcis-15107	131	109	are	be	AUX
fcis-15107	131	110	2.74	2.74	NUM
fcis-15107	131	111	%	%	NOUN
fcis-15107	131	112	and	and	CCONJ
fcis-15107	131	113	2.76	2.76	NUM
fcis-15107	131	114	%	%	NOUN
fcis-15107	131	115	higher	high	ADJ
fcis-15107	131	116	than	than	ADP
fcis-15107	131	117	u	u	NOUN
fcis-15107	131	118	-	-	NOUN
fcis-15107	131	119	net	net	NOUN
fcis-15107	131	120	respectively	respectively	ADV
fcis-15107	131	121	,	,	PUNCT
fcis-15107	131	122	0.48	0.48	NUM
fcis-15107	131	123	%	%	NOUN
fcis-15107	131	124	and	and	CCONJ
fcis-15107	131	125	0.42	0.42	NUM
fcis-15107	131	126	%	%	NOUN
fcis-15107	131	127	higher	high	ADJ
fcis-15107	131	128	than	than	ADP
fcis-15107	131	129	unext	unext	ADJ
fcis-15107	131	130	respectively	respectively	ADV
fcis-15107	131	131	,	,	PUNCT
fcis-15107	131	132	and	and	CCONJ
fcis-15107	131	133	1.39	1.39	NUM
fcis-15107	131	134	%	%	NOUN
fcis-15107	131	135	and	and	CCONJ
fcis-15107	131	136	2.01	2.01	NUM
fcis-15107	131	137	%	%	NOUN
fcis-15107	131	138	higher	high	ADJ
fcis-15107	131	139	than	than	ADP
fcis-15107	131	140	resunet++	resunet++	NOUN
fcis-15107	131	141	.	.	PUNCT
fcis-15107	132	1	we	we	PRON
fcis-15107	132	2	noticed	notice	VERB
fcis-15107	132	3	,	,	PUNCT
fcis-15107	132	4	compared	compare	VERB
fcis-15107	132	5	with	with	ADP
fcis-15107	132	6	u	u	NOUN
fcis-15107	132	7	-	-	NOUN
fcis-15107	132	8	net	net	NOUN
fcis-15107	132	9	's	's	PART
fcis-15107	132	10	9.04	9.04	NUM
fcis-15107	132	11	m	m	NOUN
fcis-15107	132	12	parameters	parameter	NOUN
fcis-15107	132	13	,	,	PUNCT
fcis-15107	132	14	sc	sc	PROPN
fcis-15107	132	15	-unext	-unext	PROPN
fcis-15107	132	16	's	's	PART
fcis-15107	132	17	243.63	243.63	NUM
fcis-15107	132	18	kb	kb	PROPN
fcis-15107	132	19	parameters	parameter	NOUN
fcis-15107	132	20	are	be	AUX
fcis-15107	132	21	also	also	ADV
fcis-15107	132	22	relatively	relatively	ADV
fcis-15107	132	23	low	low	ADJ
fcis-15107	132	24	,	,	PUNCT
fcis-15107	132	25	roughly	roughly	ADV
fcis-15107	132	26	the	the	DET
fcis-15107	132	27	same	same	ADJ
fcis-15107	132	28	as	as	ADP
fcis-15107	132	29	unext	unext	PROPN
fcis-15107	132	30	.	.	PUNCT
fcis-15107	133	1	while	while	SCONJ
fcis-15107	133	2	retaining	retain	VERB
fcis-15107	133	3	the	the	DET
fcis-15107	133	4	lightweight	lightweight	NOUN
fcis-15107	133	5	,	,	PUNCT
fcis-15107	133	6	simple	simple	ADJ
fcis-15107	133	7	calculation	calculation	NOUN
fcis-15107	133	8	,	,	PUNCT
fcis-15107	133	9	and	and	CCONJ
fcis-15107	133	10	fast	fast	ADJ
fcis-15107	133	11	characteristics	characteristic	NOUN
fcis-15107	133	12	of	of	ADP
fcis-15107	133	13	unext	unext	PROPN
fcis-15107	133	14	,	,	PUNCT
fcis-15107	133	15	the	the	DET
fcis-15107	133	16	segmentation	segmentation	NOUN
fcis-15107	133	17	effect	effect	NOUN
fcis-15107	133	18	has	have	AUX
fcis-15107	133	19	been	be	AUX
fcis-15107	133	20	significantly	significantly	ADV
fcis-15107	133	21	improved	improve	VERB
fcis-15107	133	22	from	from	ADP
fcis-15107	133	23	the	the	DET
fcis-15107	133	24	dice	dice	NOUN
fcis-15107	133	25	coefficient	coefficient	NOUN
fcis-15107	133	26	and	and	CCONJ
fcis-15107	133	27	iou	iou	ADJ
fcis-15107	133	28	coefficient	coefficient	NOUN
fcis-15107	133	29	.	.	PUNCT
fcis-15107	134	1	regarding	regard	VERB
fcis-15107	134	2	the	the	DET
fcis-15107	134	3	computational	computational	ADJ
fcis-15107	134	4	power	power	NOUN
fcis-15107	134	5	consumption	consumption	NOUN
fcis-15107	134	6	of	of	ADP
fcis-15107	134	7	the	the	DET
fcis-15107	134	8	model	model	NOUN
fcis-15107	134	9	,	,	PUNCT
fcis-15107	134	10	that	that	ADV
fcis-15107	134	11	is	is	ADV
fcis-15107	134	12	,	,	PUNCT
fcis-15107	134	13	in	in	ADP
fcis-15107	134	14	terms	term	NOUN
fcis-15107	134	15	of	of	ADP
fcis-15107	134	16	flops	flop	NOUN
fcis-15107	134	17	,	,	PUNCT
fcis-15107	134	18	it	it	PRON
fcis-15107	134	19	consumes	consume	VERB
fcis-15107	134	20	less	less	ADJ
fcis-15107	134	21	than	than	ADP
fcis-15107	134	22	unet	unet	NOUN
fcis-15107	134	23	,	,	PUNCT
fcis-15107	134	24	which	which	PRON
fcis-15107	134	25	ensures	ensure	VERB
fcis-15107	134	26	the	the	DET
fcis-15107	134	27	lightweight	lightweight	NOUN
fcis-15107	134	28	of	of	ADP
fcis-15107	134	29	the	the	DET
fcis-15107	134	30	model	model	NOUN
fcis-15107	134	31	and	and	CCONJ
fcis-15107	134	32	saves	save	VERB
fcis-15107	134	33	the	the	DET
fcis-15107	134	34	consumption	consumption	NOUN
fcis-15107	134	35	of	of	ADP
fcis-15107	134	36	computing	compute	VERB
fcis-15107	134	37	power	power	NOUN
fcis-15107	134	38	.	.	PUNCT
fcis-15107	135	1	5.2	5.2	NUM
fcis-15107	135	2	.	.	PUNCT
fcis-15107	135	3	ablation	ablation	NOUN
fcis-15107	135	4	experiment	experiment	NOUN
fcis-15107	135	5	_	_	PUNCT
fcis-15107	135	6	in	in	ADP
fcis-15107	135	7	actual	actual	ADJ
fcis-15107	135	8	situations	situation	NOUN
fcis-15107	135	9	,	,	PUNCT
fcis-15107	135	10	if	if	SCONJ
fcis-15107	135	11	a	a	DET
fcis-15107	135	12	model	model	NOUN
fcis-15107	135	13	is	be	AUX
fcis-15107	135	14	to	to	PART
fcis-15107	135	15	be	be	AUX
fcis-15107	135	16	put	put	VERB
fcis-15107	135	17	online	online	ADV
fcis-15107	135	18	,	,	PUNCT
fcis-15107	135	19	the	the	DET
fcis-15107	135	20	model	model	NOUN
fcis-15107	135	21	needs	need	VERB
fcis-15107	135	22	to	to	PART
fcis-15107	135	23	be	be	AUX
fcis-15107	135	24	repeatedly	repeatedly	ADV
fcis-15107	135	25	debugged	debug	VERB
fcis-15107	135	26	to	to	PART
fcis-15107	135	27	prevent	prevent	VERB
fcis-15107	135	28	the	the	DET
fcis-15107	135	29	model	model	NOUN
fcis-15107	135	30	from	from	ADP
fcis-15107	135	31	performing	perform	VERB
fcis-15107	135	32	better	well	ADV
fcis-15107	135	33	only	only	ADV
fcis-15107	135	34	on	on	ADP
fcis-15107	135	35	known	know	VERB
fcis-15107	135	36	data	data	NOUN
fcis-15107	135	37	sets	set	NOUN
fcis-15107	135	38	and	and	CCONJ
fcis-15107	135	39	performing	perform	VERB
fcis-15107	135	40	poorly	poorly	ADV
fcis-15107	135	41	on	on	ADP
fcis-15107	135	42	unknown	unknown	ADJ
fcis-15107	135	43	data	datum	NOUN
fcis-15107	135	44	sets	set	NOUN
fcis-15107	135	45	.	.	PUNCT
fcis-15107	136	1	that	that	PRON
fcis-15107	136	2	is	be	AUX
fcis-15107	136	3	to	to	PART
fcis-15107	136	4	ensure	ensure	VERB
fcis-15107	136	5	the	the	DET
fcis-15107	136	6	generalization	generalization	NOUN
fcis-15107	136	7	ability	ability	NOUN
fcis-15107	136	8	of	of	ADP
fcis-15107	136	9	the	the	DET
fcis-15107	136	10	model	model	NOUN
fcis-15107	136	11	,	,	PUNCT
fcis-15107	136	12	which	which	PRON
fcis-15107	136	13	refers	refer	VERB
fcis-15107	136	14	to	to	ADP
fcis-15107	136	15	the	the	DET
fcis-15107	136	16	adaptability	adaptability	NOUN
fcis-15107	136	17	of	of	ADP
fcis-15107	136	18	machine	machine	NOUN
fcis-15107	136	19	learning	learn	VERB
fcis-15107	136	20	to	to	ADP
fcis-15107	136	21	fresh	fresh	ADJ
fcis-15107	136	22	samples	sample	NOUN
fcis-15107	136	23	.	.	PUNCT
fcis-15107	137	1	only	only	ADV
fcis-15107	137	2	by	by	ADP
fcis-15107	137	3	ensuring	ensure	VERB
fcis-15107	137	4	the	the	DET
fcis-15107	137	5	generalization	generalization	NOUN
fcis-15107	137	6	ability	ability	NOUN
fcis-15107	137	7	of	of	ADP
fcis-15107	137	8	the	the	DET
fcis-15107	137	9	model	model	NOUN
fcis-15107	137	10	can	can	AUX
fcis-15107	137	11	the	the	DET
fcis-15107	137	12	construction	construction	NOUN
fcis-15107	137	13	of	of	ADP
fcis-15107	137	14	the	the	DET
fcis-15107	137	15	model	model	NOUN
fcis-15107	137	16	be	be	AUX
fcis-15107	137	17	meaningful	meaningful	ADJ
fcis-15107	137	18	.	.	PUNCT
fcis-15107	138	1	therefore	therefore	ADV
fcis-15107	138	2	,	,	PUNCT
fcis-15107	138	3	crossvalidation	crossvalidation	NOUN
fcis-15107	138	4	is	be	AUX
fcis-15107	138	5	particularly	particularly	ADV
fcis-15107	138	6	important	important	ADJ
fcis-15107	138	7	throughout	throughout	ADP
fcis-15107	138	8	the	the	DET
fcis-15107	138	9	modeling	modeling	NOUN
fcis-15107	138	10	process	process	NOUN
fcis-15107	138	11	.	.	PUNCT
fcis-15107	139	1	use	use	VERB
fcis-15107	139	2	training	training	NOUN
fcis-15107	139	3	set	set	NOUN
fcis-15107	139	4	/	/	SYM
fcis-15107	139	5	test	test	NOUN
fcis-15107	139	6	set	set	VERB
fcis-15107	139	7	splitting	splitting	NOUN
fcis-15107	139	8	and	and	CCONJ
fcis-15107	139	9	cross	cross	ADJ
fcis-15107	139	10	-	-	ADJ
fcis-15107	139	11	validation	validation	ADJ
fcis-15107	139	12	methods	method	NOUN
fcis-15107	139	13	to	to	PART
fcis-15107	139	14	avoid	avoid	VERB
fcis-15107	139	15	this	this	DET
fcis-15107	139	16	situation	situation	NOUN
fcis-15107	139	17	.	.	PUNCT
fcis-15107	140	1	as	as	SCONJ
fcis-15107	140	2	shown	show	VERB
fcis-15107	140	3	in	in	ADP
fcis-15107	140	4	the	the	DET
fcis-15107	140	5	figure	figure	NOUN
fcis-15107	140	6	below	below	ADV
fcis-15107	140	7	,	,	PUNCT
fcis-15107	140	8	split	split	VERB
fcis-15107	140	9	the	the	DET
fcis-15107	140	10	data	datum	NOUN
fcis-15107	140	11	set	set	VERB
fcis-15107	140	12	into	into	ADP
fcis-15107	140	13	training	training	NOUN
fcis-15107	140	14	set	set	NOUN
fcis-15107	140	15	/	/	SYM
fcis-15107	140	16	test	test	NOUN
fcis-15107	140	17	set	set	NOUN
fcis-15107	140	18	,	,	PUNCT
fcis-15107	140	19	and	and	CCONJ
fcis-15107	140	20	perform	perform	VERB
fcis-15107	140	21	crossvalidation	crossvalidation	NOUN
fcis-15107	140	22	on	on	ADP
fcis-15107	140	23	the	the	DET
fcis-15107	140	24	training	training	NOUN
fcis-15107	140	25	set	set	VERB
fcis-15107	140	26	to	to	PART
fcis-15107	140	27	obtain	obtain	VERB
fcis-15107	140	28	the	the	DET
fcis-15107	140	29	best	good	ADJ
fcis-15107	140	30	model	model	NOUN
fcis-15107	140	31	parameters	parameter	NOUN
fcis-15107	140	32	.	.	PUNCT
fcis-15107	140	33	,	,	PUNCT
fcis-15107	140	34	thereby	thereby	ADV
fcis-15107	140	35	obtaining	obtain	VERB
fcis-15107	140	36	the	the	DET
fcis-15107	140	37	score	score	NOUN
fcis-15107	140	38	of	of	ADP
fcis-15107	140	39	the	the	DET
fcis-15107	140	40	model	model	NOUN
fcis-15107	140	41	on	on	ADP
fcis-15107	140	42	the	the	DET
fcis-15107	140	43	test	test	NOUN
fcis-15107	140	44	set	set	NOUN
fcis-15107	140	45	.	.	PUNCT
fcis-15107	141	1	this	this	DET
fcis-15107	141	2	experiment	experiment	NOUN
fcis-15107	141	3	adopts	adopt	VERB
fcis-15107	141	4	five	five	NUM
fcis-15107	141	5	-	-	ADJ
fcis-15107	141	6	fold	fold	ADJ
fcis-15107	141	7	cross	cross	ADJ
fcis-15107	141	8	-	-	ADJ
fcis-15107	141	9	validation	validation	ADJ
fcis-15107	141	10	and	and	CCONJ
fcis-15107	141	11	conducts	conduct	VERB
fcis-15107	141	12	cross	cross	ADJ
fcis-15107	141	13	-	-	ADJ
fcis-15107	141	14	validation	validation	ADJ
fcis-15107	141	15	experiments	experiment	NOUN
fcis-15107	141	16	on	on	ADP
fcis-15107	141	17	sc	sc	PROPN
fcis-15107	141	18	-	-	NOUN
fcis-15107	141	19	unext	unext	NOUN
fcis-15107	141	20	in	in	ADP
fcis-15107	141	21	three	three	NUM
fcis-15107	141	22	directions	direction	NOUN
fcis-15107	141	23	:	:	PUNCT
fcis-15107	141	24	jump	jump	NOUN
fcis-15107	141	25	link	link	NOUN
fcis-15107	141	26	,	,	PUNCT
fcis-15107	141	27	feature	feature	NOUN
fcis-15107	141	28	fusion	fusion	NOUN
fcis-15107	141	29	,	,	PUNCT
fcis-15107	141	30	and	and	CCONJ
fcis-15107	141	31	joint	joint	ADJ
fcis-15107	141	32	loss	loss	NOUN
fcis-15107	141	33	function	function	NOUN
fcis-15107	141	34	.	.	PUNCT
fcis-15107	142	1	the	the	DET
fcis-15107	142	2	experimental	experimental	ADJ
fcis-15107	142	3	results	result	NOUN
fcis-15107	142	4	are	be	AUX
fcis-15107	142	5	as	as	SCONJ
fcis-15107	142	6	follows	follow	VERB
fcis-15107	142	7	:	:	PUNCT
fcis-15107	143	1	table	table	NOUN
fcis-15107	143	2	2	2	NUM
fcis-15107	143	3	.	.	PUNCT
fcis-15107	143	4	ablation	ablation	NOUN
fcis-15107	143	5	experiment	experiment	NOUN
fcis-15107	143	6	model	model	PROPN
fcis-15107	143	7	dsc	dsc	PROPN
fcis-15107	143	8	evaluation	evaluation	NOUN
fcis-15107	143	9	index	index	NOUN
fcis-15107	143	10	isic	isic	PROPN
fcis-15107	143	11	207	207	NUM
fcis-15107	143	12	data	datum	NOUN
fcis-15107	143	13	set	set	VERB
fcis-15107	143	14	val	val	NOUN
fcis-15107	143	15	:	:	PUNCT
fcis-15107	143	16	24	24	NUM
fcis-15107	143	17	data	datum	NOUN
fcis-15107	143	18	volume	volume	NOUN
fcis-15107	143	19	train	train	NOUN
fcis-15107	143	20	:	:	PUNCT
fcis-15107	143	21	9	9	NUM
fcis-15107	143	22	6	6	NUM
fcis-15107	143	23	val	val	NOUN
fcis-15107	143	24	:	:	PUNCT
fcis-15107	143	25	24	24	NUM
fcis-15107	143	26	5	5	NUM
fcis-15107	143	27	fold	fold	NOUN
fcis-15107	143	28	cross	cross	NOUN
fcis-15107	143	29	validation	validation	NOUN
fcis-15107	143	30	fold-1	fold-1	PROPN
fcis-15107	143	31	f	f	PROPN
fcis-15107	143	32	old-2	old-2	NUM
fcis-15107	143	33	f	f	PROPN
fcis-15107	143	34	old	old	ADJ
fcis-15107	143	35	-3	-3	INTJ
fcis-15107	143	36	f	f	PROPN
fcis-15107	143	37	old	old	ADJ
fcis-15107	143	38	-4	-4	X
fcis-15107	143	39	f	f	PROPN
fcis-15107	143	40	old	old	ADJ
fcis-15107	143	41	-5	-5	INTJ
fcis-15107	143	42	mean	mean	ADJ
fcis-15107	143	43	variance	variance	NOUN
fcis-15107	143	44	unext	unext	ADJ
fcis-15107	143	45	82.61	82.61	NUM
fcis-15107	143	46	%	%	NOUN
fcis-15107	143	47	84.66	84.66	NUM
fcis-15107	143	48	%	%	NOUN
fcis-15107	143	49	91.47	91.47	NUM
fcis-15107	143	50	%	%	NOUN
fcis-15107	143	51	87.61	87.61	NUM
fcis-15107	143	52	%	%	NOUN
fcis-15107	143	53	83.08	83.08	NUM
fcis-15107	143	54	%	%	NOUN
fcis-15107	143	55	85.89	85.89	NUM
fcis-15107	143	56	%	%	NOUN
fcis-15107	143	57	0.14	0.14	NUM
fcis-15107	143	58	%	%	NOUN
fcis-15107	143	59	sc_unext	sc_unext	NOUN
fcis-15107	143	60	(	(	PUNCT
fcis-15107	143	61	edge_loss	edge_loss	PROPN
fcis-15107	143	62	)	)	PUNCT
fcis-15107	143	63	85.10	85.10	NUM
fcis-15107	143	64	%	%	NOUN
fcis-15107	143	65	85.53	85.53	NUM
fcis-15107	143	66	%	%	NOUN
fcis-15107	143	67	88.51	88.51	NUM
fcis-15107	143	68	%	%	NOUN
fcis-15107	143	69	86.69	86.69	NUM
fcis-15107	143	70	%	%	NOUN
fcis-15107	143	71	86.84	86.84	NUM
fcis-15107	143	72	%	%	NOUN
fcis-15107	143	73	86.14	86.14	NUM
fcis-15107	143	74	%	%	NOUN
fcis-15107	143	75	0.03	0.03	NUM
fcis-15107	143	76	%	%	NOUN
fcis-15107	143	77	sc_unext	sc_unext	NOUN
fcis-15107	143	78	(	(	PUNCT
fcis-15107	143	79	skip	skip	PROPN
fcis-15107	143	80	)	)	PUNCT
fcis-15107	143	81	85.73	85.73	NUM
fcis-15107	143	82	%	%	NOUN
fcis-15107	143	83	85.90	85.90	NUM
fcis-15107	143	84	%	%	NOUN
fcis-15107	143	85	90.68	90.68	NUM
fcis-15107	143	86	%	%	NOUN
fcis-15107	143	87	82.46	82.46	NUM
fcis-15107	143	88	%	%	NOUN
fcis-15107	143	89	83.75	83.75	NUM
fcis-15107	143	90	%	%	NOUN
fcis-15107	143	91	86.53	86.53	NUM
fcis-15107	143	92	%	%	NOUN
fcis-15107	143	93	0.13	0.13	NUM
fcis-15107	143	94	%	%	NOUN
fcis-15107	143	95	sc_unext	sc_unext	NOUN
fcis-15107	143	96	(	(	PUNCT
fcis-15107	143	97	fuse	fuse	NOUN
fcis-15107	143	98	)	)	PUNCT
fcis-15107	143	99	87.17	87.17	NUM
fcis-15107	143	100	%	%	NOUN
fcis-15107	143	101	85.07	85.07	NUM
fcis-15107	143	102	%	%	NOUN
fcis-15107	143	103	90.58	90.58	NUM
fcis-15107	143	104	%	%	NOUN
fcis-15107	143	105	85.59	85.59	NUM
fcis-15107	143	106	%	%	NOUN
fcis-15107	143	107	84.92	84.92	NUM
fcis-15107	143	108	%	%	NOUN
fcis-15107	143	109	86.17	86.17	NUM
fcis-15107	143	110	%	%	NOUN
fcis-15107	143	111	0.10	0.10	NUM
fcis-15107	143	112	%	%	NOUN
fcis-15107	143	113	sc_unext(edge	sc_unext(edge	PUNCT
fcis-15107	143	114	loss+skip	loss+skip	PROPN
fcis-15107	143	115	)	)	PUNCT
fcis-15107	143	116	85.90	85.90	NUM
fcis-15107	143	117	%	%	NOUN
fcis-15107	143	118	87.98	87.98	NUM
fcis-15107	143	119	%	%	NOUN
fcis-15107	143	120	90.22	90.22	NUM
fcis-15107	143	121	%	%	NOUN
fcis-15107	143	122	85.79	85.79	NUM
fcis-15107	143	123	%	%	NOUN
fcis-15107	143	124	89.14	89.14	NUM
fcis-15107	143	125	%	%	NOUN
fcis-15107	143	126	86.90	86.90	NUM
fcis-15107	143	127	%	%	NOUN
fcis-15107	143	128	0.05	0.05	NUM
fcis-15107	143	129	%	%	NOUN
fcis-15107	143	130	sc_unext	sc_unext	NOUN
fcis-15107	143	131	(	(	PUNCT
fcis-15107	143	132	edge_loss+fuse	edge_loss+fuse	NOUN
fcis-15107	143	133	)	)	PUNCT
fcis-15107	143	134	87.98	87.98	NUM
fcis-15107	143	135	%	%	NOUN
fcis-15107	143	136	80.14	80.14	NUM
fcis-15107	143	137	%	%	NOUN
fcis-15107	143	138	90.50	90.50	NUM
fcis-15107	143	139	%	%	NOUN
fcis-15107	143	140	86.48	86.48	NUM
fcis-15107	143	141	%	%	NOUN
fcis-15107	143	142	88.03	88.03	NUM
fcis-15107	143	143	%	%	NOUN
fcis-15107	143	144	86.98	86.98	NUM
fcis-15107	143	145	%	%	NOUN
fcis-15107	143	146	0.20	0.20	NUM
fcis-15107	143	147	%	%	NOUN
fcis-15107	143	148	sc_unext	sc_unext	NOUN
fcis-15107	143	149	(	(	PUNCT
fcis-15107	143	150	skip+fuse	skip+fuse	PROPN
fcis-15107	143	151	)	)	PUNCT
fcis-15107	143	152	82.90	82.90	NUM
fcis-15107	143	153	%	%	NOUN
fcis-15107	143	154	88.62	88.62	NUM
fcis-15107	143	155	%	%	NOUN
fcis-15107	143	156	88.60	88.60	NUM
fcis-15107	143	157	%	%	NOUN
fcis-15107	143	158	84.90	84.90	NUM
fcis-15107	143	159	%	%	NOUN
fcis-15107	143	160	87.30	87.30	NUM
fcis-15107	143	161	%	%	NOUN
fcis-15107	143	162	85.90	85.90	NUM
fcis-15107	143	163	%	%	NOUN
fcis-15107	143	164	0.07	0.07	NUM
fcis-15107	143	165	%	%	NOUN
fcis-15107	143	166	sc_unext(edge_loss+skip+fuse	sc_unext(edge_loss+skip+fuse	NOUN
fcis-15107	143	167	)	)	PUNCT
fcis-15107	143	168	85.89	85.89	NUM
fcis-15107	143	169	%	%	NOUN
fcis-15107	143	170	88.11	88.11	NUM
fcis-15107	143	171	%	%	NOUN
fcis-15107	143	172	89.02	89.02	NUM
fcis-15107	143	173	%	%	NOUN
fcis-15107	143	174	86.11	86.11	NUM
fcis-15107	143	175	%	%	NOUN
fcis-15107	143	176	87.22	87.22	NUM
fcis-15107	143	177	%	%	NOUN
fcis-15107	143	178	87.29	87.29	NUM
fcis-15107	143	179	%	%	NOUN
fcis-15107	143	180	0.08	0.08	NUM
fcis-15107	143	181	%	%	NOUN
fcis-15107	143	182	through	through	ADP
fcis-15107	143	183	the	the	DET
fcis-15107	143	184	comparison	comparison	NOUN
fcis-15107	143	185	of	of	ADP
fcis-15107	143	186	ablation	ablation	NOUN
fcis-15107	143	187	experiments	experiment	NOUN
fcis-15107	143	188	,	,	PUNCT
fcis-15107	143	189	it	it	PRON
fcis-15107	143	190	was	be	AUX
fcis-15107	143	191	found	find	VERB
fcis-15107	143	192	that	that	SCONJ
fcis-15107	143	193	jump	jump	NOUN
fcis-15107	143	194	links	link	NOUN
fcis-15107	143	195	,	,	PUNCT
fcis-15107	143	196	feature	feature	NOUN
fcis-15107	143	197	fusion	fusion	NOUN
fcis-15107	143	198	,	,	PUNCT
fcis-15107	143	199	and	and	CCONJ
fcis-15107	143	200	joint	joint	ADJ
fcis-15107	143	201	loss	loss	NOUN
fcis-15107	143	202	functions	function	NOUN
fcis-15107	143	203	all	all	PRON
fcis-15107	143	204	have	have	VERB
fcis-15107	143	205	an	an	DET
fcis-15107	143	206	impact	impact	NOUN
fcis-15107	143	207	on	on	ADP
fcis-15107	143	208	segmentation	segmentation	NOUN
fcis-15107	143	209	accuracy	accuracy	NOUN
fcis-15107	143	210	.	.	PUNCT
fcis-15107	144	1	only	only	ADV
fcis-15107	144	2	under	under	ADP
fcis-15107	144	3	the	the	DET
fcis-15107	144	4	combined	combine	VERB
fcis-15107	144	5	effect	effect	NOUN
fcis-15107	144	6	of	of	ADP
fcis-15107	144	7	s	s	NOUN
fcis-15107	144	8	c	c	NOUN
fcis-15107	144	9	-	-	NOUN
fcis-15107	144	10	unext	unext	NOUN
fcis-15107	144	11	at	at	ADP
fcis-15107	144	12	the	the	DET
fcis-15107	144	13	same	same	ADJ
fcis-15107	144	14	time	time	NOUN
fcis-15107	144	15	,	,	PUNCT
fcis-15107	144	16	the	the	DET
fcis-15107	144	17	dsc	dsc	NOUN
fcis-15107	144	18	evaluation	evaluation	NOUN
fcis-15107	144	19	index	index	NOUN
fcis-15107	144	20	is	be	AUX
fcis-15107	144	21	the	the	DET
fcis-15107	144	22	highest	high	ADJ
fcis-15107	144	23	and	and	CCONJ
fcis-15107	144	24	the	the	DET
fcis-15107	144	25	segmentation	segmentation	NOUN
fcis-15107	144	26	effect	effect	NOUN
fcis-15107	144	27	is	be	AUX
fcis-15107	144	28	good	good	ADJ
fcis-15107	144	29	.	.	PUNCT
fcis-15107	145	1	6	6	X
fcis-15107	145	2	.	.	X
fcis-15107	145	3	discussion	discussion	NOUN
fcis-15107	145	4	in	in	ADP
fcis-15107	145	5	this	this	DET
fcis-15107	145	6	article	article	NOUN
fcis-15107	145	7	,	,	PUNCT
fcis-15107	145	8	our	our	PRON
fcis-15107	145	9	purpose	purpose	NOUN
fcis-15107	145	10	is	be	AUX
fcis-15107	145	11	to	to	PART
fcis-15107	145	12	make	make	VERB
fcis-15107	145	13	the	the	DET
fcis-15107	145	14	network	network	NOUN
fcis-15107	145	15	better	well	ADV
fcis-15107	145	16	learn	learn	VERB
fcis-15107	145	17	effective	effective	ADJ
fcis-15107	145	18	features	feature	NOUN
fcis-15107	145	19	and	and	CCONJ
fcis-15107	145	20	obtain	obtain	VERB
fcis-15107	145	21	more	more	ADV
fcis-15107	145	22	accurate	accurate	ADJ
fcis-15107	145	23	lesion	lesion	NOUN
fcis-15107	145	24	segmentation	segmentation	NOUN
fcis-15107	145	25	results	result	NOUN
fcis-15107	145	26	.	.	PUNCT
fcis-15107	146	1	we	we	PRON
fcis-15107	146	2	propose	propose	VERB
fcis-15107	146	3	an	an	DET
fcis-15107	146	4	improvement	improvement	NOUN
fcis-15107	146	5	that	that	PRON
fcis-15107	146	6	uses	use	VERB
fcis-15107	146	7	feature	feature	NOUN
fcis-15107	146	8	fusion	fusion	NOUN
fcis-15107	146	9	and	and	CCONJ
fcis-15107	146	10	increases	increase	VERB
fcis-15107	146	11	the	the	DET
fcis-15107	146	12	proportion	proportion	NOUN
fcis-15107	146	13	of	of	ADP
fcis-15107	146	14	edge	edge	NOUN
fcis-15107	146	15	features	feature	NOUN
fcis-15107	146	16	in	in	ADP
fcis-15107	146	17	the	the	DET
fcis-15107	146	18	total	total	ADJ
fcis-15107	146	19	sample	sample	NOUN
fcis-15107	146	20	features	feature	NOUN
fcis-15107	146	21	.	.	PUNCT
fcis-15107	147	1	network	network	NOUN
fcis-15107	147	2	architecture	architecture	NOUN
fcis-15107	147	3	.	.	PUNCT
fcis-15107	148	1	this	this	DET
fcis-15107	148	2	network	network	NOUN
fcis-15107	148	3	is	be	AUX
fcis-15107	148	4	not	not	PART
fcis-15107	148	5	only	only	ADV
fcis-15107	148	6	better	well	ADJ
fcis-15107	148	7	than	than	ADP
fcis-15107	148	8	other	other	ADJ
fcis-15107	148	9	methods	method	NOUN
fcis-15107	148	10	in	in	ADP
fcis-15107	148	11	terms	term	NOUN
fcis-15107	148	12	of	of	ADP
fcis-15107	148	13	evaluation	evaluation	NOUN
fcis-15107	148	14	indicators	indicator	NOUN
fcis-15107	148	15	,	,	PUNCT
fcis-15107	148	16	but	but	CCONJ
fcis-15107	148	17	is	be	AUX
fcis-15107	148	18	also	also	ADV
fcis-15107	148	19	cost	cost	NOUN
fcis-15107	148	20	-	-	PUNCT
fcis-15107	148	21	effective	effective	ADJ
fcis-15107	148	22	enough	enough	ADV
fcis-15107	148	23	to	to	PART
fcis-15107	148	24	better	well	ADV
fcis-15107	148	25	help	help	VERB
fcis-15107	148	26	doctors	doctor	NOUN
fcis-15107	148	27	better	well	ADV
fcis-15107	148	28	diagnose	diagnose	VERB
fcis-15107	148	29	the	the	DET
fcis-15107	148	30	details	detail	NOUN
fcis-15107	148	31	of	of	ADP
fcis-15107	148	32	these	these	DET
fcis-15107	148	33	histological	histological	ADJ
fcis-15107	148	34	images	image	NOUN
fcis-15107	148	35	.	.	PUNCT
fcis-15107	149	1	future	future	ADJ
fcis-15107	149	2	research	research	NOUN
fcis-15107	149	3	topics	topic	NOUN
fcis-15107	149	4	in	in	ADP
fcis-15107	149	5	medical	medical	ADJ
fcis-15107	149	6	image	image	NOUN
fcis-15107	149	7	segmentation	segmentation	NOUN
fcis-15107	149	8	will	will	AUX
fcis-15107	149	9	be	be	AUX
fcis-15107	149	10	deep	deep	ADJ
fcis-15107	149	11	learning	learn	VERB
fcis-15107	149	12	to	to	PART
fcis-15107	149	13	automatically	automatically	ADV
fcis-15107	149	14	select	select	VERB
fcis-15107	149	15	features	feature	NOUN
fcis-15107	149	16	from	from	ADP
fcis-15107	149	17	different	different	ADJ
fcis-15107	149	18	resolutions	resolution	NOUN
fcis-15107	149	19	,	,	PUNCT
fcis-15107	149	20	or	or	CCONJ
fcis-15107	149	21	consider	consider	VERB
fcis-15107	149	22	using	use	VERB
fcis-15107	149	23	adversarial	adversarial	ADJ
fcis-15107	149	24	training	training	NOUN
fcis-15107	149	25	including	include	VERB
fcis-15107	149	26	test	test	NOUN
fcis-15107	149	27	images	image	NOUN
fcis-15107	149	28	to	to	PART
fcis-15107	149	29	exploit	exploit	VERB
fcis-15107	149	30	features	feature	NOUN
fcis-15107	149	31	in	in	ADP
fcis-15107	149	32	test	test	NOUN
fcis-15107	149	33	images	image	NOUN
fcis-15107	149	34	without	without	ADP
fcis-15107	149	35	annotations	annotation	NOUN
fcis-15107	149	36	.	.	PUNCT
fcis-15107	150	1	it	it	PRON
fcis-15107	150	2	achieves	achieve	VERB
fcis-15107	150	3	high	high	ADJ
fcis-15107	150	4	-	-	PUNCT
fcis-15107	150	5	precision	precision	NOUN
fcis-15107	150	6	segmentation	segmentation	NOUN
fcis-15107	150	7	while	while	SCONJ
fcis-15107	150	8	also	also	ADV
fcis-15107	150	9	achieving	achieve	VERB
fcis-15107	150	10	instant	instant	ADJ
fcis-15107	150	11	feedback	feedback	NOUN
fcis-15107	150	12	and	and	CCONJ
fcis-15107	150	13	lightweight	lightweight	ADJ
fcis-15107	150	14	operations	operation	NOUN
fcis-15107	150	15	,	,	PUNCT
fcis-15107	150	16	which	which	PRON
fcis-15107	150	17	plays	play	VERB
fcis-15107	150	18	a	a	DET
fcis-15107	150	19	role	role	NOUN
fcis-15107	150	20	in	in	ADP
fcis-15107	150	21	assisting	assist	VERB
fcis-15107	150	22	diagnosis	diagnosis	NOUN
fcis-15107	150	23	and	and	CCONJ
fcis-15107	150	24	treatment	treatment	NOUN
fcis-15107	150	25	in	in	ADP
fcis-15107	150	26	the	the	DET
fcis-15107	150	27	medical	medical	ADJ
fcis-15107	150	28	process	process	NOUN
fcis-15107	150	29	.	.	PUNCT
fcis-15107	151	1	references	reference	NOUN
fcis-15107	151	2	[	[	X
fcis-15107	151	3	1	1	NUM
fcis-15107	151	4	]	]	X
fcis-15107	151	5	o.	o.	PROPN
fcis-15107	151	6	c.	c.	PROPN
fcis-15107	151	7	eidheim	eidheim	PROPN
fcis-15107	151	8	,	,	PUNCT
fcis-15107	151	9	l.	l.	PROPN
fcis-15107	151	10	aurdal	aurdal	PROPN
fcis-15107	151	11	,	,	PUNCT
fcis-15107	151	12	t.	t.	PROPN
fcis-15107	151	13	omholt	omholt	PROPN
fcis-15107	151	14	-	-	PUNCT
fcis-15107	151	15	jensen	jensen	PROPN
fcis-15107	151	16	,	,	PUNCT
fcis-15107	151	17	t.	t.	PROPN
fcis-15107	151	18	mala	mala	PROPN
fcis-15107	151	19	,	,	PUNCT
fcis-15107	151	20	and	and	CCONJ
fcis-15107	151	21	b.	b.	PROPN
fcis-15107	151	22	edwin	edwin	PROPN
fcis-15107	151	23	,	,	PUNCT
fcis-15107	151	24	‘	'	PUNCT
fcis-15107	151	25	‘	'	PUNCT
fcis-15107	151	26	segmentation	segmentation	NOUN
fcis-15107	151	27	of	of	ADP
fcis-15107	151	28	liver	liver	NOUN
fcis-15107	151	29	vessels	vessel	NOUN
fcis-15107	151	30	as	as	SCONJ
fcis-15107	151	31	seen	see	VERB
fcis-15107	151	32	in	in	ADP
fcis-15107	151	33	mr	mr	PROPN
fcis-15107	151	34	and	and	CCONJ
fcis-15107	151	35	ct	ct	NUM
fcis-15107	151	36	images	image	NOUN
fcis-15107	151	37	,	,	PUNCT
fcis-15107	151	38	’’	’'	PUNCT
fcis-15107	151	39	int	int	NOUN
fcis-15107	151	40	.	.	PUNCT
fcis-15107	152	1	congr	congr	PROPN
fcis-15107	152	2	.	.	PUNCT
fcis-15107	153	1	ser	ser	PROPN
fcis-15107	153	2	.	.	PROPN
fcis-15107	153	3	,	,	PUNCT
fcis-15107	153	4	vol	vol	NOUN
fcis-15107	153	5	.	.	PROPN
fcis-15107	153	6	1268	1268	NUM
fcis-15107	153	7	,	,	PUNCT
fcis-15107	153	8	pp	pp	ADV
fcis-15107	153	9	.	.	PUNCT
fcis-15107	154	1	201–206	201–206	NUM
fcis-15107	154	2	,	,	PUNCT
fcis-15107	154	3	jun	jun	PROPN
fcis-15107	154	4	.	.	PROPN
fcis-15107	154	5	2004	2004	NUM
fcis-15107	154	6	.	.	PUNCT
fcis-15107	155	1	[	[	X
fcis-15107	155	2	online	online	X
fcis-15107	155	3	]	]	X
fcis-15107	155	4	.	.	PUNCT
fcis-15107	156	1	available	available	ADJ
fcis-15107	156	2	:	:	PUNCT
fcis-15107	157	1	http://www	http://www	PROPN
fcis-15107	157	2	.	.	PROPN
fcis-15107	157	3	sciencedirect	sciencedirect	PROPN
fcis-15107	157	4	.	.	PUNCT
fcis-15107	157	5	com	com	NOUN
fcis-15107	157	6	/	/	SYM
fcis-15107	157	7	science/	science/	NUM
fcis-15107	157	8	article	article	NOUN
fcis-15107	157	9	/	/	SYM
fcis-15107	157	10	pii	pii	PROPN
fcis-15107	157	11	/	/	SYM
fcis-15107	157	12	s0531513104006132	s0531513104006132	NOUN
fcis-15107	157	13	.	.	PUNCT
fcis-15107	158	1	34	34	NUM
fcis-15107	159	1	[	[	X
fcis-15107	159	2	2	2	NUM
fcis-15107	159	3	]	]	PUNCT
fcis-15107	159	4	a.	a.	NOUN
fcis-15107	159	5	bert	bert	PROPN
fcis-15107	159	6	et	et	PROPN
fcis-15107	159	7	al	al	PROPN
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fcis-15107	159	11	‘	'	PUNCT
fcis-15107	159	12	an	an	DET
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fcis-15107	159	16	colon	colon	NOUN
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fcis-15107	159	18	in	in	ADP
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fcis-15107	159	21	,	,	PUNCT
fcis-15107	159	22	’’	’'	PUNCT
fcis-15107	159	23	computerized	computerize	VERB
fcis-15107	159	24	med	med	ADJ
fcis-15107	159	25	.	.	PUNCT
fcis-15107	160	1	imag	imag	PROPN
fcis-15107	160	2	.	.	PUNCT
fcis-15107	161	1	graph	graph	NOUN
fcis-15107	161	2	.	.	PUNCT
fcis-15107	161	3	,	,	PUNCT
fcis-15107	161	4	vol	vol	NOUN
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fcis-15107	162	2	,	,	PUNCT
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fcis-15107	162	5	4	4	NUM
fcis-15107	162	6	,	,	PUNCT
fcis-15107	162	7	pp	pp	ADJ
fcis-15107	162	8	.	.	PUNCT
fcis-15107	163	1	325–331	325–331	NUM
fcis-15107	163	2	,	,	PUNCT
fcis-15107	163	3	jun	jun	PROPN
fcis-15107	163	4	.	.	PROPN
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fcis-15107	163	6	.	.	PUNCT
fcis-15107	164	1	[	[	X
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fcis-15107	164	4	.	.	PUNCT
fcis-15107	165	1	available	available	ADJ
fcis-15107	165	2	:	:	PUNCT
fcis-15107	165	3	http://	http://	PROPN
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fcis-15107	165	5	.	.	PUNCT
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fcis-15107	165	9	/	/	SYM
fcis-15107	165	10	article	article	NOUN
fcis-15107	165	11	/	/	SYM
fcis-15107	165	12	pii/	pii/	ADJ
fcis-15107	165	13	s089561110900	s089561110900	ADJ
fcis-15107	165	14	0226	0226	NUM
fcis-15107	166	1	[	[	X
fcis-15107	166	2	3	3	X
fcis-15107	166	3	]	]	PUNCT
fcis-15107	166	4	t.	t.	PROPN
fcis-15107	166	5	klinder	klinder	PROPN
fcis-15107	166	6	,	,	PUNCT
fcis-15107	166	7	j.	j.	PROPN
fcis-15107	166	8	ostermann	ostermann	PROPN
fcis-15107	166	9	,	,	PUNCT
fcis-15107	166	10	m.	m.	NOUN
fcis-15107	166	11	ehm	ehm	PROPN
fcis-15107	166	12	,	,	PUNCT
fcis-15107	166	13	a.	a.	NOUN
fcis-15107	166	14	franz	franz	PROPN
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fcis-15107	166	16	r.	r.	PROPN
fcis-15107	166	17	kneser	kneser	PROPN
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fcis-15107	166	20	c.	c.	PROPN
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fcis-15107	166	22	,	,	PUNCT
fcis-15107	166	23	‘	'	PUNCT
fcis-15107	166	24	‘	'	PUNCT
fcis-15107	166	25	automated	automated	ADJ
fcis-15107	166	26	model	model	NOUN
fcis-15107	166	27	-	-	PUNCT
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fcis-15107	166	29	vertebra	vertebra	NOUN
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fcis-15107	166	33	,	,	PUNCT
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fcis-15107	166	35	segmentation	segmentation	NOUN
fcis-15107	166	36	in	in	ADP
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fcis-15107	166	38	images	image	NOUN
fcis-15107	166	39	,	,	PUNCT
fcis-15107	166	40	’’	’'	PUNCT
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fcis-15107	166	42	.	.	PUNCT
fcis-15107	166	43	image	image	PROPN
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fcis-15107	166	45	.	.	PUNCT
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fcis-15107	166	48	.	.	PROPN
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fcis-15107	166	50	,	,	PUNCT
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fcis-15107	166	54	,	,	PUNCT
fcis-15107	166	55	pp	pp	ADJ
fcis-15107	166	56	.	.	PUNCT
fcis-15107	167	1	471–482	471–482	NUM
fcis-15107	167	2	,	,	PUNCT
fcis-15107	167	3	jun	jun	PROPN
fcis-15107	167	4	.	.	PROPN
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fcis-15107	167	6	.	.	PUNCT
fcis-15107	168	1	[	[	X
fcis-15107	168	2	online	online	X
fcis-15107	168	3	]	]	X
fcis-15107	168	4	.	.	PUNCT
fcis-15107	169	1	available	available	ADJ
fcis-15107	169	2	:	:	PUNCT
fcis-15107	169	3	http://www.sciencedirect.com/science/	http://www.sciencedirect.com/science/	PUNCT
fcis-15107	169	4	article	article	NOUN
fcis-15107	169	5	/	/	SYM
fcis-15107	169	6	pii/	pii/	ADJ
fcis-15107	169	7	s1361841509000085	s1361841509000085	PROPN
fcis-15107	170	1	[	[	X
fcis-15107	170	2	4	4	X
fcis-15107	170	3	]	]	PUNCT
fcis-15107	170	4	h.	h.	PROPN
fcis-15107	170	5	lu	lu	PROPN
fcis-15107	170	6	,	,	PUNCT
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fcis-15107	170	9	,	,	PUNCT
fcis-15107	170	10	m.	m.	PROPN
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fcis-15107	170	12	,	,	PUNCT
fcis-15107	170	13	h.	h.	PROPN
fcis-15107	170	14	kim	kim	PROPN
fcis-15107	170	15	,	,	PUNCT
fcis-15107	170	16	and	and	CCONJ
fcis-15107	170	17	s.	s.	PROPN
fcis-15107	170	18	serikawa	serikawa	PROPN
fcis-15107	170	19	,	,	PUNCT
fcis-15107	170	20	‘	'	PUNCT
fcis-15107	170	21	‘	'	PUNCT
fcis-15107	170	22	brain	brain	NOUN
fcis-15107	170	23	intelligence	intelligence	NOUN
fcis-15107	170	24	:	:	PUNCT
fcis-15107	170	25	go	go	VERB
fcis-15107	170	26	beyond	beyond	ADP
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fcis-15107	170	28	intelligence	intelligence	NOUN
fcis-15107	170	29	,	,	PUNCT
fcis-15107	170	30	’’	’'	PUNCT
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fcis-15107	170	33	.	.	PUNCT
fcis-15107	171	1	appl	appl	PROPN
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fcis-15107	171	10	2	2	NUM
fcis-15107	171	11	,	,	PUNCT
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fcis-15107	171	13	.	.	PUNCT
fcis-15107	172	1	368–375	368–375	NUM
fcis-15107	172	2	,	,	PUNCT
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fcis-15107	172	4	.	.	PROPN
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fcis-15107	172	6	.	.	PUNCT
fcis-15107	173	1	doi	doi	NOUN
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fcis-15107	173	4	s11036	s11036	NOUN
fcis-15107	173	5	-	-	PUNCT
fcis-15107	173	6	017	017	NUM
fcis-15107	173	7	-	-	PUNCT
fcis-15107	173	8	0932	0932	NUM
fcis-15107	173	9	-	-	SYM
fcis-15107	173	10	8	8	NUM
fcis-15107	173	11	.	.	PUNCT
fcis-15107	174	1	[	[	X
fcis-15107	174	2	5	5	NUM
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fcis-15107	174	6	,	,	PUNCT
fcis-15107	174	7	x.	x.	PROPN
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fcis-15107	174	9	,	,	PUNCT
fcis-15107	174	10	y.	y.	PROPN
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fcis-15107	174	18	guizani	guizani	NOUN
fcis-15107	174	19	,	,	PUNCT
fcis-15107	174	20	‘	'	PUNCT
fcis-15107	174	21	‘	'	PUNCT
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fcis-15107	174	27	image	image	NOUN
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fcis-15107	175	7	.	.	PUNCT
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fcis-15107	176	4	y.	y.	PROPN
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fcis-15107	176	9	,	,	PUNCT
fcis-15107	176	10	c.-w	c.-w	PROPN
fcis-15107	176	11	.	.	PUNCT
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fcis-15107	177	2	,	,	PUNCT
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fcis-15107	177	12	‘	'	PUNCT
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fcis-15107	177	14	:	:	PUNCT
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fcis-15107	177	30	.	.	PUNCT
fcis-15107	178	1	j.	j.	PROPN
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fcis-15107	178	4	.	.	PROPN
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fcis-15107	178	10	,	,	PUNCT
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fcis-15107	178	12	.	.	PUNCT
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fcis-15107	179	2	,	,	PUNCT
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fcis-15107	179	6	.	.	PUNCT
fcis-15107	180	1	[	[	X
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fcis-15107	180	3	]	]	X
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fcis-15107	180	11	t.	t.	PROPN
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fcis-15107	180	14	‘	'	PUNCT
fcis-15107	180	15	‘	'	PUNCT
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fcis-15107	180	21	segmentation	segmentation	NOUN
fcis-15107	180	22	,	,	PUNCT
fcis-15107	180	23	’’	’'	PUNCT
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fcis-15107	180	25	proc	proc	NOUN
fcis-15107	180	26	.	.	PUNCT
fcis-15107	181	1	ieee	ieee	NOUN
fcis-15107	181	2	conf	conf	NOUN
fcis-15107	181	3	.	.	PUNCT
fcis-15107	182	1	comput	comput	NOUN
fcis-15107	182	2	.	.	PUNCT
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fcis-15107	183	2	.	.	X
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fcis-15107	183	5	.	.	PUNCT
fcis-15107	184	1	(	(	PUNCT
fcis-15107	184	2	cvpr	cvpr	NOUN
fcis-15107	184	3	)	)	PUNCT
fcis-15107	184	4	,	,	PUNCT
fcis-15107	184	5	jun	jun	PROPN
fcis-15107	184	6	.	.	PROPN
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fcis-15107	184	8	,	,	PUNCT
fcis-15107	184	9	pp	pp	ADJ
fcis-15107	184	10	.	.	PUNCT
fcis-15107	185	1	3431	3431	NUM
fcis-15107	185	2	–	–	PUNCT
fcis-15107	185	3	3440	3440	NUM
fcis-15107	185	4	.	.	PUNCT
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fcis-15107	186	19	:	:	PUNCT
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fcis-15107	186	30	.	.	PUNCT
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fcis-15107	187	2	.	.	PUNCT
fcis-15107	187	3	conf	conf	PROPN
fcis-15107	187	4	.	.	PUNCT
fcis-15107	188	1	med	med	PROPN
fcis-15107	188	2	.	.	PUNCT
fcis-15107	189	1	image	image	NOUN
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fcis-15107	189	3	.	.	PUNCT
fcis-15107	190	1	comput	comput	NOUN
fcis-15107	190	2	-	-	PUNCT
fcis-15107	190	3	assist	assist	NOUN
fcis-15107	190	4	.	.	PUNCT
fcis-15107	191	1	intervent	intervent	NOUN
fcis-15107	191	2	.	.	PUNCT
fcis-15107	192	1	(	(	PUNCT
fcis-15107	192	2	miccai	miccai	PROPN
fcis-15107	192	3	)	)	PUNCT
fcis-15107	192	4	,	,	PUNCT
fcis-15107	192	5	nov	nov	PROPN
fcis-15107	192	6	.	.	PROPN
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fcis-15107	192	8	,	,	PUNCT
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fcis-15107	193	1	234–241	234–241	NUM
fcis-15107	193	2	.	.	PUNCT
fcis-15107	194	1	[	[	X
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fcis-15107	194	4	y.	y.	NOUN
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fcis-15107	194	7	l.	l.	PROPN
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fcis-15107	194	10	y.	y.	PROPN
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fcis-15107	194	13	and	and	CCONJ
fcis-15107	194	14	p.	p.	PROPN
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fcis-15107	194	16	,	,	PUNCT
fcis-15107	194	17	‘	'	PUNCT
fcis-15107	194	18	‘	'	PUNCT
fcis-15107	194	19	gradientbased	gradientbased	ADJ
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fcis-15107	194	22	to	to	ADP
fcis-15107	194	23	document	document	NOUN
fcis-15107	194	24	recognition	recognition	NOUN
fcis-15107	194	25	,	,	PUNCT
fcis-15107	194	26	’’	’'	PUNCT
fcis-15107	194	27	proc	proc	NOUN
fcis-15107	194	28	.	.	PUNCT
fcis-15107	195	1	ieee	ieee	NOUN
fcis-15107	195	2	,	,	PUNCT
fcis-15107	195	3	vol	vol	NOUN
fcis-15107	195	4	.	.	PROPN
fcis-15107	195	5	86	86	NUM
fcis-15107	195	6	,	,	PUNCT
fcis-15107	195	7	no	no	INTJ
fcis-15107	195	8	.	.	NOUN
fcis-15107	195	9	11	11	NUM
fcis-15107	195	10	,	,	PUNCT
fcis-15107	195	11	pp	pp	ADJ
fcis-15107	195	12	.	.	PUNCT
fcis-15107	196	1	2278–2324	2278–2324	NUM
fcis-15107	196	2	,	,	PUNCT
fcis-15107	196	3	nov	nov	PROPN
fcis-15107	196	4	.	.	PROPN
fcis-15107	196	5	1998	1998	NUM
fcis-15107	196	6	.	.	PUNCT
fcis-15107	197	1	[	[	X
fcis-15107	197	2	10	10	NUM
fcis-15107	197	3	]	]	PUNCT
fcis-15107	197	4	a.	a.	NOUN
fcis-15107	197	5	krizhevsky	krizhevsky	PROPN
fcis-15107	197	6	,	,	PUNCT
fcis-15107	197	7	i.	i.	PROPN
fcis-15107	197	8	sutskever	sutskever	PROPN
fcis-15107	197	9	,	,	PUNCT
fcis-15107	197	10	and	and	CCONJ
fcis-15107	197	11	g.	g.	PROPN
fcis-15107	197	12	e.	e.	PROPN
fcis-15107	197	13	hinton	hinton	PROPN
fcis-15107	197	14	,	,	PUNCT
fcis-15107	197	15	‘	'	PUNCT
fcis-15107	197	16	‘	'	PUNCT
fcis-15107	197	17	imagenet	imagenet	ADJ
fcis-15107	197	18	classification	classification	NOUN
fcis-15107	197	19	with	with	ADP
fcis-15107	197	20	deep	deep	ADJ
fcis-15107	197	21	convolutional	convolutional	ADJ
fcis-15107	197	22	neural	neural	ADJ
fcis-15107	197	23	networks	network	NOUN
fcis-15107	197	24	,	,	PUNCT
fcis-15107	197	25	’’	’'	PUNCT
fcis-15107	197	26	commun	commun	PROPN
fcis-15107	197	27	.	.	PUNCT
fcis-15107	197	28	acm	acm	PROPN
fcis-15107	197	29	,	,	PUNCT
fcis-15107	197	30	vol	vol	NOUN
fcis-15107	197	31	.	.	PROPN
fcis-15107	197	32	60	60	NUM
fcis-15107	197	33	,	,	PUNCT
fcis-15107	197	34	no	no	INTJ
fcis-15107	197	35	.	.	NOUN
fcis-15107	197	36	6	6	NUM
fcis-15107	197	37	,	,	PUNCT
fcis-15107	197	38	pp	pp	PROPN
fcis-15107	197	39	.	.	PUNCT
fcis-15107	197	40	84–90	84–90	NUM
fcis-15107	197	41	,	,	PUNCT
fcis-15107	197	42	jun	jun	PROPN
fcis-15107	197	43	.	.	PROPN
fcis-15107	197	44	2012	2012	NUM
fcis-15107	197	45	.	.	PUNCT
fcis-15107	198	1	[	[	X
fcis-15107	198	2	11	11	NUM
fcis-15107	198	3	]	]	SYM
fcis-15107	198	4	jha	jha	PROPN
fcis-15107	198	5	,	,	PUNCT
fcis-15107	198	6	d.	d.	PROPN
fcis-15107	198	7	,	,	PUNCT
fcis-15107	198	8	et	et	PROPN
fcis-15107	198	9	al	al	PROPN
fcis-15107	198	10	.	.	PROPN
fcis-15107	198	11	doubleu	doubleu	PROPN
fcis-15107	198	12	-	-	PUNCT
fcis-15107	198	13	net	net	NOUN
fcis-15107	198	14	:	:	PUNCT
fcis-15107	198	15	a	a	DET
fcis-15107	198	16	deep	deep	ADJ
fcis-15107	198	17	convolutional	convolutional	ADJ
fcis-15107	198	18	neural	neural	ADJ
fcis-15107	198	19	network	network	NOUN
fcis-15107	198	20	for	for	ADP
fcis-15107	198	21	medical	medical	ADJ
fcis-15107	198	22	image	image	NOUN
fcis-15107	198	23	segmentation	segmentation	NOUN
fcis-15107	198	24	.	.	PUNCT
fcis-15107	199	1	in	in	ADP
fcis-15107	199	2	2020	2020	NUM
fcis-15107	199	3	ieee	ieee	NOUN
fcis-15107	199	4	33rd	33rd	ADJ
fcis-15107	199	5	international	international	ADJ
fcis-15107	199	6	symposium	symposium	NOUN
fcis-15107	199	7	on	on	ADP
fcis-15107	199	8	computer	computer	NOUN
fcis-15107	199	9	-	-	PUNCT
fcis-15107	199	10	based	base	VERB
fcis-15107	199	11	medical	medical	ADJ
fcis-15107	199	12	systems	system	NOUN
fcis-15107	199	13	(	(	PUNCT
fcis-15107	199	14	cbms	cbms	PROPN
fcis-15107	199	15	)	)	PUNCT
fcis-15107	199	16	(	(	PUNCT
fcis-15107	199	17	2020	2020	NUM
fcis-15107	199	18	)	)	PUNCT
fcis-15107	199	19	.	.	PUNCT
fcis-15107	200	1	[	[	X
fcis-15107	200	2	12	12	NUM
fcis-15107	200	3	]	]	X
fcis-15107	200	4	liu	liu	PROPN
fcis-15107	200	5	,	,	PUNCT
fcis-15107	200	6	t.	t.	PROPN
fcis-15107	200	7	et	et	PROPN
fcis-15107	200	8	al	al	PROPN
fcis-15107	200	9	.	.	PUNCT
fcis-15107	201	1	residual	residual	ADJ
fcis-15107	201	2	convolutional	convolutional	ADJ
fcis-15107	201	3	neural	neural	ADJ
fcis-15107	201	4	network	network	NOUN
fcis-15107	201	5	for	for	ADP
fcis-15107	201	6	cardiac	cardiac	ADJ
fcis-15107	201	7	image	image	NOUN
fcis-15107	201	8	segmentation	segmentation	NOUN
fcis-15107	201	9	and	and	CCONJ
fcis-15107	201	10	heart	heart	NOUN
fcis-15107	201	11	disease	disease	NOUN
fcis-15107	201	12	diagnosis	diagnosis	NOUN
fcis-15107	201	13	.	.	PUNCT
fcis-15107	202	1	ieee	ieee	NOUN
fcis-15107	202	2	access	access	NOUN
fcis-15107	202	3	.	.	PUNCT
fcis-15107	203	1	8	8	NUM
fcis-15107	203	2	,	,	PUNCT
fcis-15107	203	3	82153–82161	82153–82161	NUM
fcis-15107	203	4	(	(	PUNCT
fcis-15107	203	5	2020	2020	NUM
fcis-15107	203	6	)	)	PUNCT
fcis-15107	203	7	.	.	PUNCT
fcis-15107	204	1	[	[	X
fcis-15107	204	2	13	13	NUM
fcis-15107	204	3	]	]	SYM
fcis-15107	204	4	wu	wu	PROPN
fcis-15107	204	5	,	,	PUNCT
fcis-15107	204	6	b.	b.	PROPN
fcis-15107	204	7	,	,	PUNCT
fcis-15107	204	8	fang	fang	PROPN
fcis-15107	204	9	,	,	PUNCT
fcis-15107	204	10	y.	y.	PROPN
fcis-15107	204	11	&	&	CCONJ
fcis-15107	204	12	lai	lai	PROPN
fcis-15107	204	13	,	,	PUNCT
fcis-15107	204	14	x.	x.	PROPN
fcis-15107	204	15	lef	lef	PROPN
fcis-15107	204	16	ventricle	ventricle	NOUN
fcis-15107	204	17	automatic	automatic	ADJ
fcis-15107	204	18	segmentation	segmentation	NOUN
fcis-15107	204	19	in	in	ADP
fcis-15107	204	20	cardiac	cardiac	ADJ
fcis-15107	204	21	mri	mri	NOUN
fcis-15107	204	22	using	use	VERB
fcis-15107	204	23	a	a	DET
fcis-15107	204	24	combined	combined	ADJ
fcis-15107	204	25	cnn	cnn	NOUN
fcis-15107	204	26	and	and	CCONJ
fcis-15107	204	27	unet	unet	NOUN
fcis-15107	204	28	approach	approach	NOUN
fcis-15107	204	29	.	.	PUNCT
fcis-15107	205	1	comput	comput	NOUN
fcis-15107	205	2	.	.	PUNCT
fcis-15107	206	1	med	med	PROPN
fcis-15107	206	2	.	.	PUNCT
fcis-15107	207	1	imaging	imaging	NOUN
fcis-15107	207	2	graph	graph	NOUN
fcis-15107	207	3	.	.	PUNCT
fcis-15107	208	1	82	82	NUM
fcis-15107	208	2	,	,	PUNCT
fcis-15107	208	3	101719	101719	NUM
fcis-15107	208	4	(	(	PUNCT
fcis-15107	208	5	2020	2020	NUM
fcis-15107	208	6	)	)	PUNCT
fcis-15107	208	7	.	.	PUNCT
fcis-15107	209	1	[	[	X
fcis-15107	209	2	14	14	NUM
fcis-15107	209	3	]	]	X
fcis-15107	209	4	galati	galati	PROPN
fcis-15107	209	5	,	,	PUNCT
fcis-15107	209	6	f.	f.	PROPN
fcis-15107	209	7	&	&	CCONJ
fcis-15107	209	8	zuluaga	zuluaga	PROPN
fcis-15107	209	9	,	,	PUNCT
fcis-15107	209	10	m.	m.	NOUN
fcis-15107	209	11	a.	a.	NOUN
fcis-15107	209	12	efcient	efcient	NOUN
fcis-15107	209	13	model	model	NOUN
fcis-15107	209	14	monitoring	monitoring	NOUN
fcis-15107	209	15	for	for	ADP
fcis-15107	209	16	quality	quality	NOUN
fcis-15107	209	17	control	control	NOUN
fcis-15107	209	18	in	in	ADP
fcis-15107	209	19	cardiac	cardiac	ADJ
fcis-15107	209	20	image	image	NOUN
fcis-15107	209	21	segmentation	segmentation	NOUN
fcis-15107	209	22	.	.	PUNCT
fcis-15107	210	1	fimh	fimh	NOUN
fcis-15107	210	2	20	20	NUM
fcis-15107	210	3	,	,	PUNCT
fcis-15107	210	4	101	101	NUM
fcis-15107	210	5	–	–	SYM
fcis-15107	210	6	111	111	NUM
fcis-15107	210	7	(	(	PUNCT
fcis-15107	210	8	2021	2021	NUM
fcis-15107	210	9	)	)	PUNCT
fcis-15107	210	10	.	.	PUNCT
fcis-15107	211	1	[	[	X
fcis-15107	211	2	15	15	NUM
fcis-15107	211	3	]	]	X
fcis-15107	211	4	ronneberger	ronneberger	NOUN
fcis-15107	211	5	,	,	PUNCT
fcis-15107	211	6	o.	o.	PROPN
fcis-15107	211	7	,	,	PUNCT
fcis-15107	211	8	fischer	fischer	PROPN
fcis-15107	211	9	,	,	PUNCT
fcis-15107	211	10	p.	p.	PROPN
fcis-15107	211	11	,	,	PUNCT
fcis-15107	211	12	&	&	CCONJ
fcis-15107	211	13	brox	brox	PROPN
fcis-15107	211	14	,	,	PUNCT
fcis-15107	211	15	t.	t.	PROPN
fcis-15107	211	16	u	u	PROPN
fcis-15107	211	17	-	-	NOUN
fcis-15107	211	18	net	net	ADJ
fcis-15107	211	19	:	:	PUNCT
fcis-15107	211	20	convolutional	convolutional	ADJ
fcis-15107	211	21	networks	network	NOUN
fcis-15107	211	22	for	for	ADP
fcis-15107	211	23	biomedical	biomedical	ADJ
fcis-15107	211	24	image	image	NOUN
fcis-15107	211	25	segmentation	segmentation	NOUN
fcis-15107	211	26	.	.	PUNCT
fcis-15107	212	1	in	in	ADP
fcis-15107	212	2	miccai	miccai	PROPN
fcis-15107	212	3	2015	2015	NUM
fcis-15107	212	4	.	.	PUNCT
fcis-15107	213	1	part	part	NOUN
fcis-15107	213	2	iii	iii	NUM
fcis-15107	213	3	18	18	NUM
fcis-15107	213	4	,	,	PUNCT
fcis-15107	213	5	234–241	234–241	NUM
fcis-15107	213	6	(	(	PUNCT
fcis-15107	213	7	2015	2015	NUM
fcis-15107	213	8	)	)	PUNCT
fcis-15107	213	9	.	.	PUNCT
fcis-15107	214	1	[	[	X
fcis-15107	214	2	16	16	NUM
fcis-15107	214	3	]	]	X
fcis-15107	214	4	milletari	milletari	PROPN
fcis-15107	214	5	,	,	PUNCT
fcis-15107	214	6	f.	f.	PROPN
fcis-15107	214	7	,	,	PUNCT
fcis-15107	214	8	navab	navab	PROPN
fcis-15107	214	9	,	,	PUNCT
fcis-15107	214	10	n.	n.	NOUN
fcis-15107	214	11	,	,	PUNCT
fcis-15107	214	12	&	&	CCONJ
fcis-15107	214	13	ahmadi	ahmadi	PROPN
fcis-15107	214	14	,	,	PUNCT
fcis-15107	214	15	s.	s.	PROPN
fcis-15107	214	16	a.	a.	PROPN
fcis-15107	214	17	v	v	PROPN
fcis-15107	214	18	-	-	PUNCT
fcis-15107	214	19	net	net	NOUN
fcis-15107	214	20	:	:	PUNCT
fcis-15107	214	21	fully	fully	ADV
fcis-15107	214	22	convolutional	convolutional	ADJ
fcis-15107	214	23	neural	neural	ADJ
fcis-15107	214	24	networks	network	NOUN
fcis-15107	214	25	for	for	ADP
fcis-15107	214	26	volumetric	volumetric	ADJ
fcis-15107	214	27	medical	medical	ADJ
fcis-15107	214	28	image	image	NOUN
fcis-15107	214	29	segmentation	segmentation	NOUN
fcis-15107	214	30	.	.	PUNCT
fcis-15107	215	1	in	in	ADP
fcis-15107	215	2	2016	2016	NUM
fcis-15107	215	3	fourth	fourth	ADJ
fcis-15107	215	4	international	international	ADJ
fcis-15107	215	5	conference	conference	NOUN
fcis-15107	215	6	on	on	ADP
fcis-15107	215	7	3d	3d	PROPN
fcis-15107	215	8	vision	vision	NOUN
fcis-15107	215	9	(	(	PUNCT
fcis-15107	215	10	3dv	3dv	NOUN
fcis-15107	215	11	)	)	PUNCT
fcis-15107	215	12	.	.	PUNCT
fcis-15107	216	1	565–571	565–571	NUM
fcis-15107	216	2	(	(	PUNCT
fcis-15107	216	3	2016	2016	NUM
fcis-15107	216	4	)	)	PUNCT
fcis-15107	216	5	.	.	PUNCT
fcis-15107	217	1	[	[	X
fcis-15107	217	2	17	17	NUM
fcis-15107	217	3	]	]	X
fcis-15107	217	4	zhou	zhou	PROPN
fcis-15107	217	5	,	,	PUNCT
fcis-15107	217	6	z.	z.	PROPN
fcis-15107	217	7	,	,	PUNCT
fcis-15107	217	8	et	et	PROPN
fcis-15107	217	9	al	al	PROPN
fcis-15107	217	10	.	.	PUNCT
fcis-15107	218	1	unet++	unet++	PROPN
fcis-15107	218	2	:	:	PUNCT
fcis-15107	218	3	a	a	DET
fcis-15107	218	4	nested	nested	ADJ
fcis-15107	218	5	u	u	ADJ
fcis-15107	218	6	-	-	ADJ
fcis-15107	218	7	net	net	ADJ
fcis-15107	218	8	architecture	architecture	NOUN
fcis-15107	218	9	for	for	ADP
fcis-15107	218	10	medical	medical	ADJ
fcis-15107	218	11	image	image	NOUN
fcis-15107	218	12	segmentation	segmentation	NOUN
fcis-15107	218	13	.	.	PUNCT
fcis-15107	219	1	dlmia	dlmia	PROPN
fcis-15107	219	2	/	/	SYM
fcis-15107	219	3	ml	ml	NOUN
fcis-15107	219	4	-	-	PUNCT
fcis-15107	219	5	cds@miccai	cds@miccai	NOUN
fcis-15107	219	6	2018	2018	NUM
fcis-15107	219	7	.	.	PUNCT
fcis-15107	220	1	3–11	3–11	NOUN
fcis-15107	220	2	(	(	PUNCT
fcis-15107	220	3	2018	2018	NUM
fcis-15107	220	4	)	)	PUNCT
fcis-15107	220	5	.	.	PUNCT
fcis-15107	221	1	[	[	X
fcis-15107	221	2	18	18	NUM
fcis-15107	221	3	]	]	X
fcis-15107	221	4	zhang	zhang	PROPN
fcis-15107	221	5	,	,	PUNCT
fcis-15107	221	6	j.	j.	PROPN
fcis-15107	221	7	,	,	PUNCT
fcis-15107	221	8	et	et	PROPN
fcis-15107	221	9	al	al	PROPN
fcis-15107	221	10	.	.	PROPN
fcis-15107	221	11	mdu	mdu	PROPN
fcis-15107	221	12	-	-	PUNCT
fcis-15107	221	13	net	net	ADJ
fcis-15107	221	14	:	:	PUNCT
fcis-15107	221	15	multi	multi	ADJ
fcis-15107	221	16	-	-	ADJ
fcis-15107	221	17	scale	scale	ADJ
fcis-15107	221	18	densely	densely	ADV
fcis-15107	221	19	connected	connect	VERB
fcis-15107	221	20	unet	unet	NOUN
fcis-15107	221	21	for	for	ADP
fcis-15107	221	22	biomedical	biomedical	ADJ
fcis-15107	221	23	image	image	NOUN
fcis-15107	221	24	segmentation	segmentation	NOUN
fcis-15107	221	25	.	.	PUNCT
fcis-15107	222	1	arxiv:1812.00352	arxiv:1812.00352	PROPN
fcis-15107	222	2	(	(	PUNCT
fcis-15107	222	3	arxiv	arxiv	PROPN
fcis-15107	222	4	preprint	preprint	NOUN
fcis-15107	222	5	)	)	PUNCT
fcis-15107	222	6	(	(	PUNCT
fcis-15107	222	7	2018	2018	NUM
fcis-15107	222	8	)	)	PUNCT
fcis-15107	222	9	.	.	PUNCT
fcis-15107	223	1	[	[	X
fcis-15107	223	2	19	19	NUM
fcis-15107	223	3	]	]	SYM
fcis-15107	223	4	hu	hu	PROPN
fcis-15107	223	5	,	,	PUNCT
fcis-15107	223	6	j.	j.	PROPN
fcis-15107	223	7	,	,	PUNCT
fcis-15107	223	8	shen	shen	PROPN
fcis-15107	223	9	,	,	PUNCT
fcis-15107	223	10	l.	l.	PROPN
fcis-15107	223	11	,	,	PUNCT
fcis-15107	223	12	&	&	CCONJ
fcis-15107	223	13	sun	sun	PROPN
fcis-15107	223	14	,	,	PUNCT
fcis-15107	223	15	g.	g.	PROPN
fcis-15107	223	16	squeeze	squeeze	NOUN
fcis-15107	223	17	-	-	PUNCT
fcis-15107	223	18	and	and	CCONJ
fcis-15107	223	19	-	-	PUNCT
fcis-15107	223	20	excitation	excitation	NOUN
fcis-15107	223	21	networks	network	NOUN
fcis-15107	223	22	.	.	PUNCT
fcis-15107	224	1	in	in	ADP
fcis-15107	224	2	2018	2018	NUM
fcis-15107	224	3	ieee	ieee	NOUN
fcis-15107	224	4	/	/	SYM
fcis-15107	224	5	cvf	cvf	NOUN
fcis-15107	224	6	conference	conference	NOUN
fcis-15107	224	7	on	on	ADP
fcis-15107	224	8	computer	computer	NOUN
fcis-15107	224	9	vision	vision	NOUN
fcis-15107	224	10	and	and	CCONJ
fcis-15107	224	11	pattern	pattern	NOUN
fcis-15107	224	12	recognition	recognition	NOUN
fcis-15107	224	13	.	.	PUNCT
fcis-15107	225	1	7132–7141	7132–7141	NUM
fcis-15107	225	2	(	(	PUNCT
fcis-15107	225	3	2018	2018	NUM
fcis-15107	225	4	)	)	PUNCT
fcis-15107	225	5	.	.	PUNCT
fcis-15107	226	1	[	[	X
fcis-15107	226	2	20	20	NUM
fcis-15107	226	3	]	]	X
fcis-15107	226	4	hou	hou	PROPN
fcis-15107	226	5	,	,	PUNCT
fcis-15107	226	6	q.	q.	PROPN
fcis-15107	226	7	,	,	PUNCT
fcis-15107	226	8	zhou	zhou	PROPN
fcis-15107	226	9	,	,	PUNCT
fcis-15107	226	10	d.	d.	PROPN
fcis-15107	226	11	,	,	PUNCT
fcis-15107	226	12	&	&	CCONJ
fcis-15107	226	13	feng	feng	PROPN
fcis-15107	226	14	,	,	PUNCT
fcis-15107	226	15	j.	j.	PROPN
fcis-15107	226	16	coordinate	coordinate	VERB
fcis-15107	226	17	attention	attention	NOUN
fcis-15107	226	18	for	for	ADP
fcis-15107	226	19	efcient	efcient	NOUN
fcis-15107	226	20	mobile	mobile	NOUN
fcis-15107	226	21	network	network	NOUN
fcis-15107	226	22	design	design	NOUN
fcis-15107	226	23	.	.	PUNCT
fcis-15107	227	1	in	in	ADP
fcis-15107	227	2	2021	2021	NUM
fcis-15107	227	3	ieee	ieee	NOUN
fcis-15107	227	4	/	/	SYM
fcis-15107	227	5	cvf	cvf	NOUN
fcis-15107	227	6	conference	conference	NOUN
fcis-15107	227	7	on	on	ADP
fcis-15107	227	8	computer	computer	NOUN
fcis-15107	227	9	vision	vision	NOUN
fcis-15107	227	10	and	and	CCONJ
fcis-15107	227	11	pattern	pattern	NOUN
fcis-15107	227	12	recognition	recognition	NOUN
fcis-15107	227	13	(	(	PUNCT
fcis-15107	227	14	cvpr	cvpr	NOUN
fcis-15107	227	15	)	)	PUNCT
fcis-15107	227	16	.	.	PUNCT
fcis-15107	227	17	13708	13708	NUM
fcis-15107	227	18	–	–	PUNCT
fcis-15107	227	19	13717	13717	NUM
fcis-15107	227	20	(	(	PUNCT
fcis-15107	227	21	2021	2021	NUM
fcis-15107	227	22	)	)	PUNCT
fcis-15107	227	23	.	.	PUNCT
fcis-15107	228	1	[	[	X
fcis-15107	228	2	21	21	NUM
fcis-15107	228	3	]	]	X
fcis-15107	228	4	woo	woo	PROPN
fcis-15107	228	5	,	,	PUNCT
fcis-15107	228	6	s.	s.	PROPN
fcis-15107	228	7	,	,	PUNCT
fcis-15107	228	8	park	park	PROPN
fcis-15107	228	9	,	,	PUNCT
fcis-15107	228	10	j.	j.	PROPN
fcis-15107	228	11	,	,	PUNCT
fcis-15107	228	12	lee	lee	PROPN
fcis-15107	228	13	,	,	PUNCT
fcis-15107	228	14	j.	j.	PROPN
fcis-15107	228	15	y.	y.	PROPN
fcis-15107	228	16	,	,	PUNCT
fcis-15107	228	17	&	&	CCONJ
fcis-15107	228	18	kweon	kweon	PROPN
fcis-15107	228	19	,	,	PUNCT
fcis-15107	228	20	i.	i.	PROPN
fcis-15107	228	21	s.	s.	PROPN
fcis-15107	228	22	cbam	cbam	PROPN
fcis-15107	228	23	:	:	PUNCT
fcis-15107	228	24	convolutional	convolutional	ADJ
fcis-15107	228	25	block	block	NOUN
fcis-15107	228	26	attention	attention	NOUN
fcis-15107	228	27	module	module	NOUN
fcis-15107	228	28	.	.	PUNCT
fcis-15107	229	1	in	in	ADP
fcis-15107	229	2	proceedings	proceeding	NOUN
fcis-15107	229	3	of	of	ADP
fcis-15107	229	4	the	the	DET
fcis-15107	229	5	european	european	PROPN
fcis-15107	229	6	conference	conference	PROPN
fcis-15107	229	7	on	on	ADP
fcis-15107	229	8	computer	computer	NOUN
fcis-15107	229	9	vision	vision	NOUN
fcis-15107	229	10	(	(	PUNCT
fcis-15107	229	11	eccv	eccv	ADV
fcis-15107	229	12	)	)	PUNCT
fcis-15107	229	13	(	(	PUNCT
fcis-15107	229	14	2018	2018	NUM
fcis-15107	229	15	)	)	PUNCT
fcis-15107	229	16	.	.	PUNCT
fcis-15107	230	1	[	[	X
fcis-15107	230	2	22	22	NUM
fcis-15107	230	3	]	]	X
fcis-15107	230	4	tu	tu	PROPN
fcis-15107	230	5	,	,	PUNCT
fcis-15107	230	6	z.	z.	PROPN
fcis-15107	230	7	,	,	PUNCT
fcis-15107	230	8	et	et	PROPN
fcis-15107	230	9	al	al	PROPN
fcis-15107	230	10	.	.	PROPN
fcis-15107	230	11	maxim	maxim	NOUN
fcis-15107	230	12	:	:	PUNCT
fcis-15107	230	13	multi	multi	ADJ
fcis-15107	230	14	-	-	ADJ
fcis-15107	230	15	axis	axis	ADJ
fcis-15107	230	16	mlp	mlp	NOUN
fcis-15107	230	17	for	for	ADP
fcis-15107	230	18	image	image	NOUN
fcis-15107	230	19	processing[c	processing[c	NOUN
fcis-15107	230	20	]	]	PUNCT
fcis-15107	230	21	.	.	PUNCT
fcis-15107	231	1	in	in	ADP
fcis-15107	231	2	proceedings	proceeding	NOUN
fcis-15107	231	3	of	of	ADP
fcis-15107	231	4	the	the	DET
fcis-15107	231	5	ieee	ieee	NOUN
fcis-15107	231	6	/	/	SYM
fcis-15107	231	7	cvf	cvf	NOUN
fcis-15107	231	8	conference	conference	NOUN
fcis-15107	231	9	on	on	ADP
fcis-15107	231	10	computer	computer	NOUN
fcis-15107	231	11	vision	vision	NOUN
fcis-15107	231	12	and	and	CCONJ
fcis-15107	231	13	pattern	pattern	NOUN
fcis-15107	231	14	recognition	recognition	NOUN
fcis-15107	231	15	.	.	PUNCT
fcis-15107	232	1	5769–5780	5769–5780	NUM
fcis-15107	232	2	(	(	PUNCT
fcis-15107	232	3	2022	2022	NUM
fcis-15107	232	4	)	)	PUNCT
fcis-15107	232	5	.	.	PUNCT
fcis-15107	233	1	[	[	X
fcis-15107	233	2	23	23	NUM
fcis-15107	233	3	]	]	X
fcis-15107	233	4	valanarasu	valanarasu	PROPN
fcis-15107	233	5	,	,	PUNCT
fcis-15107	233	6	j.	j.	PROPN
fcis-15107	233	7	m.	m.	PROPN
fcis-15107	233	8	j.	j.	PROPN
fcis-15107	233	9	&	&	CCONJ
fcis-15107	233	10	patel	patel	PROPN
fcis-15107	233	11	,	,	PUNCT
fcis-15107	233	12	v.	v.	ADP
fcis-15107	234	1	m.	m.	NOUN
fcis-15107	234	2	unext	unext	PROPN
fcis-15107	234	3	:	:	PUNCT
fcis-15107	234	4	mlp	mlp	NOUN
fcis-15107	234	5	-	-	PUNCT
fcis-15107	234	6	based	base	VERB
fcis-15107	234	7	rapid	rapid	ADJ
fcis-15107	234	8	medical	medical	ADJ
fcis-15107	234	9	image	image	NOUN
fcis-15107	234	10	segmentation	segmentation	NOUN
fcis-15107	234	11	network	network	NOUN
fcis-15107	234	12	.	.	PUNCT
fcis-15107	235	1	miccai	miccai	PROPN
fcis-15107	235	2	5	5	NUM
fcis-15107	235	3	,	,	PUNCT
fcis-15107	235	4	23–33	23–33	NUM
fcis-15107	235	5	(	(	PUNCT
fcis-15107	235	6	2022	2022	NUM
fcis-15107	235	7	)	)	PUNCT
fcis-15107	235	8	.	.	PUNCT
fcis-15107	236	1	[	[	X
fcis-15107	236	2	24	24	NUM
fcis-15107	236	3	]	]	SYM
fcis-15107	236	4	tyagi	tyagi	PROPN
fcis-15107	236	5	,	,	PUNCT
fcis-15107	236	6	t.	t.	PROPN
fcis-15107	236	7	,	,	PUNCT
fcis-15107	236	8	gupta	gupta	PROPN
fcis-15107	236	9	,	,	PUNCT
fcis-15107	236	10	p.	p.	NOUN
fcis-15107	236	11	,	,	PUNCT
fcis-15107	236	12	&	&	CCONJ
fcis-15107	236	13	singh	singh	PROPN
fcis-15107	236	14	,	,	PUNCT
fcis-15107	236	15	p.	p.	NOUN
fcis-15107	236	16	a	a	DET
fcis-15107	236	17	hybrid	hybrid	ADJ
fcis-15107	236	18	multi	multi	ADJ
fcis-15107	236	19	-	-	ADJ
fcis-15107	236	20	focus	focus	ADJ
fcis-15107	236	21	image	image	NOUN
fcis-15107	236	22	fusion	fusion	NOUN
fcis-15107	236	23	technique	technique	NOUN
fcis-15107	236	24	using	use	VERB
fcis-15107	236	25	swt	swt	PROPN
fcis-15107	236	26	and	and	CCONJ
fcis-15107	236	27	pca	pca	PROPN
fcis-15107	236	28	.	.	PUNCT
fcis-15107	237	1	in	in	ADP
fcis-15107	237	2	2020	2020	NUM
fcis-15107	237	3	10th	10th	ADJ
fcis-15107	237	4	international	international	ADJ
fcis-15107	237	5	conference	conference	NOUN
fcis-15107	237	6	on	on	ADP
fcis-15107	237	7	cloud	cloud	NOUN
fcis-15107	237	8	computing	computing	NOUN
fcis-15107	237	9	,	,	PUNCT
fcis-15107	237	10	data	data	NOUN
fcis-15107	237	11	science	science	NOUN
fcis-15107	237	12	and	and	CCONJ
fcis-15107	237	13	engineering	engineering	NOUN
fcis-15107	237	14	(	(	PUNCT
fcis-15107	237	15	confuence	confuence	PROPN
fcis-15107	237	16	)	)	PUNCT
fcis-15107	237	17	.	.	PUNCT
fcis-15107	238	1	491–497	491–497	NUM
fcis-15107	238	2	(	(	PUNCT
fcis-15107	238	3	2020	2020	NUM
fcis-15107	238	4	)	)	PUNCT
fcis-15107	238	5	.	.	PUNCT
fcis-15107	239	1	[	[	X
fcis-15107	239	2	25	25	NUM
fcis-15107	239	3	]	]	PUNCT
fcis-15107	239	4	ramlal	ramlal	PROPN
fcis-15107	239	5	,	,	PUNCT
fcis-15107	239	6	s.	s.	PROPN
fcis-15107	239	7	d.	d.	PROPN
fcis-15107	239	8	,	,	PUNCT
fcis-15107	239	9	sachdeva	sachdeva	PROPN
fcis-15107	239	10	,	,	PUNCT
fcis-15107	239	11	j.	j.	PROPN
fcis-15107	239	12	,	,	PUNCT
fcis-15107	239	13	ahuja	ahuja	PROPN
fcis-15107	239	14	,	,	PUNCT
fcis-15107	239	15	c.	c.	PROPN
fcis-15107	239	16	k.	k.	PROPN
fcis-15107	239	17	&	&	CCONJ
fcis-15107	239	18	khandelwal	khandelwal	PROPN
fcis-15107	239	19	,	,	PUNCT
fcis-15107	239	20	n.	n.	PROPN
fcis-15107	239	21	an	an	DET
fcis-15107	239	22	improved	improved	ADJ
fcis-15107	239	23	multimodal	multimodal	ADJ
fcis-15107	239	24	medical	medical	ADJ
fcis-15107	239	25	image	image	NOUN
fcis-15107	239	26	fusion	fusion	NOUN
fcis-15107	239	27	scheme	scheme	NOUN
fcis-15107	239	28	based	base	VERB
fcis-15107	239	29	on	on	ADP
fcis-15107	239	30	hybrid	hybrid	ADJ
fcis-15107	239	31	combination	combination	NOUN
fcis-15107	239	32	of	of	ADP
fcis-15107	239	33	nonsubsampled	nonsubsample	VERB
fcis-15107	239	34	contourlet	contourlet	NOUN
fcis-15107	239	35	transform	transform	NOUN
fcis-15107	239	36	and	and	CCONJ
fcis-15107	239	37	stationary	stationary	ADJ
fcis-15107	239	38	wavelet	wavelet	NOUN
fcis-15107	239	39	transform	transform	NOUN
fcis-15107	239	40	.	.	PUNCT
fcis-15107	240	1	int	int	NOUN
fcis-15107	240	2	.	.	PUNCT
fcis-15107	241	1	j.	j.	PROPN
fcis-15107	241	2	imaging	imaging	PROPN
fcis-15107	241	3	syst	syst	PROPN
fcis-15107	241	4	.	.	PUNCT
fcis-15107	242	1	technol	technol	PROPN
fcis-15107	242	2	.	.	PUNCT
fcis-15107	243	1	29(2	29(2	NUM
fcis-15107	243	2	)	)	PUNCT
fcis-15107	243	3	,	,	PUNCT
fcis-15107	243	4	146–160	146–160	NUM
fcis-15107	243	5	(	(	PUNCT
fcis-15107	243	6	2019	2019	NUM
fcis-15107	243	7	)	)	PUNCT
fcis-15107	243	8	.	.	PUNCT
fcis-15107	244	1	[	[	X
fcis-15107	244	2	26	26	NUM
fcis-15107	244	3	]	]	X
fcis-15107	244	4	joshi	joshi	PROPN
fcis-15107	244	5	,	,	PUNCT
fcis-15107	244	6	k.	k.	PROPN
fcis-15107	244	7	,	,	PUNCT
fcis-15107	244	8	kirola	kirola	PROPN
fcis-15107	244	9	,	,	PUNCT
fcis-15107	244	10	m.	m.	NOUN
fcis-15107	244	11	,	,	PUNCT
fcis-15107	244	12	chaudhary	chaudhary	PROPN
fcis-15107	244	13	,	,	PUNCT
fcis-15107	244	14	s.	s.	PROPN
fcis-15107	244	15	,	,	PUNCT
fcis-15107	244	16	diwakar	diwakar	PROPN
fcis-15107	244	17	,	,	PUNCT
fcis-15107	244	18	m.	m.	NOUN
fcis-15107	244	19	,	,	PUNCT
fcis-15107	244	20	&	&	CCONJ
fcis-15107	244	21	joshi	joshi	PROPN
fcis-15107	244	22	,	,	PUNCT
fcis-15107	244	23	n.	n.	PROPN
fcis-15107	244	24	k.	k.	PROPN
fcis-15107	244	25	multi	multi	ADJ
fcis-15107	244	26	-	-	ADJ
fcis-15107	244	27	focus	focus	ADJ
fcis-15107	244	28	image	image	NOUN
fcis-15107	244	29	fusion	fusion	NOUN
fcis-15107	244	30	using	use	VERB
fcis-15107	244	31	discrete	discrete	ADJ
fcis-15107	244	32	wavelet	wavelet	NOUN
fcis-15107	244	33	transform	transform	NOUN
fcis-15107	244	34	method	method	NOUN
fcis-15107	244	35	.	.	PUNCT
fcis-15107	245	1	in	in	ADP
fcis-15107	245	2	international	international	ADJ
fcis-15107	245	3	conference	conference	NOUN
fcis-15107	245	4	on	on	ADP
fcis-15107	245	5	advances	advance	NOUN
fcis-15107	245	6	in	in	ADP
fcis-15107	245	7	engineering	engineering	NOUN
fcis-15107	245	8	science	science	NOUN
fcis-15107	245	9	management	management	NOUN
fcis-15107	245	10	&	&	CCONJ
fcis-15107	245	11	technology	technology	PROPN
fcis-15107	245	12	(	(	PUNCT
fcis-15107	245	13	icaesmt)-2019	icaesmt)-2019	ADJ
fcis-15107	245	14	,	,	PUNCT
fcis-15107	245	15	uttaranchal	uttaranchal	PROPN
fcis-15107	245	16	university	university	PROPN
fcis-15107	245	17	,	,	PUNCT
fcis-15107	245	18	dehradun	dehradun	PROPN
fcis-15107	245	19	,	,	PUNCT
fcis-15107	245	20	india	india	PROPN
fcis-15107	245	21	(	(	PUNCT
fcis-15107	245	22	2019	2019	NUM
fcis-15107	245	23	)	)	PUNCT
fcis-15107	245	24	.	.	PUNCT
fcis-15107	246	1	[	[	X
fcis-15107	246	2	27	27	NUM
fcis-15107	246	3	]	]	SYM
fcis-15107	246	4	mao	mao	PROPN
fcis-15107	246	5	,	,	PUNCT
fcis-15107	246	6	r.	r.	PROPN
fcis-15107	246	7	,	,	PUNCT
fcis-15107	246	8	et	et	PROPN
fcis-15107	246	9	al	al	PROPN
fcis-15107	246	10	.	.	PUNCT
fcis-15107	246	11	multi	multi	ADJ
fcis-15107	246	12	-	-	ADJ
fcis-15107	246	13	directional	directional	ADJ
fcis-15107	246	14	laplacian	laplacian	ADJ
fcis-15107	246	15	pyramid	pyramid	NOUN
fcis-15107	246	16	image	image	NOUN
fcis-15107	246	17	fusion	fusion	NOUN
fcis-15107	246	18	algorithm[c	algorithm[c	NOUN
fcis-15107	246	19	]	]	PUNCT
fcis-15107	246	20	.	.	PUNCT
fcis-15107	247	1	in	in	ADP
fcis-15107	247	2	2018	2018	NUM
fcis-15107	247	3	3rd	3rd	ADJ
fcis-15107	247	4	international	international	ADJ
fcis-15107	247	5	conference	conference	NOUN
fcis-15107	247	6	on	on	ADP
fcis-15107	247	7	mechanical	mechanical	ADJ
fcis-15107	247	8	,	,	PUNCT
fcis-15107	247	9	control	control	NOUN
fcis-15107	247	10	and	and	CCONJ
fcis-15107	247	11	computer	computer	NOUN
fcis-15107	247	12	engineering	engineering	NOUN
fcis-15107	247	13	(	(	PUNCT
fcis-15107	247	14	icmcce	icmcce	ADJ
fcis-15107	247	15	)	)	PUNCT
fcis-15107	247	16	.	.	PUNCT
fcis-15107	248	1	ieee	ieee	NOUN
fcis-15107	248	2	,	,	PUNCT
fcis-15107	248	3	2018	2018	NUM
fcis-15107	248	4	.	.	PUNCT
fcis-15107	249	1	568–572	568–572	NUM
fcis-15107	249	2	(	(	PUNCT
fcis-15107	249	3	2018	2018	NUM
fcis-15107	249	4	)	)	PUNCT
fcis-15107	249	5	.	.	PUNCT
fcis-15107	250	1	[	[	X
fcis-15107	250	2	28	28	NUM
fcis-15107	250	3	]	]	X
fcis-15107	250	4	long	long	ADV
fcis-15107	250	5	,	,	PUNCT
fcis-15107	250	6	j.	j.	PROPN
fcis-15107	250	7	,	,	PUNCT
fcis-15107	250	8	shelhamer	shelhamer	PROPN
fcis-15107	250	9	,	,	PUNCT
fcis-15107	250	10	e.	e.	PROPN
fcis-15107	250	11	,	,	PUNCT
fcis-15107	250	12	&	&	CCONJ
fcis-15107	250	13	darrell	darrell	PROPN
fcis-15107	250	14	,	,	PUNCT
fcis-15107	250	15	t.	t.	NOUN
fcis-15107	250	16	fully	fully	ADV
fcis-15107	250	17	convolutional	convolutional	ADJ
fcis-15107	250	18	networks	network	NOUN
fcis-15107	250	19	for	for	ADP
fcis-15107	250	20	semantic	semantic	ADJ
fcis-15107	250	21	segmentation	segmentation	NOUN
fcis-15107	250	22	.	.	PUNCT
fcis-15107	251	1	in	in	ADP
fcis-15107	251	2	2015	2015	NUM
fcis-15107	251	3	ieee	ieee	NOUN
fcis-15107	251	4	conference	conference	NOUN
fcis-15107	251	5	on	on	ADP
fcis-15107	251	6	computer	computer	NOUN
fcis-15107	251	7	vision	vision	NOUN
fcis-15107	251	8	and	and	CCONJ
fcis-15107	251	9	pattern	pattern	NOUN
fcis-15107	251	10	recognition	recognition	NOUN
fcis-15107	251	11	(	(	PUNCT
fcis-15107	251	12	cvpr	cvpr	NOUN
fcis-15107	251	13	)	)	PUNCT
fcis-15107	251	14	.	.	PUNCT
fcis-15107	252	1	3431	3431	NUM
fcis-15107	252	2	–	–	PUNCT
fcis-15107	252	3	3440	3440	NUM
fcis-15107	252	4	(	(	PUNCT
fcis-15107	252	5	2015	2015	NUM
fcis-15107	252	6	)	)	PUNCT
fcis-15107	252	7	.	.	PUNCT