id	sid	tid	token	lemma	pos
ajst-19195	1	1	academic	academic	ADJ
ajst-19195	1	2	journal	journal	NOUN
ajst-19195	1	3	of	of	ADP
ajst-19195	1	4	science	science	NOUN
ajst-19195	1	5	and	and	CCONJ
ajst-19195	1	6	technology	technology	NOUN
ajst-19195	1	7	issn	issn	NOUN
ajst-19195	1	8	:	:	PUNCT
ajst-19195	1	9	2771	2771	NUM
ajst-19195	1	10	-	-	SYM
ajst-19195	1	11	3032	3032	NUM
ajst-19195	1	12	|	|	NOUN
ajst-19195	1	13	vol	vol	NOUN
ajst-19195	1	14	.	.	PROPN
ajst-19195	2	1	10	10	NUM
ajst-19195	2	2	,	,	PUNCT
ajst-19195	2	3	no	no	INTJ
ajst-19195	2	4	.	.	NOUN
ajst-19195	2	5	1	1	NUM
ajst-19195	2	6	,	,	PUNCT
ajst-19195	2	7	2024	2024	NUM
ajst-19195	2	8	250	250	NUM
ajst-19195	2	9	improved	improve	VERB
ajst-19195	2	10	mri	mri	NOUN
ajst-19195	2	11	brain	brain	NOUN
ajst-19195	2	12	tumor	tumor	NOUN
ajst-19195	2	13	segmentation	segmentation	NOUN
ajst-19195	2	14	method	method	NOUN
ajst-19195	2	15	based	base	VERB
ajst-19195	2	16	on	on	ADP
ajst-19195	2	17	unet++	unet++	PROPN
ajst-19195	2	18	ke	ke	PROPN
ajst-19195	2	19	tong1	tong1	PROPN
ajst-19195	2	20	,	,	PUNCT
ajst-19195	2	21	2	2	NUM
ajst-19195	2	22	,	,	PUNCT
ajst-19195	2	23	jurong	jurong	PROPN
ajst-19195	2	24	ding1	ding1	PROPN
ajst-19195	2	25	,	,	PUNCT
ajst-19195	2	26	2	2	NUM
ajst-19195	2	27	,	,	PUNCT
ajst-19195	2	28	*	*	NOUN
ajst-19195	2	29	,	,	PUNCT
ajst-19195	2	30	xia	xia	PROPN
ajst-19195	2	31	li1	li1	NOUN
ajst-19195	2	32	,	,	PUNCT
ajst-19195	2	33	2	2	NUM
ajst-19195	2	34	1	1	NUM
ajst-19195	2	35	school	school	NOUN
ajst-19195	2	36	of	of	ADP
ajst-19195	2	37	automation	automation	NOUN
ajst-19195	2	38	and	and	CCONJ
ajst-19195	2	39	information	information	NOUN
ajst-19195	2	40	engineering	engineering	NOUN
ajst-19195	2	41	,	,	PUNCT
ajst-19195	2	42	sichuan	sichuan	PROPN
ajst-19195	2	43	university	university	PROPN
ajst-19195	2	44	of	of	ADP
ajst-19195	2	45	science	science	NOUN
ajst-19195	2	46	and	and	CCONJ
ajst-19195	2	47	engineering	engineering	NOUN
ajst-19195	2	48	,	,	PUNCT
ajst-19195	2	49	zigong	zigong	PROPN
ajst-19195	2	50	,	,	PUNCT
ajst-19195	2	51	china	china	PROPN
ajst-19195	2	52	2	2	NUM
ajst-19195	2	53	artificial	artificial	ADJ
ajst-19195	2	54	intelligence	intelligence	NOUN
ajst-19195	2	55	key	key	NOUN
ajst-19195	2	56	laboratory	laboratory	NOUN
ajst-19195	2	57	of	of	ADP
ajst-19195	2	58	sichuan	sichuan	PROPN
ajst-19195	2	59	province	province	PROPN
ajst-19195	2	60	,	,	PUNCT
ajst-19195	2	61	sichuan	sichuan	PROPN
ajst-19195	2	62	university	university	PROPN
ajst-19195	2	63	of	of	ADP
ajst-19195	2	64	science	science	NOUN
ajst-19195	2	65	and	and	CCONJ
ajst-19195	2	66	engineering	engineering	NOUN
ajst-19195	2	67	,	,	PUNCT
ajst-19195	2	68	zigong	zigong	PROPN
ajst-19195	2	69	,	,	PUNCT
ajst-19195	2	70	china	china	PROPN
ajst-19195	2	71	*	*	PUNCT
ajst-19195	2	72	corresponding	correspond	VERB
ajst-19195	2	73	author	author	NOUN
ajst-19195	2	74	:	:	PUNCT
ajst-19195	2	75	ju	ju	PROPN
ajst-19195	2	76	-	-	PUNCT
ajst-19195	2	77	rong	rong	PROPN
ajst-19195	2	78	ding	ding	PROPN
ajst-19195	2	79	(	(	PUNCT
ajst-19195	2	80	email	email	NOUN
ajst-19195	2	81	:	:	PUNCT
ajst-19195	2	82	jurongding@gmail.com	jurongding@gmail.com	X
ajst-19195	2	83	)	)	PUNCT
ajst-19195	2	84	abstract	abstract	ADJ
ajst-19195	2	85	:	:	PUNCT
ajst-19195	2	86	brain	brain	NOUN
ajst-19195	2	87	tumors	tumor	NOUN
ajst-19195	2	88	are	be	AUX
ajst-19195	2	89	one	one	NUM
ajst-19195	2	90	of	of	ADP
ajst-19195	2	91	the	the	DET
ajst-19195	2	92	most	most	ADV
ajst-19195	2	93	common	common	ADJ
ajst-19195	2	94	tumors	tumor	NOUN
ajst-19195	2	95	with	with	ADP
ajst-19195	2	96	high	high	ADJ
ajst-19195	2	97	mortality	mortality	NOUN
ajst-19195	2	98	.	.	PUNCT
ajst-19195	3	1	accurate	accurate	ADJ
ajst-19195	3	2	detection	detection	NOUN
ajst-19195	3	3	and	and	CCONJ
ajst-19195	3	4	quantitative	quantitative	ADJ
ajst-19195	3	5	evaluation	evaluation	NOUN
ajst-19195	3	6	of	of	ADP
ajst-19195	3	7	brain	brain	NOUN
ajst-19195	3	8	tumors	tumor	NOUN
ajst-19195	3	9	are	be	AUX
ajst-19195	3	10	necessary	necessary	ADJ
ajst-19195	3	11	for	for	ADP
ajst-19195	3	12	patient	patient	ADJ
ajst-19195	3	13	treatment	treatment	NOUN
ajst-19195	3	14	.	.	PUNCT
ajst-19195	4	1	a	a	DET
ajst-19195	4	2	reliable	reliable	ADJ
ajst-19195	4	3	and	and	CCONJ
ajst-19195	4	4	effective	effective	ADJ
ajst-19195	4	5	method	method	NOUN
ajst-19195	4	6	for	for	ADP
ajst-19195	4	7	automatic	automatic	ADJ
ajst-19195	4	8	segmentation	segmentation	NOUN
ajst-19195	4	9	of	of	ADP
ajst-19195	4	10	brain	brain	NOUN
ajst-19195	4	11	tumors	tumor	NOUN
ajst-19195	4	12	by	by	ADP
ajst-19195	4	13	magnetic	magnetic	ADJ
ajst-19195	4	14	resonance	resonance	NOUN
ajst-19195	4	15	imaging	imaging	NOUN
ajst-19195	4	16	(	(	PUNCT
ajst-19195	4	17	mri	mri	NOUN
ajst-19195	4	18	)	)	PUNCT
ajst-19195	4	19	plays	play	VERB
ajst-19195	4	20	a	a	DET
ajst-19195	4	21	crucial	crucial	ADJ
ajst-19195	4	22	role	role	NOUN
ajst-19195	4	23	in	in	ADP
ajst-19195	4	24	patient	patient	ADJ
ajst-19195	4	25	treatment	treatment	NOUN
ajst-19195	4	26	.	.	PUNCT
ajst-19195	5	1	in	in	ADP
ajst-19195	5	2	recent	recent	ADJ
ajst-19195	5	3	years	year	NOUN
ajst-19195	5	4	,	,	PUNCT
ajst-19195	5	5	the	the	DET
ajst-19195	5	6	unet++	unet++	ADJ
ajst-19195	5	7	network	network	NOUN
ajst-19195	5	8	structure	structure	NOUN
ajst-19195	5	9	has	have	AUX
ajst-19195	5	10	shown	show	VERB
ajst-19195	5	11	better	well	ADJ
ajst-19195	5	12	performance	performance	NOUN
ajst-19195	5	13	in	in	ADP
ajst-19195	5	14	image	image	NOUN
ajst-19195	5	15	segmentation	segmentation	NOUN
ajst-19195	5	16	.	.	PUNCT
ajst-19195	6	1	however	however	ADV
ajst-19195	6	2	,	,	PUNCT
ajst-19195	6	3	it	it	PRON
ajst-19195	6	4	is	be	AUX
ajst-19195	6	5	deficient	deficient	ADJ
ajst-19195	6	6	in	in	ADP
ajst-19195	6	7	small	small	ADJ
ajst-19195	6	8	-	-	PUNCT
ajst-19195	6	9	scale	scale	NOUN
ajst-19195	6	10	feature	feature	NOUN
ajst-19195	6	11	extraction	extraction	NOUN
ajst-19195	6	12	and	and	CCONJ
ajst-19195	6	13	segmentation	segmentation	NOUN
ajst-19195	6	14	accuracy	accuracy	NOUN
ajst-19195	6	15	.	.	PUNCT
ajst-19195	7	1	in	in	ADP
ajst-19195	7	2	this	this	DET
ajst-19195	7	3	study	study	NOUN
ajst-19195	7	4	,	,	PUNCT
ajst-19195	7	5	the	the	DET
ajst-19195	7	6	ac	ac	PROPN
ajst-19195	7	7	-	-	PUNCT
ajst-19195	7	8	resunet++	resunet++	NOUN
ajst-19195	7	9	network	network	NOUN
ajst-19195	7	10	was	be	AUX
ajst-19195	7	11	proposed	propose	VERB
ajst-19195	7	12	to	to	PART
ajst-19195	7	13	address	address	VERB
ajst-19195	7	14	the	the	DET
ajst-19195	7	15	problems	problem	NOUN
ajst-19195	7	16	of	of	ADP
ajst-19195	7	17	unet++	unet++	PROPN
ajst-19195	7	18	network	network	NOUN
ajst-19195	7	19	mentioned	mention	VERB
ajst-19195	7	20	above	above	ADV
ajst-19195	7	21	,	,	PUNCT
ajst-19195	7	22	which	which	PRON
ajst-19195	7	23	combined	combine	VERB
ajst-19195	7	24	residual	residual	ADJ
ajst-19195	7	25	module	module	NOUN
ajst-19195	7	26	,	,	PUNCT
ajst-19195	7	27	convolutional	convolutional	ADJ
ajst-19195	7	28	block	block	NOUN
ajst-19195	7	29	attention	attention	NOUN
ajst-19195	7	30	module	module	NOUN
ajst-19195	7	31	(	(	PUNCT
ajst-19195	7	32	cbam	cbam	NOUN
ajst-19195	7	33	)	)	PUNCT
ajst-19195	7	34	and	and	CCONJ
ajst-19195	7	35	atrous	atrous	ADJ
ajst-19195	7	36	spatial	spatial	ADJ
ajst-19195	7	37	pyramidal	pyramidal	NOUN
ajst-19195	7	38	pooling	pooling	NOUN
ajst-19195	7	39	(	(	PUNCT
ajst-19195	7	40	aspp	aspp	NOUN
ajst-19195	7	41	)	)	PUNCT
ajst-19195	7	42	.	.	PUNCT
ajst-19195	8	1	the	the	DET
ajst-19195	8	2	residual	residual	ADJ
ajst-19195	8	3	module	module	NOUN
ajst-19195	8	4	can	can	AUX
ajst-19195	8	5	solve	solve	VERB
ajst-19195	8	6	the	the	DET
ajst-19195	8	7	problem	problem	NOUN
ajst-19195	8	8	of	of	ADP
ajst-19195	8	9	gradient	gradient	ADJ
ajst-19195	8	10	explosion	explosion	NOUN
ajst-19195	8	11	in	in	ADP
ajst-19195	8	12	the	the	DET
ajst-19195	8	13	deep	deep	ADJ
ajst-19195	8	14	network	network	NOUN
ajst-19195	8	15	,	,	PUNCT
ajst-19195	8	16	cbam	cbam	NOUN
ajst-19195	8	17	can	can	AUX
ajst-19195	8	18	focus	focus	VERB
ajst-19195	8	19	on	on	ADP
ajst-19195	8	20	local	local	ADJ
ajst-19195	8	21	feature	feature	NOUN
ajst-19195	8	22	information	information	NOUN
ajst-19195	8	23	and	and	CCONJ
ajst-19195	8	24	enhance	enhance	VERB
ajst-19195	8	25	the	the	DET
ajst-19195	8	26	feature	feature	NOUN
ajst-19195	8	27	learning	learn	VERB
ajst-19195	8	28	ability	ability	NOUN
ajst-19195	8	29	of	of	ADP
ajst-19195	8	30	the	the	DET
ajst-19195	8	31	network	network	NOUN
ajst-19195	8	32	for	for	ADP
ajst-19195	8	33	the	the	DET
ajst-19195	8	34	target	target	NOUN
ajst-19195	8	35	range	range	NOUN
ajst-19195	8	36	,	,	PUNCT
ajst-19195	8	37	and	and	CCONJ
ajst-19195	8	38	aspp	aspp	NOUN
ajst-19195	8	39	module	module	NOUN
ajst-19195	8	40	can	can	AUX
ajst-19195	8	41	generate	generate	VERB
ajst-19195	8	42	different	different	ADJ
ajst-19195	8	43	receptive	receptive	ADJ
ajst-19195	8	44	fields	field	NOUN
ajst-19195	8	45	and	and	CCONJ
ajst-19195	8	46	obtain	obtain	VERB
ajst-19195	8	47	multi	multi	ADJ
ajst-19195	8	48	-	-	ADJ
ajst-19195	8	49	scale	scale	ADJ
ajst-19195	8	50	contextual	contextual	ADJ
ajst-19195	8	51	feature	feature	NOUN
ajst-19195	8	52	information	information	NOUN
ajst-19195	8	53	.	.	PUNCT
ajst-19195	9	1	the	the	DET
ajst-19195	9	2	brats	brat	NOUN
ajst-19195	9	3	2018	2018	NUM
ajst-19195	9	4	and	and	CCONJ
ajst-19195	9	5	brats	brat	NOUN
ajst-19195	9	6	2019	2019	NUM
ajst-19195	9	7	datasets	dataset	NOUN
ajst-19195	9	8	were	be	AUX
ajst-19195	9	9	used	use	VERB
ajst-19195	9	10	to	to	PART
ajst-19195	9	11	test	test	VERB
ajst-19195	9	12	the	the	DET
ajst-19195	9	13	proposed	propose	VERB
ajst-19195	9	14	network	network	NOUN
ajst-19195	9	15	.	.	PUNCT
ajst-19195	10	1	the	the	DET
ajst-19195	10	2	dice	dice	NOUN
ajst-19195	10	3	similarity	similarity	NOUN
ajst-19195	10	4	coefficient	coefficient	NOUN
ajst-19195	10	5	of	of	ADP
ajst-19195	10	6	ac	ac	PROPN
ajst-19195	10	7	-	-	NOUN
ajst-19195	10	8	resunet++	resunet++	NOUN
ajst-19195	10	9	in	in	ADP
ajst-19195	10	10	whole	whole	ADJ
ajst-19195	10	11	tumor	tumor	NOUN
ajst-19195	10	12	,	,	PUNCT
ajst-19195	10	13	tumor	tumor	NOUN
ajst-19195	10	14	core	core	NOUN
ajst-19195	10	15	and	and	CCONJ
ajst-19195	10	16	enhanced	enhance	VERB
ajst-19195	10	17	tumor	tumor	NOUN
ajst-19195	10	18	are	be	AUX
ajst-19195	10	19	0.8521	0.8521	NUM
ajst-19195	10	20	,	,	PUNCT
ajst-19195	10	21	0.8696	0.8696	NUM
ajst-19195	10	22	and	and	CCONJ
ajst-19195	10	23	0.7868	0.7868	NOUN
ajst-19195	10	24	,	,	PUNCT
ajst-19195	10	25	respectively	respectively	ADV
ajst-19195	10	26	.	.	PUNCT
ajst-19195	11	1	compared	compare	VERB
ajst-19195	11	2	with	with	ADP
ajst-19195	11	3	unet++	unet++	PROPN
ajst-19195	11	4	network	network	NOUN
ajst-19195	11	5	,	,	PUNCT
ajst-19195	11	6	the	the	DET
ajst-19195	11	7	dice	dice	NOUN
ajst-19195	11	8	similarity	similarity	NOUN
ajst-19195	11	9	coefficient	coefficient	NOUN
ajst-19195	11	10	increased	increase	VERB
ajst-19195	11	11	by	by	ADP
ajst-19195	11	12	1.22	1.22	NUM
ajst-19195	11	13	%	%	NOUN
ajst-19195	11	14	,	,	PUNCT
ajst-19195	11	15	5.08	5.08	NUM
ajst-19195	11	16	%	%	NOUN
ajst-19195	11	17	and	and	CCONJ
ajst-19195	11	18	2.03	2.03	NUM
ajst-19195	11	19	%	%	NOUN
ajst-19195	11	20	on	on	ADP
ajst-19195	11	21	the	the	DET
ajst-19195	11	22	baselines	baseline	NOUN
ajst-19195	11	23	.	.	PUNCT
ajst-19195	12	1	the	the	DET
ajst-19195	12	2	comprehensive	comprehensive	ADJ
ajst-19195	12	3	results	result	NOUN
ajst-19195	12	4	demonstrate	demonstrate	VERB
ajst-19195	12	5	that	that	SCONJ
ajst-19195	12	6	ac	ac	PROPN
ajst-19195	12	7	-	-	PUNCT
ajst-19195	12	8	resunet++	resunet++	NOUN
ajst-19195	12	9	performs	perform	VERB
ajst-19195	12	10	more	more	ADV
ajst-19195	12	11	effectively	effectively	ADV
ajst-19195	12	12	in	in	ADP
ajst-19195	12	13	improving	improve	VERB
ajst-19195	12	14	the	the	DET
ajst-19195	12	15	segmentation	segmentation	NOUN
ajst-19195	12	16	accuracy	accuracy	NOUN
ajst-19195	12	17	of	of	ADP
ajst-19195	12	18	brain	brain	NOUN
ajst-19195	12	19	tumor	tumor	NOUN
ajst-19195	12	20	.	.	PUNCT
ajst-19195	13	1	keywords	keyword	NOUN
ajst-19195	13	2	:	:	PUNCT
ajst-19195	13	3	brain	brain	NOUN
ajst-19195	13	4	tumor	tumor	NOUN
ajst-19195	13	5	segmentation	segmentation	NOUN
ajst-19195	13	6	,	,	PUNCT
ajst-19195	13	7	unet++	unet++	PROPN
ajst-19195	13	8	,	,	PUNCT
ajst-19195	13	9	residual	residual	ADJ
ajst-19195	13	10	module	module	NOUN
ajst-19195	13	11	,	,	PUNCT
ajst-19195	13	12	cbam	cbam	NOUN
ajst-19195	13	13	,	,	PUNCT
ajst-19195	13	14	aspp	aspp	NOUN
ajst-19195	13	15	.	.	PUNCT
ajst-19195	14	1	1	1	X
ajst-19195	14	2	.	.	X
ajst-19195	14	3	introduction	introduction	NOUN
ajst-19195	14	4	brain	brain	NOUN
ajst-19195	14	5	tumors	tumor	NOUN
ajst-19195	14	6	are	be	AUX
ajst-19195	14	7	one	one	NUM
ajst-19195	14	8	of	of	ADP
ajst-19195	14	9	the	the	DET
ajst-19195	14	10	most	most	ADV
ajst-19195	14	11	dangerous	dangerous	ADJ
ajst-19195	14	12	diseases	disease	NOUN
ajst-19195	14	13	endangering	endanger	VERB
ajst-19195	14	14	human	human	ADJ
ajst-19195	14	15	life	life	NOUN
ajst-19195	14	16	and	and	CCONJ
ajst-19195	14	17	health	health	NOUN
ajst-19195	15	1	[	[	X
ajst-19195	15	2	1	1	NUM
ajst-19195	15	3	]	]	PUNCT
ajst-19195	15	4	.	.	PUNCT
ajst-19195	16	1	brain	brain	NOUN
ajst-19195	16	2	tumors	tumor	NOUN
ajst-19195	16	3	are	be	AUX
ajst-19195	16	4	caused	cause	VERB
ajst-19195	16	5	by	by	ADP
ajst-19195	16	6	the	the	DET
ajst-19195	16	7	abnormal	abnormal	ADJ
ajst-19195	16	8	proliferation	proliferation	NOUN
ajst-19195	16	9	of	of	ADP
ajst-19195	16	10	cells	cell	NOUN
ajst-19195	16	11	in	in	ADP
ajst-19195	16	12	the	the	DET
ajst-19195	16	13	brain	brain	NOUN
ajst-19195	16	14	,	,	PUNCT
ajst-19195	16	15	which	which	PRON
ajst-19195	16	16	seriously	seriously	ADV
ajst-19195	16	17	damage	damage	VERB
ajst-19195	16	18	the	the	DET
ajst-19195	16	19	nervous	nervous	ADJ
ajst-19195	16	20	system	system	NOUN
ajst-19195	16	21	and	and	CCONJ
ajst-19195	16	22	nearby	nearby	ADJ
ajst-19195	16	23	healthy	healthy	ADJ
ajst-19195	16	24	brain	brain	NOUN
ajst-19195	16	25	tissues	tissue	NOUN
ajst-19195	16	26	.	.	PUNCT
ajst-19195	17	1	glioma	glioma	NOUN
ajst-19195	17	2	is	be	AUX
ajst-19195	17	3	the	the	DET
ajst-19195	17	4	most	most	ADV
ajst-19195	17	5	common	common	ADJ
ajst-19195	17	6	brain	brain	NOUN
ajst-19195	17	7	tumor	tumor	NOUN
ajst-19195	18	1	[	[	X
ajst-19195	18	2	2	2	NUM
ajst-19195	18	3	]	]	PUNCT
ajst-19195	18	4	.	.	PUNCT
ajst-19195	19	1	according	accord	VERB
ajst-19195	19	2	to	to	ADP
ajst-19195	19	3	the	the	DET
ajst-19195	19	4	severity	severity	NOUN
ajst-19195	19	5	of	of	ADP
ajst-19195	19	6	tumor	tumor	NOUN
ajst-19195	19	7	cells	cell	NOUN
ajst-19195	19	8	,	,	PUNCT
ajst-19195	19	9	brain	brain	NOUN
ajst-19195	19	10	tumors	tumor	NOUN
ajst-19195	19	11	are	be	AUX
ajst-19195	19	12	divided	divide	VERB
ajst-19195	19	13	into	into	ADP
ajst-19195	19	14	malignant	malignant	ADJ
ajst-19195	19	15	and	and	CCONJ
ajst-19195	19	16	non	non	ADJ
ajst-19195	19	17	-	-	ADJ
ajst-19195	19	18	malignant	malignant	ADJ
ajst-19195	19	19	.	.	PUNCT
ajst-19195	20	1	the	the	DET
ajst-19195	20	2	world	world	PROPN
ajst-19195	20	3	health	health	PROPN
ajst-19195	20	4	organization	organization	NOUN
ajst-19195	20	5	(	(	PUNCT
ajst-19195	20	6	who	who	PRON
ajst-19195	20	7	)	)	PUNCT
ajst-19195	20	8	classifies	classify	VERB
ajst-19195	20	9	glioma	glioma	NOUN
ajst-19195	20	10	into	into	ADP
ajst-19195	20	11	four	four	NUM
ajst-19195	20	12	grades	grade	NOUN
ajst-19195	20	13	according	accord	VERB
ajst-19195	20	14	to	to	ADP
ajst-19195	20	15	the	the	DET
ajst-19195	20	16	behavior	behavior	NOUN
ajst-19195	20	17	of	of	ADP
ajst-19195	20	18	tumor	tumor	NOUN
ajst-19195	20	19	cells	cell	NOUN
ajst-19195	20	20	.	.	PUNCT
ajst-19195	21	1	grades	grade	NOUN
ajst-19195	21	2	1	1	NUM
ajst-19195	21	3	and	and	CCONJ
ajst-19195	21	4	2	2	NUM
ajst-19195	21	5	are	be	AUX
ajst-19195	21	6	low	low	ADJ
ajst-19195	21	7	-	-	PUNCT
ajst-19195	21	8	grade	grade	NOUN
ajst-19195	21	9	gliomas	glioma	NOUN
ajst-19195	21	10	(	(	PUNCT
ajst-19195	21	11	lgg	lgg	PROPN
ajst-19195	21	12	)	)	PUNCT
ajst-19195	21	13	,	,	PUNCT
ajst-19195	21	14	and	and	CCONJ
ajst-19195	21	15	grades	grade	NOUN
ajst-19195	21	16	3	3	NUM
ajst-19195	21	17	and	and	CCONJ
ajst-19195	21	18	4	4	NUM
ajst-19195	21	19	are	be	AUX
ajst-19195	21	20	high	high	ADJ
ajst-19195	21	21	-	-	PUNCT
ajst-19195	21	22	grade	grade	NOUN
ajst-19195	21	23	gliomas	glioma	NOUN
ajst-19195	21	24	(	(	PUNCT
ajst-19195	21	25	hgg)[3	hgg)[3	NOUN
ajst-19195	21	26	]	]	PUNCT
ajst-19195	21	27	.	.	PUNCT
ajst-19195	22	1	therefore	therefore	ADV
ajst-19195	22	2	,	,	PUNCT
ajst-19195	22	3	accurate	accurate	ADJ
ajst-19195	22	4	clinical	clinical	ADJ
ajst-19195	22	5	detection	detection	NOUN
ajst-19195	22	6	and	and	CCONJ
ajst-19195	22	7	quantitative	quantitative	ADJ
ajst-19195	22	8	evaluation	evaluation	NOUN
ajst-19195	22	9	of	of	ADP
ajst-19195	22	10	brain	brain	NOUN
ajst-19195	22	11	tumors	tumor	NOUN
ajst-19195	22	12	are	be	AUX
ajst-19195	22	13	necessary	necessary	ADJ
ajst-19195	22	14	for	for	ADP
ajst-19195	22	15	the	the	DET
ajst-19195	22	16	treatment	treatment	NOUN
ajst-19195	22	17	of	of	ADP
ajst-19195	22	18	patient	patient	NOUN
ajst-19195	22	19	.	.	PUNCT
ajst-19195	23	1	however	however	ADV
ajst-19195	23	2	,	,	PUNCT
ajst-19195	23	3	accurate	accurate	ADJ
ajst-19195	23	4	detection	detection	NOUN
ajst-19195	23	5	of	of	ADP
ajst-19195	23	6	tumors	tumor	NOUN
ajst-19195	23	7	is	be	AUX
ajst-19195	23	8	a	a	DET
ajst-19195	23	9	challenging	challenging	ADJ
ajst-19195	23	10	task	task	NOUN
ajst-19195	23	11	because	because	SCONJ
ajst-19195	23	12	they	they	PRON
ajst-19195	23	13	vary	vary	VERB
ajst-19195	23	14	in	in	ADP
ajst-19195	23	15	size	size	NOUN
ajst-19195	23	16	and	and	CCONJ
ajst-19195	23	17	location	location	NOUN
ajst-19195	23	18	.	.	PUNCT
ajst-19195	24	1	medical	medical	ADJ
ajst-19195	24	2	imaging	imaging	NOUN
ajst-19195	24	3	technology	technology	NOUN
ajst-19195	24	4	plays	play	VERB
ajst-19195	24	5	a	a	DET
ajst-19195	24	6	crucial	crucial	ADJ
ajst-19195	24	7	role	role	NOUN
ajst-19195	24	8	in	in	ADP
ajst-19195	24	9	the	the	DET
ajst-19195	24	10	diagnosis	diagnosis	NOUN
ajst-19195	24	11	and	and	CCONJ
ajst-19195	24	12	evaluation	evaluation	NOUN
ajst-19195	24	13	of	of	ADP
ajst-19195	24	14	the	the	DET
ajst-19195	24	15	treatment	treatment	NOUN
ajst-19195	24	16	effect	effect	NOUN
ajst-19195	24	17	of	of	ADP
ajst-19195	24	18	brain	brain	NOUN
ajst-19195	24	19	tumors	tumor	NOUN
ajst-19195	24	20	.	.	PUNCT
ajst-19195	25	1	magnetic	magnetic	ADJ
ajst-19195	25	2	resonance	resonance	NOUN
ajst-19195	25	3	imaging	imaging	NOUN
ajst-19195	25	4	(	(	PUNCT
ajst-19195	25	5	mri	mri	NOUN
ajst-19195	25	6	)	)	PUNCT
ajst-19195	25	7	is	be	AUX
ajst-19195	25	8	the	the	DET
ajst-19195	25	9	most	most	ADV
ajst-19195	25	10	widely	widely	ADV
ajst-19195	25	11	used	use	VERB
ajst-19195	25	12	mode	mode	NOUN
ajst-19195	25	13	,	,	PUNCT
ajst-19195	25	14	which	which	PRON
ajst-19195	25	15	has	have	VERB
ajst-19195	25	16	the	the	DET
ajst-19195	25	17	characteristics	characteristic	NOUN
ajst-19195	25	18	of	of	ADP
ajst-19195	25	19	non	non	ADJ
ajst-19195	25	20	-	-	ADJ
ajst-19195	25	21	injury	injury	ADJ
ajst-19195	25	22	and	and	CCONJ
ajst-19195	25	23	high	high	ADJ
ajst-19195	25	24	resolution	resolution	NOUN
ajst-19195	25	25	,	,	PUNCT
ajst-19195	25	26	and	and	CCONJ
ajst-19195	25	27	can	can	AUX
ajst-19195	25	28	obtain	obtain	VERB
ajst-19195	25	29	different	different	ADJ
ajst-19195	25	30	anatomical	anatomical	ADJ
ajst-19195	25	31	information	information	NOUN
ajst-19195	25	32	by	by	ADP
ajst-19195	25	33	setting	set	VERB
ajst-19195	25	34	different	different	ADJ
ajst-19195	25	35	parameters	parameter	NOUN
ajst-19195	25	36	[	[	X
ajst-19195	25	37	4	4	NUM
ajst-19195	25	38	]	]	PUNCT
ajst-19195	25	39	.	.	PUNCT
ajst-19195	26	1	at	at	ADP
ajst-19195	26	2	present	present	ADJ
ajst-19195	26	3	,	,	PUNCT
ajst-19195	26	4	the	the	DET
ajst-19195	26	5	segmentation	segmentation	NOUN
ajst-19195	26	6	of	of	ADP
ajst-19195	26	7	brain	brain	NOUN
ajst-19195	26	8	tumors	tumor	NOUN
ajst-19195	26	9	is	be	AUX
ajst-19195	26	10	mainly	mainly	ADV
ajst-19195	26	11	performed	perform	VERB
ajst-19195	26	12	manually	manually	ADV
ajst-19195	26	13	based	base	VERB
ajst-19195	26	14	on	on	ADP
ajst-19195	26	15	mri	mri	PROPN
ajst-19195	26	16	.	.	PUNCT
ajst-19195	27	1	manual	manual	ADJ
ajst-19195	27	2	segmentation	segmentation	NOUN
ajst-19195	27	3	is	be	AUX
ajst-19195	27	4	time	time	NOUN
ajst-19195	27	5	-	-	PUNCT
ajst-19195	27	6	consuming	consume	VERB
ajst-19195	27	7	and	and	CCONJ
ajst-19195	27	8	has	have	VERB
ajst-19195	27	9	a	a	DET
ajst-19195	27	10	strong	strong	ADJ
ajst-19195	27	11	subjectivity	subjectivity	NOUN
ajst-19195	27	12	,	,	PUNCT
ajst-19195	27	13	so	so	SCONJ
ajst-19195	27	14	that	that	SCONJ
ajst-19195	27	15	the	the	DET
ajst-19195	27	16	reproducibility	reproducibility	NOUN
ajst-19195	27	17	is	be	AUX
ajst-19195	27	18	poor	poor	ADJ
ajst-19195	27	19	[	[	X
ajst-19195	27	20	5	5	NUM
ajst-19195	27	21	]	]	PUNCT
ajst-19195	27	22	.	.	PUNCT
ajst-19195	28	1	therefore	therefore	ADV
ajst-19195	28	2	,	,	PUNCT
ajst-19195	28	3	it	it	PRON
ajst-19195	28	4	is	be	AUX
ajst-19195	28	5	necessary	necessary	ADJ
ajst-19195	28	6	to	to	PART
ajst-19195	28	7	study	study	VERB
ajst-19195	28	8	the	the	DET
ajst-19195	28	9	method	method	NOUN
ajst-19195	28	10	that	that	PRON
ajst-19195	28	11	can	can	AUX
ajst-19195	28	12	be	be	AUX
ajst-19195	28	13	used	use	VERB
ajst-19195	28	14	to	to	PART
ajst-19195	28	15	segment	segment	NOUN
ajst-19195	28	16	brain	brain	NOUN
ajst-19195	28	17	tumors	tumor	NOUN
ajst-19195	28	18	accurately	accurately	ADV
ajst-19195	28	19	and	and	CCONJ
ajst-19195	28	20	automatically	automatically	ADV
ajst-19195	28	21	.	.	PUNCT
ajst-19195	29	1	the	the	DET
ajst-19195	29	2	miccai	miccai	NOUN
ajst-19195	29	3	has	have	AUX
ajst-19195	29	4	launched	launch	VERB
ajst-19195	29	5	a	a	DET
ajst-19195	29	6	multi	multi	ADJ
ajst-19195	29	7	-	-	ADJ
ajst-19195	29	8	modal	modal	ADJ
ajst-19195	29	9	brain	brain	NOUN
ajst-19195	29	10	tumor	tumor	NOUN
ajst-19195	29	11	segmentation	segmentation	NOUN
ajst-19195	29	12	challenges	challenge	NOUN
ajst-19195	29	13	(	(	PUNCT
ajst-19195	29	14	brats	brat	NOUN
ajst-19195	29	15	)	)	PUNCT
ajst-19195	29	16	since	since	SCONJ
ajst-19195	29	17	2012	2012	NUM
ajst-19195	29	18	to	to	PART
ajst-19195	29	19	promote	promote	VERB
ajst-19195	29	20	study	study	NOUN
ajst-19195	29	21	in	in	ADP
ajst-19195	29	22	this	this	DET
ajst-19195	29	23	area	area	NOUN
ajst-19195	29	24	.	.	PUNCT
ajst-19195	30	1	the	the	DET
ajst-19195	30	2	challenges	challenge	NOUN
ajst-19195	30	3	indicated	indicate	VERB
ajst-19195	30	4	that	that	SCONJ
ajst-19195	30	5	compared	compare	VERB
ajst-19195	30	6	with	with	ADP
ajst-19195	30	7	the	the	DET
ajst-19195	30	8	traditional	traditional	ADJ
ajst-19195	30	9	segmentation	segmentation	NOUN
ajst-19195	30	10	methods	method	NOUN
ajst-19195	30	11	,	,	PUNCT
ajst-19195	30	12	the	the	DET
ajst-19195	30	13	segmentation	segmentation	NOUN
ajst-19195	30	14	method	method	NOUN
ajst-19195	30	15	based	base	VERB
ajst-19195	30	16	on	on	ADP
ajst-19195	30	17	deep	deep	ADJ
ajst-19195	30	18	learning	learning	NOUN
ajst-19195	30	19	showed	show	VERB
ajst-19195	30	20	superiority	superiority	NOUN
ajst-19195	30	21	[	[	X
ajst-19195	30	22	6	6	NUM
ajst-19195	30	23	]	]	PUNCT
ajst-19195	30	24	.	.	PUNCT
ajst-19195	31	1	2d	2d	PROPN
ajst-19195	31	2	unet++	unet++	ADJ
ajst-19195	31	3	network	network	NOUN
ajst-19195	31	4	[	[	X
ajst-19195	31	5	7	7	NUM
ajst-19195	31	6	]	]	PUNCT
ajst-19195	31	7	has	have	VERB
ajst-19195	31	8	good	good	ADJ
ajst-19195	31	9	segmentation	segmentation	NOUN
ajst-19195	31	10	performance	performance	NOUN
ajst-19195	31	11	for	for	ADP
ajst-19195	31	12	lesion	lesion	NOUN
ajst-19195	31	13	areas	area	NOUN
ajst-19195	31	14	,	,	PUNCT
ajst-19195	31	15	which	which	PRON
ajst-19195	31	16	indirectly	indirectly	ADV
ajst-19195	31	17	fuses	fuse	VERB
ajst-19195	31	18	multiple	multiple	ADJ
ajst-19195	31	19	different	different	ADJ
ajst-19195	31	20	levels	level	NOUN
ajst-19195	31	21	of	of	ADP
ajst-19195	31	22	features	feature	NOUN
ajst-19195	31	23	.	.	PUNCT
ajst-19195	32	1	as	as	ADP
ajst-19195	32	2	one	one	NUM
ajst-19195	32	3	of	of	ADP
ajst-19195	32	4	the	the	DET
ajst-19195	32	5	important	important	ADJ
ajst-19195	32	6	improved	improved	ADJ
ajst-19195	32	7	networks	network	NOUN
ajst-19195	32	8	of	of	ADP
ajst-19195	32	9	unet	unet	NOUN
ajst-19195	32	10	,	,	PUNCT
ajst-19195	32	11	the	the	DET
ajst-19195	32	12	unet++	unet++	PROPN
ajst-19195	32	13	network	network	NOUN
ajst-19195	32	14	introduces	introduce	VERB
ajst-19195	32	15	a	a	DET
ajst-19195	32	16	built	build	VERB
ajst-19195	32	17	-	-	PUNCT
ajst-19195	32	18	in	in	ADP
ajst-19195	32	19	unet	unet	NOUN
ajst-19195	32	20	collection	collection	NOUN
ajst-19195	32	21	with	with	ADP
ajst-19195	32	22	variable	variable	ADJ
ajst-19195	32	23	depth	depth	NOUN
ajst-19195	32	24	in	in	ADP
ajst-19195	32	25	the	the	DET
ajst-19195	32	26	network	network	NOUN
ajst-19195	32	27	.	.	PUNCT
ajst-19195	33	1	this	this	DET
ajst-19195	33	2	kind	kind	NOUN
ajst-19195	33	3	of	of	ADP
ajst-19195	33	4	collection	collection	NOUN
ajst-19195	33	5	allows	allow	VERB
ajst-19195	33	6	the	the	DET
ajst-19195	33	7	decoder	decoder	NOUN
ajst-19195	33	8	to	to	PART
ajst-19195	33	9	perceive	perceive	VERB
ajst-19195	33	10	targets	target	NOUN
ajst-19195	33	11	with	with	ADP
ajst-19195	33	12	different	different	ADJ
ajst-19195	33	13	sizes	size	NOUN
ajst-19195	33	14	under	under	ADP
ajst-19195	33	15	different	different	ADJ
ajst-19195	33	16	receptive	receptive	ADJ
ajst-19195	33	17	fields	field	NOUN
ajst-19195	33	18	.	.	PUNCT
ajst-19195	34	1	the	the	DET
ajst-19195	34	2	skip	skip	ADJ
ajst-19195	34	3	connection	connection	NOUN
ajst-19195	34	4	is	be	AUX
ajst-19195	34	5	redesigned	redesign	VERB
ajst-19195	34	6	for	for	ADP
ajst-19195	34	7	more	more	ADV
ajst-19195	34	8	flexible	flexible	ADJ
ajst-19195	34	9	feature	feature	NOUN
ajst-19195	34	10	fusion	fusion	NOUN
ajst-19195	34	11	.	.	PUNCT
ajst-19195	35	1	however	however	ADV
ajst-19195	35	2	,	,	PUNCT
ajst-19195	35	3	too	too	ADV
ajst-19195	35	4	many	many	ADJ
ajst-19195	35	5	jump	jump	NOUN
ajst-19195	35	6	connections	connection	NOUN
ajst-19195	35	7	and	and	CCONJ
ajst-19195	35	8	nesting	nesting	NOUN
ajst-19195	35	9	would	would	AUX
ajst-19195	35	10	lead	lead	VERB
ajst-19195	35	11	to	to	ADP
ajst-19195	35	12	the	the	DET
ajst-19195	35	13	loss	loss	NOUN
ajst-19195	35	14	of	of	ADP
ajst-19195	35	15	features	feature	NOUN
ajst-19195	35	16	and	and	CCONJ
ajst-19195	35	17	prevent	prevent	VERB
ajst-19195	35	18	the	the	DET
ajst-19195	35	19	network	network	NOUN
ajst-19195	35	20	from	from	ADP
ajst-19195	35	21	getting	get	VERB
ajst-19195	35	22	enough	enough	ADJ
ajst-19195	35	23	multi	multi	ADJ
ajst-19195	35	24	-	-	ADJ
ajst-19195	35	25	scale	scale	ADJ
ajst-19195	35	26	information	information	NOUN
ajst-19195	35	27	.	.	PUNCT
ajst-19195	36	1	in	in	ADP
ajst-19195	36	2	addition	addition	NOUN
ajst-19195	36	3	,	,	PUNCT
ajst-19195	36	4	as	as	SCONJ
ajst-19195	36	5	the	the	DET
ajst-19195	36	6	network	network	NOUN
ajst-19195	36	7	gets	get	VERB
ajst-19195	36	8	deeper	deep	ADJ
ajst-19195	36	9	,	,	PUNCT
ajst-19195	36	10	there	there	PRON
ajst-19195	36	11	is	be	VERB
ajst-19195	36	12	a	a	DET
ajst-19195	36	13	problem	problem	NOUN
ajst-19195	36	14	of	of	ADP
ajst-19195	36	15	gradient	gradient	ADJ
ajst-19195	36	16	disappearance	disappearance	NOUN
ajst-19195	36	17	in	in	ADP
ajst-19195	36	18	the	the	DET
ajst-19195	36	19	process	process	NOUN
ajst-19195	36	20	of	of	ADP
ajst-19195	36	21	down	down	ADV
ajst-19195	36	22	-	-	PUNCT
ajst-19195	36	23	sampling	sampling	NOUN
ajst-19195	36	24	,	,	PUNCT
ajst-19195	36	25	which	which	PRON
ajst-19195	36	26	will	will	AUX
ajst-19195	36	27	lead	lead	VERB
ajst-19195	36	28	to	to	ADP
ajst-19195	36	29	a	a	DET
ajst-19195	36	30	reduction	reduction	NOUN
ajst-19195	36	31	in	in	ADP
ajst-19195	36	32	the	the	DET
ajst-19195	36	33	network	network	NOUN
ajst-19195	36	34	's	's	PART
ajst-19195	36	35	ability	ability	NOUN
ajst-19195	36	36	to	to	PART
ajst-19195	36	37	extract	extract	VERB
ajst-19195	36	38	brain	brain	NOUN
ajst-19195	36	39	tumor	tumor	NOUN
ajst-19195	36	40	features	feature	NOUN
ajst-19195	36	41	.	.	PUNCT
ajst-19195	37	1	during	during	ADP
ajst-19195	37	2	the	the	DET
ajst-19195	37	3	process	process	NOUN
ajst-19195	37	4	of	of	ADP
ajst-19195	37	5	up	up	ADV
ajst-19195	37	6	-	-	PUNCT
ajst-19195	37	7	sampling	sampling	NOUN
ajst-19195	37	8	,	,	PUNCT
ajst-19195	37	9	the	the	DET
ajst-19195	37	10	extracted	extract	VERB
ajst-19195	37	11	feature	feature	NOUN
ajst-19195	37	12	information	information	NOUN
ajst-19195	37	13	is	be	AUX
ajst-19195	37	14	incomplete	incomplete	ADJ
ajst-19195	37	15	,	,	PUNCT
ajst-19195	37	16	and	and	CCONJ
ajst-19195	37	17	the	the	DET
ajst-19195	37	18	edge	edge	NOUN
ajst-19195	37	19	information	information	NOUN
ajst-19195	37	20	and	and	CCONJ
ajst-19195	37	21	location	location	NOUN
ajst-19195	37	22	information	information	NOUN
ajst-19195	37	23	are	be	AUX
ajst-19195	37	24	lost	lose	VERB
ajst-19195	37	25	,	,	PUNCT
ajst-19195	37	26	which	which	PRON
ajst-19195	37	27	will	will	AUX
ajst-19195	37	28	affect	affect	VERB
ajst-19195	37	29	the	the	DET
ajst-19195	37	30	accuracy	accuracy	NOUN
ajst-19195	37	31	of	of	ADP
ajst-19195	37	32	the	the	DET
ajst-19195	37	33	network	network	NOUN
ajst-19195	37	34	segmentation	segmentation	NOUN
ajst-19195	37	35	on	on	ADP
ajst-19195	37	36	small	small	ADJ
ajst-19195	37	37	-	-	PUNCT
ajst-19195	37	38	scale	scale	NOUN
ajst-19195	37	39	brain	brain	NOUN
ajst-19195	37	40	tumors	tumor	NOUN
ajst-19195	37	41	.	.	PUNCT
ajst-19195	38	1	in	in	ADP
ajst-19195	38	2	this	this	DET
ajst-19195	38	3	study	study	NOUN
ajst-19195	38	4	,	,	PUNCT
ajst-19195	38	5	the	the	DET
ajst-19195	38	6	ac	ac	PROPN
ajst-19195	38	7	-	-	PUNCT
ajst-19195	38	8	resunet++	resunet++	NOUN
ajst-19195	38	9	network	network	NOUN
ajst-19195	38	10	for	for	ADP
ajst-19195	38	11	medical	medical	ADJ
ajst-19195	38	12	image	image	NOUN
ajst-19195	38	13	segmentation	segmentation	NOUN
ajst-19195	38	14	is	be	AUX
ajst-19195	38	15	proposed	propose	VERB
ajst-19195	38	16	to	to	PART
ajst-19195	38	17	solve	solve	VERB
ajst-19195	38	18	the	the	DET
ajst-19195	38	19	problem	problem	NOUN
ajst-19195	38	20	of	of	ADP
ajst-19195	38	21	the	the	DET
ajst-19195	38	22	unet++	unet++	PROPN
ajst-19195	38	23	network	network	NOUN
ajst-19195	38	24	.	.	PUNCT
ajst-19195	39	1	a	a	DET
ajst-19195	39	2	residual	residual	ADJ
ajst-19195	39	3	block	block	NOUN
ajst-19195	39	4	is	be	AUX
ajst-19195	39	5	added	add	VERB
ajst-19195	39	6	to	to	ADP
ajst-19195	39	7	each	each	DET
ajst-19195	39	8	downsampling	downsampling	NOUN
ajst-19195	39	9	of	of	ADP
ajst-19195	39	10	the	the	DET
ajst-19195	39	11	network	network	NOUN
ajst-19195	39	12	to	to	PART
ajst-19195	39	13	solve	solve	VERB
ajst-19195	39	14	the	the	DET
ajst-19195	39	15	problem	problem	NOUN
ajst-19195	39	16	of	of	ADP
ajst-19195	39	17	network	network	NOUN
ajst-19195	39	18	gradient	gradient	NOUN
ajst-19195	39	19	disappearance	disappearance	NOUN
ajst-19195	39	20	.	.	PUNCT
ajst-19195	40	1	convolutional	convolutional	ADJ
ajst-19195	40	2	block	block	NOUN
ajst-19195	40	3	attention	attention	NOUN
ajst-19195	40	4	module	module	NOUN
ajst-19195	40	5	(	(	PUNCT
ajst-19195	40	6	cbam	cbam	NOUN
ajst-19195	40	7	)	)	PUNCT
ajst-19195	40	8	is	be	AUX
ajst-19195	40	9	fused	fuse	VERB
ajst-19195	40	10	in	in	ADP
ajst-19195	40	11	each	each	DET
ajst-19195	40	12	up	up	ADV
ajst-19195	40	13	-	-	PUNCT
ajst-19195	40	14	sampling	sample	VERB
ajst-19195	40	15	to	to	PART
ajst-19195	40	16	enhance	enhance	VERB
ajst-19195	40	17	the	the	DET
ajst-19195	40	18	network	network	NOUN
ajst-19195	40	19	extraction	extraction	NOUN
ajst-19195	40	20	ability	ability	NOUN
ajst-19195	40	21	of	of	ADP
ajst-19195	40	22	local	local	ADJ
ajst-19195	40	23	features	feature	NOUN
ajst-19195	40	24	and	and	CCONJ
ajst-19195	40	25	suppress	suppress	VERB
ajst-19195	40	26	redundant	redundant	ADJ
ajst-19195	40	27	information	information	NOUN
ajst-19195	40	28	.	.	PUNCT
ajst-19195	41	1	the	the	DET
ajst-19195	41	2	inclusion	inclusion	NOUN
ajst-19195	41	3	of	of	ADP
ajst-19195	41	4	the	the	DET
ajst-19195	41	5	atrous	atrous	ADJ
ajst-19195	41	6	spatial	spatial	ADJ
ajst-19195	41	7	pyramidal	pyramidal	NOUN
ajst-19195	41	8	pooling	pool	VERB
ajst-19195	41	9	(	(	PUNCT
ajst-19195	41	10	aspp	aspp	NOUN
ajst-19195	41	11	)	)	PUNCT
ajst-19195	41	12	module	module	NOUN
ajst-19195	41	13	between	between	ADP
ajst-19195	41	14	the	the	DET
ajst-19195	41	15	encoder	encoder	NOUN
ajst-19195	41	16	and	and	CCONJ
ajst-19195	41	17	decoder	decoder	NOUN
ajst-19195	41	18	provides	provide	VERB
ajst-19195	41	19	a	a	DET
ajst-19195	41	20	different	different	ADJ
ajst-19195	41	21	perceptual	perceptual	ADJ
ajst-19195	41	22	field	field	NOUN
ajst-19195	41	23	for	for	ADP
ajst-19195	41	24	the	the	DET
ajst-19195	41	25	feature	feature	NOUN
ajst-19195	41	26	map	map	NOUN
ajst-19195	41	27	,	,	PUNCT
ajst-19195	41	28	preventing	prevent	VERB
ajst-19195	41	29	the	the	DET
ajst-19195	41	30	loss	loss	NOUN
ajst-19195	41	31	of	of	ADP
ajst-19195	41	32	detailed	detailed	ADJ
ajst-19195	41	33	information	information	NOUN
ajst-19195	41	34	and	and	CCONJ
ajst-19195	41	35	promoting	promote	VERB
ajst-19195	41	36	the	the	DET
ajst-19195	41	37	network	network	NOUN
ajst-19195	41	38	to	to	PART
ajst-19195	41	39	capture	capture	VERB
ajst-19195	41	40	more	more	ADV
ajst-19195	41	41	useful	useful	ADJ
ajst-19195	41	42	multi	multi	ADJ
ajst-19195	41	43	-	-	ADJ
ajst-19195	41	44	scale	scale	ADJ
ajst-19195	41	45	information	information	NOUN
ajst-19195	41	46	.	.	PUNCT
ajst-19195	42	1	finally	finally	ADV
ajst-19195	42	2	,	,	PUNCT
ajst-19195	42	3	the	the	DET
ajst-19195	42	4	performance	performance	NOUN
ajst-19195	42	5	of	of	ADP
ajst-19195	42	6	ac	ac	ADJ
ajst-19195	42	7	-	-	PUNCT
ajst-19195	42	8	resunet++	resunet++	NOUN
ajst-19195	42	9	model	model	NOUN
ajst-19195	42	10	in	in	ADP
ajst-19195	42	11	this	this	DET
ajst-19195	42	12	study	study	NOUN
ajst-19195	42	13	is	be	AUX
ajst-19195	42	14	evaluated	evaluate	VERB
ajst-19195	42	15	on	on	ADP
ajst-19195	42	16	the	the	DET
ajst-19195	42	17	brats	brat	NOUN
ajst-19195	42	18	2018	2018	NUM
ajst-19195	42	19	and	and	CCONJ
ajst-19195	42	20	brats	brat	NOUN
ajst-19195	42	21	2019	2019	NUM
ajst-19195	42	22	public	public	ADJ
ajst-19195	42	23	dataset	dataset	NOUN
ajst-19195	42	24	.	.	PUNCT
ajst-19195	43	1	251	251	NUM
ajst-19195	43	2	2	2	NUM
ajst-19195	43	3	.	.	PUNCT
ajst-19195	43	4	method	method	PROPN
ajst-19195	43	5	2.1	2.1	NUM
ajst-19195	43	6	.	.	PUNCT
ajst-19195	44	1	ac	ac	PROPN
ajst-19195	44	2	-	-	PUNCT
ajst-19195	44	3	resunet++	resunet++	NOUN
ajst-19195	44	4	unet++	unet++	PROPN
ajst-19195	44	5	is	be	AUX
ajst-19195	44	6	an	an	DET
ajst-19195	44	7	improved	improved	ADJ
ajst-19195	44	8	network	network	NOUN
ajst-19195	44	9	based	base	VERB
ajst-19195	44	10	on	on	ADP
ajst-19195	44	11	unet	unet	NOUN
ajst-19195	44	12	,	,	PUNCT
ajst-19195	44	13	which	which	PRON
ajst-19195	44	14	is	be	AUX
ajst-19195	44	15	structured	structure	VERB
ajst-19195	44	16	as	as	ADP
ajst-19195	44	17	a	a	DET
ajst-19195	44	18	deeply	deeply	ADV
ajst-19195	44	19	supervised	supervised	ADJ
ajst-19195	44	20	encoder	encoder	NOUN
ajst-19195	44	21	-	-	PUNCT
ajst-19195	44	22	decoder	decoder	NOUN
ajst-19195	44	23	network	network	NOUN
ajst-19195	44	24	essentially	essentially	ADV
ajst-19195	44	25	[	[	X
ajst-19195	44	26	8	8	NUM
ajst-19195	44	27	]	]	PUNCT
ajst-19195	44	28	.	.	PUNCT
ajst-19195	45	1	the	the	DET
ajst-19195	45	2	encoder	encoder	NOUN
ajst-19195	45	3	and	and	CCONJ
ajst-19195	45	4	decoder	decoder	NOUN
ajst-19195	45	5	subnetworks	subnetwork	NOUN
ajst-19195	45	6	are	be	AUX
ajst-19195	45	7	connected	connect	VERB
ajst-19195	45	8	through	through	ADP
ajst-19195	45	9	a	a	DET
ajst-19195	45	10	series	series	NOUN
ajst-19195	45	11	of	of	ADP
ajst-19195	45	12	nested	nested	ADJ
ajst-19195	45	13	dense	dense	ADJ
ajst-19195	45	14	jumps	jump	NOUN
ajst-19195	45	15	[	[	X
ajst-19195	45	16	9	9	NUM
ajst-19195	45	17	]	]	PUNCT
ajst-19195	45	18	to	to	PART
ajst-19195	45	19	capture	capture	VERB
ajst-19195	45	20	more	more	ADJ
ajst-19195	45	21	feature	feature	NOUN
ajst-19195	45	22	layers	layer	NOUN
ajst-19195	45	23	.	.	PUNCT
ajst-19195	46	1	the	the	DET
ajst-19195	46	2	unet++	unet++	PROPN
ajst-19195	46	3	will	will	AUX
ajst-19195	46	4	continuously	continuously	ADV
ajst-19195	46	5	deepen	deepen	VERB
ajst-19195	46	6	the	the	DET
ajst-19195	46	7	depth	depth	NOUN
ajst-19195	46	8	of	of	ADP
ajst-19195	46	9	the	the	DET
ajst-19195	46	10	network	network	NOUN
ajst-19195	46	11	during	during	ADP
ajst-19195	46	12	the	the	DET
ajst-19195	46	13	down	down	ADV
ajst-19195	46	14	-	-	PUNCT
ajst-19195	46	15	sampling	sample	VERB
ajst-19195	46	16	process	process	NOUN
ajst-19195	46	17	,	,	PUNCT
ajst-19195	46	18	resulting	result	VERB
ajst-19195	46	19	in	in	ADP
ajst-19195	46	20	the	the	DET
ajst-19195	46	21	phenomenon	phenomenon	NOUN
ajst-19195	46	22	of	of	ADP
ajst-19195	46	23	gradient	gradient	ADJ
ajst-19195	46	24	degradation	degradation	NOUN
ajst-19195	46	25	.	.	PUNCT
ajst-19195	47	1	therefore	therefore	ADV
ajst-19195	47	2	,	,	PUNCT
ajst-19195	47	3	a	a	DET
ajst-19195	47	4	residual	residual	ADJ
ajst-19195	47	5	block	block	NOUN
ajst-19195	47	6	is	be	AUX
ajst-19195	47	7	added	add	VERB
ajst-19195	47	8	to	to	ADP
ajst-19195	47	9	each	each	DET
ajst-19195	47	10	down	down	ADV
ajst-19195	47	11	-	-	PUNCT
ajst-19195	47	12	sampling	sampling	NOUN
ajst-19195	47	13	to	to	PART
ajst-19195	47	14	address	address	VERB
ajst-19195	47	15	the	the	DET
ajst-19195	47	16	encoder	encoder	NOUN
ajst-19195	47	17	degradation	degradation	NOUN
ajst-19195	47	18	problem	problem	NOUN
ajst-19195	47	19	and	and	CCONJ
ajst-19195	47	20	improve	improve	VERB
ajst-19195	47	21	the	the	DET
ajst-19195	47	22	network	network	NOUN
ajst-19195	47	23	's	's	PART
ajst-19195	47	24	capacity	capacity	NOUN
ajst-19195	47	25	for	for	ADP
ajst-19195	47	26	deeper	deep	ADJ
ajst-19195	47	27	feature	feature	NOUN
ajst-19195	47	28	extraction	extraction	NOUN
ajst-19195	47	29	and	and	CCONJ
ajst-19195	47	30	representation	representation	NOUN
ajst-19195	47	31	.	.	PUNCT
ajst-19195	48	1	brain	brain	NOUN
ajst-19195	48	2	tumors	tumor	NOUN
ajst-19195	48	3	are	be	AUX
ajst-19195	48	4	complex	complex	ADJ
ajst-19195	48	5	in	in	ADP
ajst-19195	48	6	shape	shape	NOUN
ajst-19195	48	7	and	and	CCONJ
ajst-19195	48	8	vary	vary	VERB
ajst-19195	48	9	in	in	ADP
ajst-19195	48	10	size	size	NOUN
ajst-19195	48	11	.	.	PUNCT
ajst-19195	49	1	during	during	ADP
ajst-19195	49	2	the	the	DET
ajst-19195	49	3	up	up	ADV
ajst-19195	49	4	-	-	PUNCT
ajst-19195	49	5	sampling	sample	VERB
ajst-19195	49	6	process	process	NOUN
ajst-19195	49	7	,	,	PUNCT
ajst-19195	49	8	the	the	DET
ajst-19195	49	9	spatial	spatial	ADJ
ajst-19195	49	10	and	and	CCONJ
ajst-19195	49	11	location	location	NOUN
ajst-19195	49	12	details	detail	NOUN
ajst-19195	49	13	of	of	ADP
ajst-19195	49	14	the	the	DET
ajst-19195	49	15	feature	feature	NOUN
ajst-19195	49	16	map	map	NOUN
ajst-19195	49	17	are	be	AUX
ajst-19195	49	18	easily	easily	ADV
ajst-19195	49	19	lost	lose	VERB
ajst-19195	49	20	,	,	PUNCT
ajst-19195	49	21	which	which	PRON
ajst-19195	49	22	makes	make	VERB
ajst-19195	49	23	network	network	NOUN
ajst-19195	49	24	difficult	difficult	ADJ
ajst-19195	49	25	to	to	PART
ajst-19195	49	26	segment	segment	VERB
ajst-19195	49	27	the	the	DET
ajst-19195	49	28	location	location	NOUN
ajst-19195	49	29	and	and	CCONJ
ajst-19195	49	30	size	size	NOUN
ajst-19195	49	31	of	of	ADP
ajst-19195	49	32	small	small	ADJ
ajst-19195	49	33	-	-	PUNCT
ajst-19195	49	34	scale	scale	NOUN
ajst-19195	49	35	brain	brain	NOUN
ajst-19195	49	36	tumors	tumor	NOUN
ajst-19195	49	37	.	.	PUNCT
ajst-19195	50	1	this	this	PRON
ajst-19195	50	2	is	be	AUX
ajst-19195	50	3	an	an	DET
ajst-19195	50	4	important	important	ADJ
ajst-19195	50	5	factor	factor	NOUN
ajst-19195	50	6	that	that	PRON
ajst-19195	50	7	restricts	restrict	VERB
ajst-19195	50	8	the	the	DET
ajst-19195	50	9	improvement	improvement	NOUN
ajst-19195	50	10	of	of	ADP
ajst-19195	50	11	segmentation	segmentation	NOUN
ajst-19195	50	12	accuracy	accuracy	NOUN
ajst-19195	50	13	.	.	PUNCT
ajst-19195	51	1	thus	thus	ADV
ajst-19195	51	2	,	,	PUNCT
ajst-19195	51	3	cbam	cbam	NOUN
ajst-19195	51	4	is	be	AUX
ajst-19195	51	5	incorporated	incorporate	VERB
ajst-19195	51	6	in	in	ADP
ajst-19195	51	7	each	each	DET
ajst-19195	51	8	up	up	ADV
ajst-19195	51	9	-	-	PUNCT
ajst-19195	51	10	sampling	sample	VERB
ajst-19195	51	11	to	to	PART
ajst-19195	51	12	enhance	enhance	VERB
ajst-19195	51	13	the	the	DET
ajst-19195	51	14	network	network	NOUN
ajst-19195	51	15	's	's	PART
ajst-19195	51	16	ability	ability	NOUN
ajst-19195	51	17	to	to	PART
ajst-19195	51	18	extract	extract	VERB
ajst-19195	51	19	and	and	CCONJ
ajst-19195	51	20	represent	represent	VERB
ajst-19195	51	21	local	local	ADJ
ajst-19195	51	22	features	feature	NOUN
ajst-19195	51	23	.	.	PUNCT
ajst-19195	52	1	the	the	DET
ajst-19195	52	2	spatial	spatial	ADJ
ajst-19195	52	3	and	and	CCONJ
ajst-19195	52	4	channel	channel	NOUN
ajst-19195	52	5	attention	attention	NOUN
ajst-19195	52	6	can	can	AUX
ajst-19195	52	7	make	make	VERB
ajst-19195	52	8	the	the	DET
ajst-19195	52	9	network	network	NOUN
ajst-19195	52	10	more	more	ADV
ajst-19195	52	11	focused	focused	ADJ
ajst-19195	52	12	on	on	ADP
ajst-19195	52	13	useful	useful	ADJ
ajst-19195	52	14	feature	feature	NOUN
ajst-19195	52	15	mapping	mapping	NOUN
ajst-19195	52	16	,	,	PUNCT
ajst-19195	52	17	suppress	suppress	VERB
ajst-19195	52	18	redundant	redundant	ADJ
ajst-19195	52	19	information	information	NOUN
ajst-19195	52	20	,	,	PUNCT
ajst-19195	52	21	and	and	CCONJ
ajst-19195	52	22	solve	solve	VERB
ajst-19195	52	23	the	the	DET
ajst-19195	52	24	problem	problem	NOUN
ajst-19195	52	25	of	of	ADP
ajst-19195	52	26	small	small	ADJ
ajst-19195	52	27	-	-	PUNCT
ajst-19195	52	28	scale	scale	NOUN
ajst-19195	52	29	tumors	tumor	NOUN
ajst-19195	52	30	being	be	AUX
ajst-19195	52	31	ignored	ignore	VERB
ajst-19195	52	32	[	[	PUNCT
ajst-19195	52	33	10	10	NUM
ajst-19195	52	34	]	]	PUNCT
ajst-19195	52	35	.	.	PUNCT
ajst-19195	53	1	brain	brain	NOUN
ajst-19195	53	2	tumors	tumor	NOUN
ajst-19195	53	3	differ	differ	VERB
ajst-19195	53	4	in	in	ADP
ajst-19195	53	5	location	location	NOUN
ajst-19195	53	6	,	,	PUNCT
ajst-19195	53	7	size	size	NOUN
ajst-19195	53	8	and	and	CCONJ
ajst-19195	53	9	shape	shape	NOUN
ajst-19195	53	10	,	,	PUNCT
ajst-19195	53	11	and	and	CCONJ
ajst-19195	53	12	are	be	AUX
ajst-19195	53	13	often	often	ADV
ajst-19195	53	14	surrounded	surround	VERB
ajst-19195	53	15	by	by	ADP
ajst-19195	53	16	edema	edema	PROPN
ajst-19195	53	17	,	,	PUNCT
ajst-19195	53	18	which	which	PRON
ajst-19195	53	19	leads	lead	VERB
ajst-19195	53	20	to	to	ADP
ajst-19195	53	21	insufficient	insufficient	ADJ
ajst-19195	53	22	information	information	NOUN
ajst-19195	53	23	extraction	extraction	NOUN
ajst-19195	53	24	during	during	ADP
ajst-19195	53	25	segmentation	segmentation	NOUN
ajst-19195	53	26	.	.	PUNCT
ajst-19195	54	1	hence	hence	ADV
ajst-19195	54	2	,	,	PUNCT
ajst-19195	54	3	aspp	aspp	NOUN
ajst-19195	54	4	module	module	NOUN
ajst-19195	54	5	is	be	AUX
ajst-19195	54	6	added	add	VERB
ajst-19195	54	7	between	between	ADP
ajst-19195	54	8	the	the	DET
ajst-19195	54	9	network	network	NOUN
ajst-19195	54	10	encoder	encoder	NOUN
ajst-19195	54	11	and	and	CCONJ
ajst-19195	54	12	decoder	decoder	NOUN
ajst-19195	54	13	to	to	PART
ajst-19195	54	14	generate	generate	VERB
ajst-19195	54	15	different	different	ADJ
ajst-19195	54	16	receptive	receptive	ADJ
ajst-19195	54	17	fields	field	NOUN
ajst-19195	54	18	,	,	PUNCT
ajst-19195	54	19	which	which	PRON
ajst-19195	54	20	makes	make	VERB
ajst-19195	54	21	the	the	DET
ajst-19195	54	22	network	network	NOUN
ajst-19195	54	23	obtain	obtain	VERB
ajst-19195	54	24	image	image	NOUN
ajst-19195	54	25	multi	multi	ADJ
ajst-19195	54	26	-	-	ADJ
ajst-19195	54	27	scale	scale	ADJ
ajst-19195	54	28	context	context	NOUN
ajst-19195	54	29	feature	feature	NOUN
ajst-19195	54	30	information	information	NOUN
ajst-19195	54	31	and	and	CCONJ
ajst-19195	54	32	solve	solve	VERB
ajst-19195	54	33	the	the	DET
ajst-19195	54	34	problem	problem	NOUN
ajst-19195	54	35	of	of	ADP
ajst-19195	54	36	image	image	NOUN
ajst-19195	54	37	boundary	boundary	ADJ
ajst-19195	54	38	detail	detail	NOUN
ajst-19195	54	39	information	information	NOUN
ajst-19195	54	40	loss	loss	NOUN
ajst-19195	54	41	.	.	PUNCT
ajst-19195	55	1	the	the	DET
ajst-19195	55	2	ac	ac	PROPN
ajst-19195	55	3	-	-	PUNCT
ajst-19195	55	4	resunet++	resunet++	NOUN
ajst-19195	55	5	network	network	NOUN
ajst-19195	55	6	architecture	architecture	NOUN
ajst-19195	55	7	is	be	AUX
ajst-19195	55	8	shown	show	VERB
ajst-19195	55	9	in	in	ADP
ajst-19195	55	10	fig	fig	NOUN
ajst-19195	55	11	.	.	PUNCT
ajst-19195	56	1	1	1	X
ajst-19195	56	2	.	.	X
ajst-19195	56	3	figure	figure	NOUN
ajst-19195	56	4	1	1	NUM
ajst-19195	56	5	.	.	PUNCT
ajst-19195	57	1	ac	ac	ADJ
ajst-19195	57	2	-	-	PUNCT
ajst-19195	57	3	resunet++	resunet++	NOUN
ajst-19195	57	4	network	network	NOUN
ajst-19195	57	5	architecture	architecture	NOUN
ajst-19195	57	6	2.2	2.2	NUM
ajst-19195	57	7	.	.	PUNCT
ajst-19195	58	1	residual	residual	ADJ
ajst-19195	58	2	module	module	NOUN
ajst-19195	58	3	the	the	PRON
ajst-19195	58	4	deeper	deep	ADJ
ajst-19195	58	5	the	the	DET
ajst-19195	58	6	level	level	NOUN
ajst-19195	58	7	of	of	ADP
ajst-19195	58	8	a	a	DET
ajst-19195	58	9	convolutional	convolutional	ADJ
ajst-19195	58	10	network	network	NOUN
ajst-19195	58	11	,	,	PUNCT
ajst-19195	58	12	the	the	PRON
ajst-19195	58	13	better	well	ADJ
ajst-19195	58	14	the	the	DET
ajst-19195	58	15	ability	ability	NOUN
ajst-19195	58	16	of	of	ADP
ajst-19195	58	17	the	the	DET
ajst-19195	58	18	network	network	NOUN
ajst-19195	58	19	to	to	PART
ajst-19195	58	20	extract	extract	VERB
ajst-19195	58	21	features	feature	NOUN
ajst-19195	58	22	from	from	ADP
ajst-19195	58	23	images	image	NOUN
ajst-19195	58	24	.	.	PUNCT
ajst-19195	59	1	however	however	ADV
ajst-19195	59	2	,	,	PUNCT
ajst-19195	59	3	with	with	ADP
ajst-19195	59	4	the	the	DET
ajst-19195	59	5	deepening	deepening	NOUN
ajst-19195	59	6	of	of	ADP
ajst-19195	59	7	the	the	DET
ajst-19195	59	8	network	network	NOUN
ajst-19195	59	9	,	,	PUNCT
ajst-19195	59	10	the	the	DET
ajst-19195	59	11	gradient	gradient	NOUN
ajst-19195	59	12	will	will	AUX
ajst-19195	59	13	disappear	disappear	VERB
ajst-19195	59	14	when	when	SCONJ
ajst-19195	59	15	the	the	DET
ajst-19195	59	16	accuracy	accuracy	NOUN
ajst-19195	59	17	reaches	reach	VERB
ajst-19195	59	18	saturation	saturation	NOUN
ajst-19195	59	19	.	.	PUNCT
ajst-19195	60	1	he	he	PRON
ajst-19195	60	2	et	et	PROPN
ajst-19195	60	3	al.[11	al.[11	PROPN
ajst-19195	60	4	]	]	PUNCT
ajst-19195	60	5	proposed	propose	VERB
ajst-19195	60	6	a	a	DET
ajst-19195	60	7	residual	residual	ADJ
ajst-19195	60	8	network	network	NOUN
ajst-19195	60	9	consisting	consist	VERB
ajst-19195	60	10	of	of	ADP
ajst-19195	60	11	multiple	multiple	ADJ
ajst-19195	60	12	residual	residual	ADJ
ajst-19195	60	13	blocks	block	NOUN
ajst-19195	60	14	to	to	PART
ajst-19195	60	15	solve	solve	VERB
ajst-19195	60	16	this	this	DET
ajst-19195	60	17	problem	problem	NOUN
ajst-19195	60	18	.	.	PUNCT
ajst-19195	61	1	fig	fig	NOUN
ajst-19195	61	2	.	.	PUNCT
ajst-19195	62	1	2	2	X
ajst-19195	62	2	.	.	X
ajst-19195	62	3	shows	show	VERB
ajst-19195	62	4	the	the	DET
ajst-19195	62	5	schematic	schematic	ADJ
ajst-19195	62	6	diagram	diagram	NOUN
ajst-19195	62	7	of	of	ADP
ajst-19195	62	8	residual	residual	ADJ
ajst-19195	62	9	block	block	NOUN
ajst-19195	62	10	.	.	PUNCT
ajst-19195	63	1	figure	figure	NOUN
ajst-19195	63	2	2	2	NUM
ajst-19195	63	3	.	.	PUNCT
ajst-19195	63	4	residual	residual	ADJ
ajst-19195	63	5	block	block	NOUN
ajst-19195	63	6	a	a	DET
ajst-19195	63	7	neural	neural	ADJ
ajst-19195	63	8	network	network	NOUN
ajst-19195	63	9	supposes	suppose	VERB
ajst-19195	63	10	x	x	PUNCT
ajst-19195	63	11	as	as	ADP
ajst-19195	63	12	an	an	DET
ajst-19195	63	13	input	input	NOUN
ajst-19195	63	14	and	and	CCONJ
ajst-19195	63	15	the	the	DET
ajst-19195	63	16	desired	desire	VERB
ajst-19195	63	17	underlying	underlie	VERB
ajst-19195	63	18	mapping	mapping	NOUN
ajst-19195	63	19	is	be	AUX
ajst-19195	63	20	represented	represent	VERB
ajst-19195	63	21	as	as	ADP
ajst-19195	63	22	h(x	h(x	PROPN
ajst-19195	63	23	)	)	PUNCT
ajst-19195	63	24	.	.	PUNCT
ajst-19195	64	1	the	the	DET
ajst-19195	64	2	formula	formula	NOUN
ajst-19195	64	3	is	be	AUX
ajst-19195	64	4	as	as	SCONJ
ajst-19195	64	5	follows	follow	VERB
ajst-19195	64	6	:	:	PUNCT
ajst-19195	64	7	(	(	PUNCT
ajst-19195	64	8	)	)	PUNCT
ajst-19195	64	9	(	(	PUNCT
ajst-19195	64	10	)	)	PUNCT
ajst-19195	64	11	f	f	X
ajst-19195	64	12	x	x	SYM
ajst-19195	64	13	h	h	NOUN
ajst-19195	64	14	x	x	X
ajst-19195	65	1	x	x	PUNCT
ajst-19195	65	2			NOUN
ajst-19195	65	3	(	(	PUNCT
ajst-19195	65	4	1	1	NUM
ajst-19195	65	5	)	)	PUNCT
ajst-19195	65	6	where	where	SCONJ
ajst-19195	65	7	,	,	PUNCT
ajst-19195	65	8	f(x	f(x	PROPN
ajst-19195	65	9	)	)	PUNCT
ajst-19195	65	10	is	be	AUX
ajst-19195	65	11	a	a	DET
ajst-19195	65	12	residual	residual	ADJ
ajst-19195	65	13	unit	unit	NOUN
ajst-19195	65	14	.	.	PUNCT
ajst-19195	66	1	due	due	ADP
ajst-19195	66	2	to	to	ADP
ajst-19195	66	3	the	the	DET
ajst-19195	66	4	skip	skip	ADJ
ajst-19195	66	5	connection	connection	NOUN
ajst-19195	66	6	,	,	PUNCT
ajst-19195	66	7	x	x	PRON
ajst-19195	66	8	skips	skip	VERB
ajst-19195	66	9	the	the	DET
ajst-19195	66	10	intermediate	intermediate	ADJ
ajst-19195	66	11	layers	layer	NOUN
ajst-19195	66	12	and	and	CCONJ
ajst-19195	66	13	is	be	AUX
ajst-19195	66	14	transmitted	transmit	VERB
ajst-19195	66	15	to	to	ADP
ajst-19195	66	16	the	the	DET
ajst-19195	66	17	deeper	deep	ADJ
ajst-19195	66	18	network	network	NOUN
ajst-19195	66	19	,	,	PUNCT
ajst-19195	66	20	then	then	ADV
ajst-19195	66	21	the	the	DET
ajst-19195	66	22	original	original	ADJ
ajst-19195	66	23	function	function	NOUN
ajst-19195	66	24	becomes	become	VERB
ajst-19195	66	25	f(x)+x	f(x)+x	NOUN
ajst-19195	66	26	.	.	PUNCT
ajst-19195	67	1	the	the	DET
ajst-19195	67	2	input	input	NOUN
ajst-19195	67	3	and	and	CCONJ
ajst-19195	67	4	output	output	NOUN
ajst-19195	67	5	are	be	AUX
ajst-19195	67	6	superimposed	superimpose	VERB
ajst-19195	67	7	,	,	PUNCT
ajst-19195	67	8	which	which	PRON
ajst-19195	67	9	propagates	propagate	VERB
ajst-19195	67	10	larger	large	ADJ
ajst-19195	67	11	gradients	gradient	NOUN
ajst-19195	67	12	to	to	ADP
ajst-19195	67	13	the	the	DET
ajst-19195	67	14	initial	initial	ADJ
ajst-19195	67	15	layers	layer	NOUN
ajst-19195	67	16	and	and	CCONJ
ajst-19195	67	17	allows	allow	VERB
ajst-19195	67	18	these	these	DET
ajst-19195	67	19	layers	layer	NOUN
ajst-19195	67	20	to	to	PART
ajst-19195	67	21	learn	learn	VERB
ajst-19195	67	22	as	as	ADV
ajst-19195	67	23	quickly	quickly	ADV
ajst-19195	67	24	as	as	ADP
ajst-19195	67	25	the	the	DET
ajst-19195	67	26	final	final	ADJ
ajst-19195	67	27	layers	layer	NOUN
ajst-19195	67	28	,	,	PUNCT
ajst-19195	67	29	and	and	CCONJ
ajst-19195	67	30	then	then	ADV
ajst-19195	67	31	allows	allow	VERB
ajst-19195	67	32	the	the	DET
ajst-19195	67	33	training	training	NOUN
ajst-19195	67	34	of	of	ADP
ajst-19195	67	35	deeper	deep	ADJ
ajst-19195	67	36	networks	network	NOUN
ajst-19195	67	37	[	[	X
ajst-19195	67	38	12	12	NUM
ajst-19195	67	39	]	]	PUNCT
ajst-19195	67	40	.	.	PUNCT
ajst-19195	68	1	the	the	DET
ajst-19195	68	2	network	network	NOUN
ajst-19195	68	3	uses	use	VERB
ajst-19195	68	4	relu	relu	NOUN
ajst-19195	68	5	as	as	SCONJ
ajst-19195	68	6	the	the	DET
ajst-19195	68	7	activation	activation	NOUN
ajst-19195	68	8	function	function	VERB
ajst-19195	68	9	to	to	PART
ajst-19195	68	10	improve	improve	VERB
ajst-19195	68	11	the	the	DET
ajst-19195	68	12	linear	linear	NOUN
ajst-19195	68	13	fitting	fitting	NOUN
ajst-19195	68	14	of	of	ADP
ajst-19195	68	15	the	the	DET
ajst-19195	68	16	network	network	NOUN
ajst-19195	68	17	.	.	PUNCT
ajst-19195	69	1	the	the	DET
ajst-19195	69	2	residual	residual	ADJ
ajst-19195	69	3	module	module	NOUN
ajst-19195	69	4	enables	enable	VERB
ajst-19195	69	5	the	the	DET
ajst-19195	69	6	deep	deep	ADJ
ajst-19195	69	7	network	network	NOUN
ajst-19195	69	8	to	to	PART
ajst-19195	69	9	transmit	transmit	VERB
ajst-19195	69	10	information	information	NOUN
ajst-19195	69	11	better	well	ADV
ajst-19195	69	12	and	and	CCONJ
ajst-19195	69	13	solves	solve	VERB
ajst-19195	69	14	the	the	DET
ajst-19195	69	15	problem	problem	NOUN
ajst-19195	69	16	of	of	ADP
ajst-19195	69	17	information	information	NOUN
ajst-19195	69	18	loss	loss	NOUN
ajst-19195	69	19	caused	cause	VERB
ajst-19195	69	20	by	by	ADP
ajst-19195	69	21	the	the	DET
ajst-19195	69	22	disappearance	disappearance	NOUN
ajst-19195	69	23	of	of	ADP
ajst-19195	69	24	gradients	gradient	NOUN
ajst-19195	69	25	in	in	ADP
ajst-19195	69	26	the	the	DET
ajst-19195	69	27	network	network	NOUN
ajst-19195	69	28	training	training	NOUN
ajst-19195	69	29	process	process	NOUN
ajst-19195	69	30	.	.	PUNCT
ajst-19195	70	1	this	this	DET
ajst-19195	70	2	module	module	NOUN
ajst-19195	70	3	is	be	AUX
ajst-19195	70	4	added	add	VERB
ajst-19195	70	5	to	to	ADP
ajst-19195	70	6	the	the	DET
ajst-19195	70	7	up	up	NOUN
ajst-19195	70	8	-	-	PUNCT
ajst-19195	70	9	sampling	sampling	NOUN
ajst-19195	70	10	of	of	ADP
ajst-19195	70	11	the	the	DET
ajst-19195	70	12	network	network	NOUN
ajst-19195	70	13	to	to	PART
ajst-19195	70	14	improve	improve	VERB
ajst-19195	70	15	feature	feature	NOUN
ajst-19195	70	16	extraction	extraction	NOUN
ajst-19195	70	17	and	and	CCONJ
ajst-19195	70	18	expression	expression	NOUN
ajst-19195	70	19	capabilities	capability	NOUN
ajst-19195	70	20	at	at	ADP
ajst-19195	70	21	deeper	deep	ADJ
ajst-19195	70	22	levels	level	NOUN
ajst-19195	70	23	of	of	ADP
ajst-19195	70	24	the	the	DET
ajst-19195	70	25	network	network	NOUN
ajst-19195	70	26	.	.	PUNCT
ajst-19195	71	1	2.3	2.3	NUM
ajst-19195	71	2	.	.	PUNCT
ajst-19195	71	3	convolutional	convolutional	ADJ
ajst-19195	71	4	block	block	NOUN
ajst-19195	71	5	attention	attention	NOUN
ajst-19195	71	6	module	module	NOUN
ajst-19195	71	7	cbam	cbam	NOUN
ajst-19195	71	8	is	be	AUX
ajst-19195	71	9	a	a	DET
ajst-19195	71	10	lightweight	lightweight	ADJ
ajst-19195	71	11	attention	attention	NOUN
ajst-19195	71	12	module	module	NOUN
ajst-19195	71	13	that	that	PRON
ajst-19195	71	14	can	can	AUX
ajst-19195	71	15	be	be	AUX
ajst-19195	71	16	integrated	integrate	VERB
ajst-19195	71	17	into	into	ADP
ajst-19195	71	18	any	any	DET
ajst-19195	71	19	convolutional	convolutional	ADJ
ajst-19195	71	20	neural	neural	ADJ
ajst-19195	71	21	network	network	NOUN
ajst-19195	71	22	framework	framework	NOUN
ajst-19195	71	23	[	[	X
ajst-19195	71	24	13	13	NUM
ajst-19195	71	25	]	]	PUNCT
ajst-19195	71	26	.	.	PUNCT
ajst-19195	72	1	cbam	cbam	NOUN
ajst-19195	72	2	emphasizes	emphasize	VERB
ajst-19195	72	3	the	the	DET
ajst-19195	72	4	meaning	meaning	NOUN
ajst-19195	72	5	features	feature	NOUN
ajst-19195	72	6	in	in	ADP
ajst-19195	72	7	both	both	DET
ajst-19195	72	8	channel	channel	NOUN
ajst-19195	72	9	and	and	CCONJ
ajst-19195	72	10	space	space	NOUN
ajst-19195	72	11	dimensions	dimension	NOUN
ajst-19195	72	12	.	.	PUNCT
ajst-19195	73	1	each	each	DET
ajst-19195	73	2	convolutional	convolutional	ADJ
ajst-19195	73	3	block	block	NOUN
ajst-19195	73	4	of	of	ADP
ajst-19195	73	5	a	a	DET
ajst-19195	73	6	deep	deep	ADJ
ajst-19195	73	7	neural	neural	ADJ
ajst-19195	73	8	network	network	NOUN
ajst-19195	73	9	can	can	AUX
ajst-19195	73	10	be	be	AUX
ajst-19195	73	11	adaptively	adaptively	ADV
ajst-19195	73	12	mapped	map	VERB
ajst-19195	73	13	with	with	ADP
ajst-19195	73	14	intermediate	intermediate	ADJ
ajst-19195	73	15	features	feature	NOUN
ajst-19195	73	16	by	by	ADP
ajst-19195	73	17	the	the	DET
ajst-19195	73	18	cbam	cbam	NOUN
ajst-19195	73	19	module	module	NOUN
ajst-19195	73	20	.	.	PUNCT
ajst-19195	74	1	there	there	PRON
ajst-19195	74	2	are	be	VERB
ajst-19195	74	3	two	two	NUM
ajst-19195	74	4	attention	attention	NOUN
ajst-19195	74	5	modules	module	NOUN
ajst-19195	74	6	in	in	ADP
ajst-19195	74	7	cbam	cbam	NOUN
ajst-19195	74	8	,	,	PUNCT
ajst-19195	74	9	named	name	VERB
ajst-19195	74	10	channel	channel	NOUN
ajst-19195	74	11	attention	attention	NOUN
ajst-19195	74	12	and	and	CCONJ
ajst-19195	74	13	spatial	spatial	ADJ
ajst-19195	74	14	attention	attention	NOUN
ajst-19195	74	15	.	.	PUNCT
ajst-19195	75	1	feature	feature	NOUN
ajst-19195	75	2	images	image	NOUN
ajst-19195	75	3	are	be	AUX
ajst-19195	75	4	first	first	ADJ
ajst-19195	75	5	input	input	NOUN
ajst-19195	75	6	to	to	PART
ajst-19195	75	7	passed	pass	VERB
ajst-19195	75	8	through	through	ADP
ajst-19195	75	9	the	the	DET
ajst-19195	75	10	channel	channel	NOUN
ajst-19195	75	11	attention	attention	NOUN
ajst-19195	75	12	module	module	NOUN
ajst-19195	75	13	for	for	ADP
ajst-19195	75	14	max	max	PROPN
ajst-19195	75	15	and	and	CCONJ
ajst-19195	75	16	avg	avg	PROPN
ajst-19195	75	17	pooling	pooling	PROPN
ajst-19195	75	18	,	,	PUNCT
ajst-19195	75	19	the	the	DET
ajst-19195	75	20	results	result	NOUN
ajst-19195	75	21	of	of	ADP
ajst-19195	75	22	pooling	pooling	NOUN
ajst-19195	75	23	are	be	AUX
ajst-19195	75	24	summed	sum	VERB
ajst-19195	75	25	by	by	ADP
ajst-19195	75	26	the	the	DET
ajst-19195	75	27	mlp	mlp	NOUN
ajst-19195	75	28	layer	layer	NOUN
ajst-19195	75	29	respectively	respectively	ADV
ajst-19195	75	30	.	.	PUNCT
ajst-19195	76	1	then	then	ADV
ajst-19195	76	2	the	the	DET
ajst-19195	76	3	channel	channel	NOUN
ajst-19195	76	4	feature	feature	NOUN
ajst-19195	76	5	maps	map	NOUN
ajst-19195	76	6	are	be	AUX
ajst-19195	76	7	generated	generate	VERB
ajst-19195	76	8	by	by	ADP
ajst-19195	76	9	the	the	DET
ajst-19195	76	10	sigmoid	sigmoid	NOUN
ajst-19195	76	11	activation	activation	NOUN
ajst-19195	76	12	function	function	NOUN
ajst-19195	76	13	,	,	PUNCT
ajst-19195	76	14	and	and	CCONJ
ajst-19195	76	15	then	then	ADV
ajst-19195	76	16	input	input	VERB
ajst-19195	76	17	into	into	ADP
ajst-19195	76	18	the	the	DET
ajst-19195	76	19	spatial	spatial	ADJ
ajst-19195	76	20	attention	attention	NOUN
ajst-19195	76	21	module	module	NOUN
ajst-19195	76	22	.	.	PUNCT
ajst-19195	77	1	the	the	DET
ajst-19195	77	2	above	above	ADJ
ajst-19195	77	3	operations	operation	NOUN
ajst-19195	77	4	are	be	AUX
ajst-19195	77	5	repeated	repeat	VERB
ajst-19195	77	6	to	to	PART
ajst-19195	77	7	generate	generate	VERB
ajst-19195	77	8	the	the	DET
ajst-19195	77	9	final	final	ADJ
ajst-19195	77	10	feature	feature	NOUN
ajst-19195	77	11	images	image	NOUN
ajst-19195	77	12	.	.	PUNCT
ajst-19195	78	1	after	after	ADP
ajst-19195	78	2	this	this	DET
ajst-19195	78	3	process	process	NOUN
ajst-19195	78	4	,	,	PUNCT
ajst-19195	78	5	the	the	DET
ajst-19195	78	6	image	image	NOUN
ajst-19195	78	7	loss	loss	NOUN
ajst-19195	78	8	caused	cause	VERB
ajst-19195	78	9	by	by	ADP
ajst-19195	78	10	network	network	NOUN
ajst-19195	78	11	jumps	jump	VERB
ajst-19195	78	12	can	can	AUX
ajst-19195	78	13	be	be	AUX
ajst-19195	78	14	effectively	effectively	ADV
ajst-19195	78	15	reduced	reduce	VERB
ajst-19195	78	16	and	and	CCONJ
ajst-19195	78	17	the	the	DET
ajst-19195	78	18	accuracy	accuracy	NOUN
ajst-19195	78	19	of	of	ADP
ajst-19195	78	20	feature	feature	NOUN
ajst-19195	78	21	maps	map	NOUN
ajst-19195	78	22	can	can	AUX
ajst-19195	78	23	be	be	AUX
ajst-19195	78	24	improved	improve	VERB
ajst-19195	78	25	[	[	X
ajst-19195	78	26	14	14	NUM
ajst-19195	78	27	]	]	PUNCT
ajst-19195	78	28	.	.	PUNCT
ajst-19195	79	1	assuming	assume	VERB
ajst-19195	79	2	an	an	DET
ajst-19195	79	3	intermediate	intermediate	ADJ
ajst-19195	79	4	feature	feature	NOUN
ajst-19195	79	5	c	c	NOUN
ajst-19195	79	6	h	h	NOUN
ajst-19195	79	7	wf	wf	NOUN
ajst-19195	79	8	r	r	NOUN
ajst-19195	79	9			NOUN
ajst-19195	79	10			NOUN
ajst-19195	79	11	as	as	ADP
ajst-19195	79	12	an	an	DET
ajst-19195	79	13	input	input	NOUN
ajst-19195	79	14	feature	feature	NOUN
ajst-19195	79	15	,	,	PUNCT
ajst-19195	79	16	then	then	ADV
ajst-19195	79	17	a	a	DET
ajst-19195	79	18	channel	channel	NOUN
ajst-19195	79	19	attention	attention	NOUN
ajst-19195	79	20	1	1	NUM
ajst-19195	79	21	1c	1c	NUM
ajst-19195	79	22	cm	cm	NOUN
ajst-19195	79	23	r	r	NOUN
ajst-19195	79	24			NOUN
ajst-19195	79	25			NOUN
ajst-19195	79	26	and	and	CCONJ
ajst-19195	79	27	a	a	DET
ajst-19195	79	28	spatial	spatial	ADJ
ajst-19195	79	29	attention	attention	NOUN
ajst-19195	79	30	1	1	NUM
ajst-19195	79	31	h	h	NOUN
ajst-19195	79	32	w	w	NOUN
ajst-19195	79	33	sm	sm	NOUN
ajst-19195	79	34	r	r	NOUN
ajst-19195	79	35			NOUN
ajst-19195	79	36			NOUN
ajst-19195	79	37	can	can	AUX
ajst-19195	79	38	be	be	AUX
ajst-19195	79	39	inferred	infer	VERB
ajst-19195	79	40	sequentially	sequentially	ADV
ajst-19195	79	41	.	.	PUNCT
ajst-19195	80	1	where	where	SCONJ
ajst-19195	80	2	denotes	denote	NOUN
ajst-19195	80	3	element	element	NOUN
ajst-19195	80	4	-	-	PUNCT
ajst-19195	80	5	based	base	VERB
ajst-19195	80	6	multiplication	multiplication	NOUN
ajst-19195	80	7	.	.	PUNCT
ajst-19195	81	1	the	the	DET
ajst-19195	81	2	feature	feature	NOUN
ajst-19195	81	3	map	map	NOUN
ajst-19195	81	4	after	after	SCONJ
ajst-19195	81	5	channel	channel	NOUN
ajst-19195	81	6	attention	attention	NOUN
ajst-19195	81	7	is	be	AUX
ajst-19195	81	8	given	give	VERB
ajst-19195	81	9	by	by	ADP
ajst-19195	81	10	the	the	DET
ajst-19195	81	11	equation	equation	NOUN
ajst-19195	81	12	'	'	PUNCT
ajst-19195	81	13	(	(	PUNCT
ajst-19195	81	14	)	)	PUNCT
ajst-19195	81	15	cf	cf	NOUN
ajst-19195	81	16	m	m	VERB
ajst-19195	81	17	f	f	X
ajst-19195	81	18	f	f	VERB
ajst-19195	81	19			NOUN
ajst-19195	81	20	and	and	CCONJ
ajst-19195	81	21	the	the	DET
ajst-19195	81	22	refined	refined	ADJ
ajst-19195	81	23	feature	feature	NOUN
ajst-19195	81	24	is	be	AUX
ajst-19195	81	25	obtained	obtain	VERB
ajst-19195	81	26	by	by	ADP
ajst-19195	81	27	the	the	DET
ajst-19195	81	28	equation	equation	NOUN
ajst-19195	81	29	''	''	PUNCT
ajst-19195	81	30	(	(	PUNCT
ajst-19195	81	31	'	'	PUNCT
ajst-19195	81	32	)	)	PUNCT
ajst-19195	81	33	'	'	PUNCT
ajst-19195	81	34	sf	sf	INTJ
ajst-19195	81	35	m	m	VERB
ajst-19195	81	36	f	f	X
ajst-19195	81	37	f	f	PROPN
ajst-19195	81	38			ADJ
ajst-19195	81	39	.	.	PUNCT
ajst-19195	82	1	the	the	DET
ajst-19195	82	2	cbam	cbam	NOUN
ajst-19195	82	3	is	be	AUX
ajst-19195	82	4	shown	show	VERB
ajst-19195	82	5	in	in	ADP
ajst-19195	82	6	fig	fig	NOUN
ajst-19195	82	7	.	.	PUNCT
ajst-19195	83	1	3	3	X
ajst-19195	83	2	.	.	X
ajst-19195	83	3	figure	figure	NOUN
ajst-19195	83	4	3	3	NUM
ajst-19195	83	5	.	.	PUNCT
ajst-19195	83	6	convolutional	convolutional	ADJ
ajst-19195	83	7	block	block	NOUN
ajst-19195	83	8	attention	attention	NOUN
ajst-19195	83	9	module	module	NOUN
ajst-19195	83	10	2.4	2.4	NUM
ajst-19195	83	11	.	.	PUNCT
ajst-19195	84	1	atrous	atrous	ADJ
ajst-19195	84	2	spatial	spatial	ADJ
ajst-19195	84	3	pyramidal	pyramidal	NOUN
ajst-19195	84	4	pooling	pool	VERB
ajst-19195	84	5	aspp	aspp	NOUN
ajst-19195	84	6	is	be	AUX
ajst-19195	84	7	composed	compose	VERB
ajst-19195	84	8	of	of	ADP
ajst-19195	84	9	multiple	multiple	ADJ
ajst-19195	84	10	parallel	parallel	ADJ
ajst-19195	84	11	atrous	atrous	ADJ
ajst-19195	84	12	convolutions	convolution	NOUN
ajst-19195	84	13	with	with	ADP
ajst-19195	84	14	different	different	ADJ
ajst-19195	84	15	sampling	sampling	NOUN
ajst-19195	84	16	rates	rate	NOUN
ajst-19195	84	17	and	and	CCONJ
ajst-19195	84	18	proportions	proportion	NOUN
ajst-19195	84	19	[	[	X
ajst-19195	84	20	15	15	NUM
ajst-19195	84	21	]	]	PUNCT
ajst-19195	84	22	.	.	PUNCT
ajst-19195	85	1	it	it	PRON
ajst-19195	85	2	consists	consist	VERB
ajst-19195	85	3	of	of	ADP
ajst-19195	85	4	convolution	convolution	NOUN
ajst-19195	85	5	kernels	kernel	NOUN
ajst-19195	85	6	with	with	ADP
ajst-19195	85	7	different	different	ADJ
ajst-19195	85	8	receptive	receptive	ADJ
ajst-19195	85	9	fields	field	NOUN
ajst-19195	85	10	,	,	PUNCT
ajst-19195	85	11	captures	capture	VERB
ajst-19195	85	12	contextual	contextual	ADJ
ajst-19195	85	13	information	information	NOUN
ajst-19195	85	14	,	,	PUNCT
ajst-19195	85	15	and	and	CCONJ
ajst-19195	85	16	accurately	accurately	ADV
ajst-19195	85	17	obtains	obtain	VERB
ajst-19195	85	18	multi	multi	ADJ
ajst-19195	85	19	-	-	ADJ
ajst-19195	85	20	scale	scale	ADJ
ajst-19195	85	21	information	information	NOUN
ajst-19195	85	22	.	.	PUNCT
ajst-19195	86	1	the	the	DET
ajst-19195	86	2	aspp	aspp	NOUN
ajst-19195	86	3	module	module	NOUN
ajst-19195	86	4	can	can	AUX
ajst-19195	86	5	solve	solve	VERB
ajst-19195	86	6	the	the	DET
ajst-19195	86	7	problem	problem	NOUN
ajst-19195	86	8	of	of	ADP
ajst-19195	86	9	the	the	DET
ajst-19195	86	10	loss	loss	NOUN
ajst-19195	86	11	of	of	ADP
ajst-19195	86	12	image	image	NOUN
ajst-19195	86	13	boundary	boundary	ADJ
ajst-19195	86	14	details	detail	NOUN
ajst-19195	86	15	caused	cause	VERB
ajst-19195	86	16	by	by	ADP
ajst-19195	86	17	the	the	DET
ajst-19195	86	18	decrease	decrease	NOUN
ajst-19195	86	19	of	of	ADP
ajst-19195	86	20	feature	feature	NOUN
ajst-19195	86	21	map	map	NOUN
ajst-19195	86	22	resolution	resolution	NOUN
ajst-19195	86	23	.	.	PUNCT
ajst-19195	87	1	it	it	PRON
ajst-19195	87	2	can	can	AUX
ajst-19195	87	3	also	also	ADV
ajst-19195	87	4	provide	provide	VERB
ajst-19195	87	5	different	different	ADJ
ajst-19195	87	6	receptive	receptive	ADJ
ajst-19195	87	7	fields	field	NOUN
ajst-19195	87	8	for	for	ADP
ajst-19195	87	9	image	image	NOUN
ajst-19195	87	10	feature	feature	NOUN
ajst-19195	87	11	extraction	extraction	NOUN
ajst-19195	87	12	to	to	PART
ajst-19195	87	13	prevent	prevent	VERB
ajst-19195	87	14	the	the	DET
ajst-19195	87	15	loss	loss	NOUN
ajst-19195	87	16	of	of	ADP
ajst-19195	87	17	too	too	ADV
ajst-19195	87	18	much	much	ADJ
ajst-19195	87	19	information	information	NOUN
ajst-19195	87	20	.	.	PUNCT
ajst-19195	88	1	252	252	NUM
ajst-19195	88	2	in	in	ADP
ajst-19195	88	3	this	this	DET
ajst-19195	88	4	proposed	propose	VERB
ajst-19195	88	5	network	network	NOUN
ajst-19195	88	6	,	,	PUNCT
ajst-19195	88	7	the	the	DET
ajst-19195	88	8	aspp	aspp	NOUN
ajst-19195	88	9	module	module	NOUN
ajst-19195	88	10	acts	act	VERB
ajst-19195	88	11	as	as	ADP
ajst-19195	88	12	a	a	DET
ajst-19195	88	13	bridge	bridge	NOUN
ajst-19195	88	14	between	between	ADP
ajst-19195	88	15	encoder	encoder	NOUN
ajst-19195	88	16	and	and	CCONJ
ajst-19195	88	17	decoder	decoder	NOUN
ajst-19195	88	18	to	to	PART
ajst-19195	88	19	capture	capture	VERB
ajst-19195	88	20	multi	multi	ADJ
ajst-19195	88	21	-	-	ADJ
ajst-19195	88	22	scale	scale	ADJ
ajst-19195	88	23	useful	useful	ADJ
ajst-19195	88	24	information	information	NOUN
ajst-19195	88	25	in	in	ADP
ajst-19195	88	26	semantic	semantic	ADJ
ajst-19195	88	27	segmentation	segmentation	NOUN
ajst-19195	88	28	tasks	task	NOUN
ajst-19195	88	29	[	[	X
ajst-19195	88	30	16	16	NUM
ajst-19195	88	31	]	]	PUNCT
ajst-19195	88	32	,	,	PUNCT
ajst-19195	88	33	which	which	PRON
ajst-19195	88	34	can	can	AUX
ajst-19195	88	35	effectively	effectively	ADV
ajst-19195	88	36	improve	improve	VERB
ajst-19195	88	37	the	the	DET
ajst-19195	88	38	accuracy	accuracy	NOUN
ajst-19195	88	39	of	of	ADP
ajst-19195	88	40	segmentation	segmentation	NOUN
ajst-19195	88	41	.	.	PUNCT
ajst-19195	89	1	2.5	2.5	NUM
ajst-19195	89	2	.	.	PUNCT
ajst-19195	90	1	combined	combine	VERB
ajst-19195	90	2	loss	loss	NOUN
ajst-19195	90	3	function	function	VERB
ajst-19195	90	4	the	the	DET
ajst-19195	90	5	phenomenon	phenomenon	NOUN
ajst-19195	90	6	of	of	ADP
ajst-19195	90	7	class	class	NOUN
ajst-19195	90	8	imbalance	imbalance	NOUN
ajst-19195	90	9	is	be	AUX
ajst-19195	90	10	challenging	challenge	VERB
ajst-19195	90	11	for	for	ADP
ajst-19195	90	12	medical	medical	ADJ
ajst-19195	90	13	image	image	NOUN
ajst-19195	90	14	segmentation	segmentation	NOUN
ajst-19195	91	1	[	[	X
ajst-19195	91	2	17	17	NUM
ajst-19195	91	3	]	]	PUNCT
ajst-19195	91	4	.	.	PUNCT
ajst-19195	92	1	although	although	SCONJ
ajst-19195	92	2	the	the	DET
ajst-19195	92	3	cross	cross	ADJ
ajst-19195	92	4	-	-	ADJ
ajst-19195	92	5	entropy	entropy	ADJ
ajst-19195	92	6	loss	loss	NOUN
ajst-19195	92	7	function	function	NOUN
ajst-19195	92	8	is	be	AUX
ajst-19195	92	9	popular	popular	ADJ
ajst-19195	92	10	in	in	ADP
ajst-19195	92	11	conventional	conventional	ADJ
ajst-19195	92	12	classification	classification	NOUN
ajst-19195	92	13	,	,	PUNCT
ajst-19195	92	14	it	it	PRON
ajst-19195	92	15	can	can	AUX
ajst-19195	92	16	not	not	PART
ajst-19195	92	17	obtain	obtain	VERB
ajst-19195	92	18	the	the	DET
ajst-19195	92	19	same	same	ADJ
ajst-19195	92	20	desirable	desirable	ADJ
ajst-19195	92	21	dice	dice	NOUN
ajst-19195	92	22	score	score	NOUN
ajst-19195	92	23	performance	performance	NOUN
ajst-19195	92	24	as	as	ADP
ajst-19195	92	25	the	the	DET
ajst-19195	92	26	dice	dice	NOUN
ajst-19195	92	27	loss	loss	NOUN
ajst-19195	92	28	function	function	NOUN
ajst-19195	92	29	.	.	PUNCT
ajst-19195	93	1	this	this	DET
ajst-19195	93	2	study	study	NOUN
ajst-19195	93	3	proposed	propose	VERB
ajst-19195	93	4	a	a	DET
ajst-19195	93	5	mixed	mixed	ADJ
ajst-19195	93	6	loss	loss	NOUN
ajst-19195	93	7	function	function	NOUN
ajst-19195	93	8	by	by	ADP
ajst-19195	93	9	combining	combine	VERB
ajst-19195	93	10	dice	dice	NOUN
ajst-19195	93	11	loss	loss	NOUN
ajst-19195	93	12	and	and	CCONJ
ajst-19195	93	13	cross	cross	ADJ
ajst-19195	93	14	-	-	ADJ
ajst-19195	93	15	entropy	entropy	ADJ
ajst-19195	93	16	loss	loss	NOUN
ajst-19195	93	17	,	,	PUNCT
ajst-19195	93	18	and	and	CCONJ
ajst-19195	93	19	the	the	DET
ajst-19195	93	20	mixed	mixed	ADJ
ajst-19195	93	21	loss	loss	NOUN
ajst-19195	93	22	function	function	NOUN
ajst-19195	93	23	can	can	AUX
ajst-19195	93	24	consider	consider	VERB
ajst-19195	93	25	the	the	DET
ajst-19195	93	26	weight	weight	NOUN
ajst-19195	93	27	information	information	NOUN
ajst-19195	93	28	of	of	ADP
ajst-19195	93	29	the	the	DET
ajst-19195	93	30	categories	category	NOUN
ajst-19195	93	31	of	of	ADP
ajst-19195	93	32	brain	brain	NOUN
ajst-19195	93	33	tumors	tumor	NOUN
ajst-19195	93	34	,	,	PUNCT
ajst-19195	93	35	and	and	CCONJ
ajst-19195	93	36	fully	fully	ADV
ajst-19195	93	37	suppress	suppress	VERB
ajst-19195	93	38	the	the	DET
ajst-19195	93	39	effect	effect	NOUN
ajst-19195	93	40	of	of	ADP
ajst-19195	93	41	category	category	NOUN
ajst-19195	93	42	imbalance	imbalance	NOUN
ajst-19195	93	43	on	on	ADP
ajst-19195	93	44	brain	brain	NOUN
ajst-19195	93	45	tumor	tumor	NOUN
ajst-19195	93	46	segmentation	segmentation	NOUN
ajst-19195	93	47	.	.	PUNCT
ajst-19195	94	1	the	the	DET
ajst-19195	94	2	definition	definition	NOUN
ajst-19195	94	3	formula	formula	NOUN
ajst-19195	94	4	of	of	ADP
ajst-19195	94	5	the	the	DET
ajst-19195	94	6	mixed	mixed	ADJ
ajst-19195	94	7	loss	loss	NOUN
ajst-19195	94	8	function	function	NOUN
ajst-19195	94	9	is	be	AUX
ajst-19195	94	10	as	as	SCONJ
ajst-19195	94	11	follows	follow	VERB
ajst-19195	94	12	:	:	PUNCT
ajst-19195	94	13	,	,	PUNCT
ajst-19195	94	14	,	,	PUNCT
ajst-19195	94	15	,	,	PUNCT
ajst-19195	94	16	,	,	PUNCT
ajst-19195	94	17	2	2	NUM
ajst-19195	94	18	2	2	NUM
ajst-19195	94	19	1	1	NUM
ajst-19195	94	20	1	1	NUM
ajst-19195	94	21	,	,	PUNCT
ajst-19195	94	22	,	,	PUNCT
ajst-19195	94	23	21	21	NUM
ajst-19195	94	24	(	(	PUNCT
ajst-19195	94	25	,	,	PUNCT
ajst-19195	94	26	)	)	PUNCT
ajst-19195	94	27	(	(	PUNCT
ajst-19195	94	28	log	log	NOUN
ajst-19195	94	29	)	)	PUNCT
ajst-19195	94	30	c	c	PROPN
ajst-19195	94	31	n	n	CCONJ
ajst-19195	94	32	n	n	PROPN
ajst-19195	94	33	c	c	NOUN
ajst-19195	95	1	n	n	ADP
ajst-19195	95	2	c	c	NOUN
ajst-19195	95	3	n	n	ADP
ajst-19195	95	4	c	c	NOUN
ajst-19195	95	5	n	n	NOUN
ajst-19195	95	6	c	c	NOUN
ajst-19195	95	7	c	c	NOUN
ajst-19195	95	8	n	n	CCONJ
ajst-19195	95	9	n	n	PROPN
ajst-19195	95	10	c	c	NOUN
ajst-19195	95	11	n	n	ADP
ajst-19195	95	12	c	c	NOUN
ajst-19195	95	13	y	y	PROPN
ajst-19195	95	14	p	p	PROPN
ajst-19195	95	15	y	y	PROPN
ajst-19195	95	16	p	p	PROPN
ajst-19195	95	17	y	y	PROPN
ajst-19195	95	18	p	p	PROPN
ajst-19195	95	19	n	n	PROPN
ajst-19195	95	20	y	y	PROPN
ajst-19195	95	21	p	p	PROPN
ajst-19195	95	22			PROPN
ajst-19195	96	1			NUM
ajst-19195	97	1			NUM
ajst-19195	97	2			PROPN
ajst-19195	97	3			PROPN
ajst-19195	97	4			NOUN
ajst-19195	97	5	(	(	PUNCT
ajst-19195	97	6	2	2	NUM
ajst-19195	97	7	)	)	PUNCT
ajst-19195	97	8	where	where	SCONJ
ajst-19195	97	9	,	,	PUNCT
ajst-19195	97	10	n	n	PROPN
ajst-19195	97	11	cy	cy	PROPN
ajst-19195	97	12	y	y	PROPN
ajst-19195	97	13	,	,	PUNCT
ajst-19195	97	14	y	y	PROPN
ajst-19195	97	15	and	and	CCONJ
ajst-19195	97	16	p	p	NOUN
ajst-19195	97	17	are	be	AUX
ajst-19195	97	18	the	the	DET
ajst-19195	97	19	retinal	retinal	ADJ
ajst-19195	97	20	image	image	NOUN
ajst-19195	97	21	truth	truth	NOUN
ajst-19195	97	22	value	value	NOUN
ajst-19195	97	23	and	and	CCONJ
ajst-19195	97	24	prediction	prediction	NOUN
ajst-19195	97	25	result	result	NOUN
ajst-19195	97	26	,	,	PUNCT
ajst-19195	97	27	respectively	respectively	ADV
ajst-19195	97	28	,	,	PUNCT
ajst-19195	97	29	c	c	PROPN
ajst-19195	97	30	and	and	CCONJ
ajst-19195	97	31	n	n	PROPN
ajst-19195	97	32	represent	represent	VERB
ajst-19195	97	33	the	the	DET
ajst-19195	97	34	number	number	NOUN
ajst-19195	97	35	of	of	ADP
ajst-19195	97	36	classes	class	NOUN
ajst-19195	97	37	and	and	CCONJ
ajst-19195	97	38	pixels	pixel	NOUN
ajst-19195	97	39	of	of	ADP
ajst-19195	97	40	the	the	DET
ajst-19195	97	41	dataset	dataset	NOUN
ajst-19195	97	42	in	in	ADP
ajst-19195	97	43	batch	batch	NOUN
ajst-19195	97	44	processing	processing	NOUN
ajst-19195	97	45	,	,	PUNCT
ajst-19195	97	46	respectively	respectively	ADV
ajst-19195	97	47	.	.	PUNCT
ajst-19195	98	1	3	3	X
ajst-19195	98	2	.	.	NOUN
ajst-19195	98	3	experiments	experiment	NOUN
ajst-19195	98	4	and	and	CCONJ
ajst-19195	98	5	analysis	analysis	NOUN
ajst-19195	98	6	3.1	3.1	NUM
ajst-19195	98	7	.	.	PUNCT
ajst-19195	99	1	datasets	dataset	VERB
ajst-19195	99	2	the	the	DET
ajst-19195	99	3	experimental	experimental	ADJ
ajst-19195	99	4	data	data	NOUN
ajst-19195	99	5	sets	set	NOUN
ajst-19195	99	6	are	be	AUX
ajst-19195	99	7	the	the	DET
ajst-19195	99	8	brats2018	brats2018	PROPN
ajst-19195	99	9	and	and	CCONJ
ajst-19195	99	10	brats2019	brats2019	PROPN
ajst-19195	99	11	public	public	ADJ
ajst-19195	99	12	datasets	dataset	NOUN
ajst-19195	99	13	provided	provide	VERB
ajst-19195	99	14	by	by	ADP
ajst-19195	99	15	brats	brat	NOUN
ajst-19195	99	16	[	[	X
ajst-19195	99	17	18	18	NUM
ajst-19195	99	18	,	,	PUNCT
ajst-19195	99	19	19	19	NUM
ajst-19195	99	20	]	]	PUNCT
ajst-19195	99	21	.	.	PUNCT
ajst-19195	100	1	the	the	DET
ajst-19195	100	2	brats2018	brats2018	PROPN
ajst-19195	100	3	dataset	dataset	NOUN
ajst-19195	100	4	contains	contain	VERB
ajst-19195	100	5	a	a	DET
ajst-19195	100	6	training	training	NOUN
ajst-19195	100	7	dataset	dataset	NOUN
ajst-19195	100	8	of	of	ADP
ajst-19195	100	9	210	210	NUM
ajst-19195	100	10	hgg	hgg	NOUN
ajst-19195	100	11	cases	case	NOUN
ajst-19195	100	12	and	and	CCONJ
ajst-19195	100	13	75	75	NUM
ajst-19195	100	14	lgg	lgg	NUM
ajst-19195	100	15	cases	case	NOUN
ajst-19195	100	16	.	.	PUNCT
ajst-19195	101	1	the	the	DET
ajst-19195	101	2	brats2019	brats2019	PROPN
ajst-19195	101	3	dataset	dataset	NOUN
ajst-19195	101	4	adds	add	VERB
ajst-19195	101	5	49	49	NUM
ajst-19195	101	6	hgg	hgg	NOUN
ajst-19195	101	7	cases	case	NOUN
ajst-19195	101	8	and	and	CCONJ
ajst-19195	101	9	1	1	NUM
ajst-19195	101	10	lgg	lgg	NOUN
ajst-19195	101	11	case	case	NOUN
ajst-19195	101	12	to	to	ADP
ajst-19195	101	13	the	the	DET
ajst-19195	101	14	brats2018	brats2018	PROPN
ajst-19195	101	15	dataset	dataset	NOUN
ajst-19195	101	16	.	.	PUNCT
ajst-19195	102	1	each	each	DET
ajst-19195	102	2	patient	patient	NOUN
ajst-19195	102	3	has	have	VERB
ajst-19195	102	4	four	four	NUM
ajst-19195	102	5	mri	mri	NOUN
ajst-19195	102	6	modalities	modality	NOUN
ajst-19195	102	7	(	(	PUNCT
ajst-19195	102	8	flair	flair	NOUN
ajst-19195	102	9	,	,	PUNCT
ajst-19195	102	10	t1	t1	NOUN
ajst-19195	102	11	,	,	PUNCT
ajst-19195	102	12	t1ce	t1ce	NUM
ajst-19195	102	13	,	,	PUNCT
ajst-19195	102	14	and	and	CCONJ
ajst-19195	102	15	t2	t2	NOUN
ajst-19195	102	16	)	)	PUNCT
ajst-19195	102	17	,	,	PUNCT
ajst-19195	102	18	and	and	CCONJ
ajst-19195	102	19	the	the	DET
ajst-19195	102	20	size	size	NOUN
ajst-19195	102	21	of	of	ADP
ajst-19195	102	22	each	each	DET
ajst-19195	102	23	mri	mri	NOUN
ajst-19195	102	24	image	image	NOUN
ajst-19195	102	25	in	in	ADP
ajst-19195	102	26	the	the	DET
ajst-19195	102	27	dataset	dataset	NOUN
ajst-19195	102	28	is	be	AUX
ajst-19195	102	29	240	240	NUM
ajst-19195	102	30	×	×	NOUN
ajst-19195	102	31	240	240	NUM
ajst-19195	102	32	×	×	NOUN
ajst-19195	102	33	155	155	NUM
ajst-19195	102	34	.	.	PUNCT
ajst-19195	102	35	images	image	NOUN
ajst-19195	102	36	with	with	ADP
ajst-19195	102	37	different	different	ADJ
ajst-19195	102	38	modes	mode	NOUN
ajst-19195	102	39	show	show	VERB
ajst-19195	102	40	different	different	ADJ
ajst-19195	102	41	parts	part	NOUN
ajst-19195	102	42	of	of	ADP
ajst-19195	102	43	the	the	DET
ajst-19195	102	44	tumor	tumor	NOUN
ajst-19195	102	45	.	.	PUNCT
ajst-19195	103	1	flair	flair	ADJ
ajst-19195	103	2	image	image	NOUN
ajst-19195	103	3	clearly	clearly	ADV
ajst-19195	103	4	shows	show	VERB
ajst-19195	103	5	the	the	DET
ajst-19195	103	6	whole	whole	ADJ
ajst-19195	103	7	tumor	tumor	NOUN
ajst-19195	103	8	,	,	PUNCT
ajst-19195	103	9	but	but	CCONJ
ajst-19195	103	10	can	can	AUX
ajst-19195	103	11	not	not	PART
ajst-19195	103	12	distinguish	distinguish	VERB
ajst-19195	103	13	the	the	DET
ajst-19195	103	14	necrotic	necrotic	ADJ
ajst-19195	103	15	components	component	NOUN
ajst-19195	103	16	.	.	PUNCT
ajst-19195	104	1	t1	t1	NOUN
ajst-19195	104	2	image	image	NOUN
ajst-19195	104	3	shows	show	VERB
ajst-19195	104	4	the	the	DET
ajst-19195	104	5	basic	basic	ADJ
ajst-19195	104	6	brain	brain	NOUN
ajst-19195	104	7	tumor	tumor	NOUN
ajst-19195	104	8	imaging	imaging	NOUN
ajst-19195	104	9	.	.	PUNCT
ajst-19195	105	1	t1ce	t1ce	X
ajst-19195	105	2	image	image	NOUN
ajst-19195	105	3	can	can	AUX
ajst-19195	105	4	distinguish	distinguish	VERB
ajst-19195	105	5	necrotic	necrotic	ADJ
ajst-19195	105	6	components	component	NOUN
ajst-19195	105	7	,	,	PUNCT
ajst-19195	105	8	but	but	CCONJ
ajst-19195	105	9	can	can	AUX
ajst-19195	105	10	not	not	PART
ajst-19195	105	11	identify	identify	VERB
ajst-19195	105	12	edema	edema	NOUN
ajst-19195	105	13	around	around	ADP
ajst-19195	105	14	tumors	tumor	NOUN
ajst-19195	105	15	from	from	ADP
ajst-19195	105	16	normal	normal	ADJ
ajst-19195	105	17	tissue	tissue	NOUN
ajst-19195	105	18	.	.	PUNCT
ajst-19195	106	1	t2	t2	NOUN
ajst-19195	106	2	image	image	NOUN
ajst-19195	106	3	are	be	AUX
ajst-19195	106	4	sensitive	sensitive	ADJ
ajst-19195	106	5	to	to	PART
ajst-19195	106	6	edema	edema	VERB
ajst-19195	106	7	around	around	ADP
ajst-19195	106	8	the	the	DET
ajst-19195	106	9	tumor	tumor	NOUN
ajst-19195	106	10	.	.	PUNCT
ajst-19195	107	1	brain	brain	NOUN
ajst-19195	107	2	tumor	tumor	NOUN
ajst-19195	107	3	labels	label	NOUN
ajst-19195	107	4	are	be	AUX
ajst-19195	107	5	divided	divide	VERB
ajst-19195	107	6	into	into	ADP
ajst-19195	107	7	three	three	NUM
ajst-19195	107	8	classes	class	NOUN
ajst-19195	107	9	:	:	PUNCT
ajst-19195	107	10	necrotic	necrotic	ADJ
ajst-19195	107	11	and	and	CCONJ
ajst-19195	107	12	non	non	ADJ
ajst-19195	107	13	-	-	ADJ
ajst-19195	107	14	enhancing	enhance	VERB
ajst-19195	107	15	tumor	tumor	NOUN
ajst-19195	107	16	core	core	NOUN
ajst-19195	107	17	(	(	PUNCT
ajst-19195	107	18	net	net	NOUN
ajst-19195	107	19	,	,	PUNCT
ajst-19195	107	20	label1	label1	PROPN
ajst-19195	107	21	)	)	PUNCT
ajst-19195	107	22	,	,	PUNCT
ajst-19195	107	23	peritumoral	peritumoral	ADJ
ajst-19195	107	24	edema	edema	NOUN
ajst-19195	107	25	(	(	PUNCT
ajst-19195	107	26	ed	ed	NOUN
ajst-19195	107	27	,	,	PUNCT
ajst-19195	107	28	label2	label2	PROPN
ajst-19195	107	29	)	)	PUNCT
ajst-19195	107	30	,	,	PUNCT
ajst-19195	107	31	and	and	CCONJ
ajst-19195	107	32	enhanced	enhance	VERB
ajst-19195	107	33	tumor	tumor	NOUN
ajst-19195	107	34	(	(	PUNCT
ajst-19195	107	35	et	et	NOUN
ajst-19195	107	36	,	,	PUNCT
ajst-19195	107	37	label4	label4	PROPN
ajst-19195	107	38	)	)	PUNCT
ajst-19195	107	39	.	.	PUNCT
ajst-19195	108	1	ground	ground	NOUN
ajst-19195	108	2	truth	truth	NOUN
ajst-19195	108	3	(	(	PUNCT
ajst-19195	108	4	gt	gt	INTJ
ajst-19195	108	5	)	)	PUNCT
ajst-19195	108	6	is	be	AUX
ajst-19195	108	7	manual	manual	ADJ
ajst-19195	108	8	segmentation	segmentation	NOUN
ajst-19195	108	9	of	of	ADP
ajst-19195	108	10	brain	brain	NOUN
ajst-19195	108	11	tumors	tumor	NOUN
ajst-19195	108	12	by	by	ADP
ajst-19195	108	13	experienced	experienced	ADJ
ajst-19195	108	14	experts	expert	NOUN
ajst-19195	108	15	.	.	PUNCT
ajst-19195	109	1	to	to	PART
ajst-19195	109	2	better	well	ADV
ajst-19195	109	3	evaluate	evaluate	VERB
ajst-19195	109	4	the	the	DET
ajst-19195	109	5	segmentation	segmentation	NOUN
ajst-19195	109	6	effect	effect	NOUN
ajst-19195	109	7	,	,	PUNCT
ajst-19195	109	8	it	it	PRON
ajst-19195	109	9	is	be	AUX
ajst-19195	109	10	necessary	necessary	ADJ
ajst-19195	109	11	to	to	PART
ajst-19195	109	12	segment	segment	VERB
ajst-19195	109	13	whole	whole	ADJ
ajst-19195	109	14	tumor	tumor	NOUN
ajst-19195	109	15	(	(	PUNCT
ajst-19195	109	16	wt	wt	NOUN
ajst-19195	109	17	,	,	PUNCT
ajst-19195	109	18	net	net	NOUN
ajst-19195	109	19	+	+	CCONJ
ajst-19195	109	20	ed	ed	NOUN
ajst-19195	109	21	+	+	NUM
ajst-19195	109	22	et	et	NOUN
ajst-19195	109	23	)	)	PUNCT
ajst-19195	109	24	,	,	PUNCT
ajst-19195	109	25	tumor	tumor	NOUN
ajst-19195	109	26	core	core	NOUN
ajst-19195	109	27	(	(	PUNCT
ajst-19195	109	28	tc	tc	NOUN
ajst-19195	109	29	,	,	PUNCT
ajst-19195	109	30	net	net	NOUN
ajst-19195	109	31	+	+	CCONJ
ajst-19195	109	32	et	et	NOUN
ajst-19195	109	33	)	)	PUNCT
ajst-19195	109	34	,	,	PUNCT
ajst-19195	109	35	and	and	CCONJ
ajst-19195	109	36	enhanced	enhance	VERB
ajst-19195	109	37	tumor	tumor	NOUN
ajst-19195	109	38	(	(	PUNCT
ajst-19195	109	39	et	et	NOUN
ajst-19195	109	40	)	)	PUNCT
ajst-19195	109	41	(	(	PUNCT
ajst-19195	109	42	see	see	VERB
ajst-19195	109	43	table	table	NOUN
ajst-19195	109	44	1	1	NUM
ajst-19195	109	45	)	)	PUNCT
ajst-19195	109	46	.	.	PUNCT
ajst-19195	110	1	fig	fig	NOUN
ajst-19195	110	2	.	.	PUNCT
ajst-19195	111	1	4	4	NUM
ajst-19195	111	2	illuminates	illuminate	VERB
ajst-19195	111	3	a	a	DET
ajst-19195	111	4	typical	typical	ADJ
ajst-19195	111	5	case	case	NOUN
ajst-19195	111	6	of	of	ADP
ajst-19195	111	7	mri	mri	NOUN
ajst-19195	111	8	brain	brain	NOUN
ajst-19195	111	9	image	image	NOUN
ajst-19195	111	10	and	and	CCONJ
ajst-19195	111	11	gt	gt	PROPN
ajst-19195	111	12	.	.	PROPN
ajst-19195	111	13	figure	figure	NOUN
ajst-19195	111	14	4	4	NUM
ajst-19195	111	15	.	.	NOUN
ajst-19195	111	16	example	example	NOUN
ajst-19195	111	17	of	of	ADP
ajst-19195	111	18	the	the	DET
ajst-19195	111	19	brain	brain	NOUN
ajst-19195	111	20	mri	mri	NOUN
ajst-19195	111	21	data	datum	NOUN
ajst-19195	111	22	from	from	ADP
ajst-19195	111	23	a	a	DET
ajst-19195	111	24	patient	patient	NOUN
ajst-19195	111	25	in	in	ADP
ajst-19195	111	26	the	the	DET
ajst-19195	111	27	brats2018	brats2018	PROPN
ajst-19195	111	28	dataset	dataset	NOUN
ajst-19195	111	29	.	.	PUNCT
ajst-19195	112	1	from	from	ADP
ajst-19195	112	2	left	left	ADJ
ajst-19195	112	3	to	to	ADP
ajst-19195	112	4	right	right	NOUN
ajst-19195	112	5	:	:	PUNCT
ajst-19195	112	6	flair	flair	NOUN
ajst-19195	112	7	modality	modality	NOUN
ajst-19195	112	8	,	,	PUNCT
ajst-19195	112	9	t1	t1	NOUN
ajst-19195	112	10	modality	modality	NOUN
ajst-19195	112	11	,	,	PUNCT
ajst-19195	112	12	t1ce	t1ce	X
ajst-19195	112	13	modality	modality	NOUN
ajst-19195	112	14	,	,	PUNCT
ajst-19195	112	15	t2	t2	NOUN
ajst-19195	112	16	modality	modality	NOUN
ajst-19195	112	17	and	and	CCONJ
ajst-19195	112	18	ground	ground	NOUN
ajst-19195	112	19	truth	truth	NOUN
ajst-19195	112	20	.	.	PUNCT
ajst-19195	113	1	3.2	3.2	NUM
ajst-19195	113	2	.	.	PUNCT
ajst-19195	113	3	datasets	dataset	NOUN
ajst-19195	113	4	first	first	ADV
ajst-19195	113	5	,	,	PUNCT
ajst-19195	113	6	the	the	DET
ajst-19195	113	7	contrast	contrast	NOUN
ajst-19195	113	8	of	of	ADP
ajst-19195	113	9	mri	mri	NOUN
ajst-19195	113	10	images	image	NOUN
ajst-19195	113	11	of	of	ADP
ajst-19195	113	12	different	different	ADJ
ajst-19195	113	13	modalities	modality	NOUN
ajst-19195	113	14	is	be	AUX
ajst-19195	113	15	different	different	ADJ
ajst-19195	113	16	,	,	PUNCT
ajst-19195	113	17	and	and	CCONJ
ajst-19195	113	18	it	it	PRON
ajst-19195	113	19	is	be	AUX
ajst-19195	113	20	easy	easy	ADJ
ajst-19195	113	21	to	to	PART
ajst-19195	113	22	produce	produce	VERB
ajst-19195	113	23	overfitting	overfitting	NOUN
ajst-19195	113	24	in	in	ADP
ajst-19195	113	25	the	the	DET
ajst-19195	113	26	training	training	NOUN
ajst-19195	113	27	process	process	NOUN
ajst-19195	113	28	.	.	PUNCT
ajst-19195	114	1	in	in	ADP
ajst-19195	114	2	this	this	DET
ajst-19195	114	3	study	study	NOUN
ajst-19195	114	4	,	,	PUNCT
ajst-19195	114	5	the	the	DET
ajst-19195	114	6	z	z	NOUN
ajst-19195	114	7	-	-	PUNCT
ajst-19195	114	8	score	score	NOUN
ajst-19195	114	9	normalization	normalization	NOUN
ajst-19195	114	10	method	method	NOUN
ajst-19195	114	11	is	be	AUX
ajst-19195	114	12	used	use	VERB
ajst-19195	114	13	to	to	PART
ajst-19195	114	14	normalize	normalize	VERB
ajst-19195	114	15	the	the	DET
ajst-19195	114	16	mean	mean	ADJ
ajst-19195	114	17	value	value	NOUN
ajst-19195	114	18	of	of	ADP
ajst-19195	114	19	the	the	DET
ajst-19195	114	20	four	four	NUM
ajst-19195	114	21	modalities	modality	NOUN
ajst-19195	114	22	of	of	ADP
ajst-19195	114	23	patient	patient	ADJ
ajst-19195	114	24	data	datum	NOUN
ajst-19195	114	25	.	.	PUNCT
ajst-19195	115	1	secondly	secondly	ADV
ajst-19195	115	2	,	,	PUNCT
ajst-19195	115	3	the	the	DET
ajst-19195	115	4	size	size	NOUN
ajst-19195	115	5	of	of	ADP
ajst-19195	115	6	brain	brain	NOUN
ajst-19195	115	7	tumor	tumor	NOUN
ajst-19195	115	8	images	image	NOUN
ajst-19195	115	9	in	in	ADP
ajst-19195	115	10	the	the	DET
ajst-19195	115	11	brats	brat	NOUN
ajst-19195	115	12	dataset	dataset	VERB
ajst-19195	115	13	is	be	AUX
ajst-19195	115	14	155×240×240	155×240×240	NUM
ajst-19195	115	15	,	,	PUNCT
ajst-19195	115	16	there	there	PRON
ajst-19195	115	17	are	be	VERB
ajst-19195	115	18	a	a	DET
ajst-19195	115	19	large	large	ADJ
ajst-19195	115	20	number	number	NOUN
ajst-19195	115	21	of	of	ADP
ajst-19195	115	22	background	background	NOUN
ajst-19195	115	23	regions	region	NOUN
ajst-19195	115	24	that	that	PRON
ajst-19195	115	25	do	do	AUX
ajst-19195	115	26	not	not	PART
ajst-19195	115	27	contain	contain	VERB
ajst-19195	115	28	brain	brain	NOUN
ajst-19195	115	29	tumor	tumor	NOUN
ajst-19195	115	30	information	information	NOUN
ajst-19195	115	31	,	,	PUNCT
ajst-19195	115	32	and	and	CCONJ
ajst-19195	115	33	they	they	PRON
ajst-19195	115	34	account	account	VERB
ajst-19195	115	35	for	for	ADP
ajst-19195	115	36	a	a	DET
ajst-19195	115	37	large	large	ADJ
ajst-19195	115	38	proportion	proportion	NOUN
ajst-19195	115	39	in	in	ADP
ajst-19195	115	40	the	the	DET
ajst-19195	115	41	overall	overall	ADJ
ajst-19195	115	42	image	image	NOUN
ajst-19195	115	43	,	,	PUNCT
ajst-19195	115	44	which	which	PRON
ajst-19195	115	45	will	will	AUX
ajst-19195	115	46	affect	affect	VERB
ajst-19195	115	47	the	the	DET
ajst-19195	115	48	extraction	extraction	NOUN
ajst-19195	115	49	of	of	ADP
ajst-19195	115	50	brain	brain	NOUN
ajst-19195	115	51	tumor	tumor	NOUN
ajst-19195	115	52	feature	feature	NOUN
ajst-19195	115	53	information	information	NOUN
ajst-19195	115	54	.	.	PUNCT
ajst-19195	116	1	therefore	therefore	ADV
ajst-19195	116	2	,	,	PUNCT
ajst-19195	116	3	the	the	DET
ajst-19195	116	4	image	image	NOUN
ajst-19195	116	5	slices	slice	NOUN
ajst-19195	116	6	are	be	AUX
ajst-19195	116	7	cropped	crop	VERB
ajst-19195	116	8	to	to	PART
ajst-19195	116	9	filter	filter	VERB
ajst-19195	116	10	useless	useless	ADJ
ajst-19195	116	11	information	information	NOUN
ajst-19195	116	12	,	,	PUNCT
ajst-19195	116	13	and	and	CCONJ
ajst-19195	116	14	finally	finally	ADV
ajst-19195	116	15	155	155	NUM
ajst-19195	116	16	image	image	NOUN
ajst-19195	116	17	slices	slice	NOUN
ajst-19195	116	18	with	with	ADP
ajst-19195	116	19	a	a	DET
ajst-19195	116	20	size	size	NOUN
ajst-19195	116	21	of	of	ADP
ajst-19195	116	22	160×160	160×160	NUM
ajst-19195	116	23	are	be	AUX
ajst-19195	116	24	obtained	obtain	VERB
ajst-19195	116	25	.	.	PUNCT
ajst-19195	117	1	finally	finally	ADV
ajst-19195	117	2	,	,	PUNCT
ajst-19195	117	3	data	datum	NOUN
ajst-19195	117	4	enhancement	enhancement	NOUN
ajst-19195	117	5	was	be	AUX
ajst-19195	117	6	performed	perform	VERB
ajst-19195	117	7	on	on	ADP
ajst-19195	117	8	the	the	DET
ajst-19195	117	9	image	image	NOUN
ajst-19195	117	10	slices	slice	NOUN
ajst-19195	117	11	,	,	PUNCT
ajst-19195	117	12	and	and	CCONJ
ajst-19195	117	13	the	the	DET
ajst-19195	117	14	slices	slice	NOUN
ajst-19195	117	15	that	that	PRON
ajst-19195	117	16	did	do	AUX
ajst-19195	117	17	not	not	PART
ajst-19195	117	18	contain	contain	VERB
ajst-19195	117	19	brain	brain	NOUN
ajst-19195	117	20	tumors	tumor	NOUN
ajst-19195	117	21	were	be	AUX
ajst-19195	117	22	removed	remove	VERB
ajst-19195	117	23	to	to	PART
ajst-19195	117	24	solve	solve	VERB
ajst-19195	117	25	the	the	DET
ajst-19195	117	26	problem	problem	NOUN
ajst-19195	117	27	of	of	ADP
ajst-19195	117	28	class	class	NOUN
ajst-19195	117	29	imbalance	imbalance	NOUN
ajst-19195	117	30	.	.	PUNCT
ajst-19195	118	1	after	after	ADP
ajst-19195	118	2	preprocessing	preprocesse	VERB
ajst-19195	118	3	,	,	PUNCT
ajst-19195	118	4	the	the	DET
ajst-19195	118	5	four	four	NUM
ajst-19195	118	6	modal	modal	ADJ
ajst-19195	118	7	outputs	output	NOUN
ajst-19195	118	8	are	be	AUX
ajst-19195	118	9	merged	merge	VERB
ajst-19195	118	10	and	and	CCONJ
ajst-19195	118	11	saved	save	VERB
ajst-19195	118	12	as	as	ADP
ajst-19195	118	13	npy	npy	PROPN
ajst-19195	118	14	format	format	NOUN
ajst-19195	118	15	.	.	PUNCT
ajst-19195	119	1	we	we	PRON
ajst-19195	119	2	processed	process	VERB
ajst-19195	119	3	the	the	DET
ajst-19195	119	4	brats2018	brats2018	PROPN
ajst-19195	119	5	dataset	dataset	NOUN
ajst-19195	119	6	(	(	PUNCT
ajst-19195	119	7	210	210	NUM
ajst-19195	119	8	hgg	hgg	NOUN
ajst-19195	119	9	cases	case	NOUN
ajst-19195	119	10	and	and	CCONJ
ajst-19195	119	11	75	75	NUM
ajst-19195	119	12	lgg	lgg	NUM
ajst-19195	119	13	cases	case	NOUN
ajst-19195	119	14	)	)	PUNCT
ajst-19195	119	15	to	to	PART
ajst-19195	119	16	generate	generate	VERB
ajst-19195	119	17	a	a	DET
ajst-19195	119	18	training	training	NOUN
ajst-19195	119	19	set	set	NOUN
ajst-19195	119	20	,	,	PUNCT
ajst-19195	119	21	and	and	CCONJ
ajst-19195	119	22	the	the	DET
ajst-19195	119	23	newly	newly	ADV
ajst-19195	119	24	added	add	VERB
ajst-19195	119	25	brats2019	brats2019	PROPN
ajst-19195	119	26	dataset	dataset	VERB
ajst-19195	119	27	(	(	PUNCT
ajst-19195	119	28	49	49	NUM
ajst-19195	119	29	hgg	hgg	NOUN
ajst-19195	119	30	cases	case	NOUN
ajst-19195	119	31	and	and	CCONJ
ajst-19195	119	32	1	1	NUM
ajst-19195	119	33	lgg	lgg	NUM
ajst-19195	119	34	case	case	NOUN
ajst-19195	119	35	)	)	PUNCT
ajst-19195	119	36	to	to	PART
ajst-19195	119	37	generate	generate	VERB
ajst-19195	119	38	a	a	DET
ajst-19195	119	39	test	test	NOUN
ajst-19195	119	40	set	set	VERB
ajst-19195	119	41	.	.	PUNCT
ajst-19195	120	1	3.3	3.3	NUM
ajst-19195	120	2	.	.	PUNCT
ajst-19195	121	1	experimental	experimental	ADJ
ajst-19195	121	2	settings	setting	NOUN
ajst-19195	121	3	the	the	DET
ajst-19195	121	4	pytorch	pytorch	NOUN
ajst-19195	121	5	deep	deep	ADJ
ajst-19195	121	6	learning	learning	NOUN
ajst-19195	121	7	framework	framework	NOUN
ajst-19195	121	8	was	be	AUX
ajst-19195	121	9	employed	employ	VERB
ajst-19195	121	10	to	to	PART
ajst-19195	121	11	conduct	conduct	VERB
ajst-19195	121	12	the	the	DET
ajst-19195	121	13	experiments	experiment	NOUN
ajst-19195	121	14	.	.	PUNCT
ajst-19195	122	1	software	software	NOUN
ajst-19195	122	2	environment	environment	NOUN
ajst-19195	122	3	:	:	PUNCT
ajst-19195	123	1	win10	win10	PROPN
ajst-19195	123	2	and	and	CCONJ
ajst-19195	123	3	python	python	NOUN
ajst-19195	123	4	3.6	3.6	NUM
ajst-19195	123	5	and	and	CCONJ
ajst-19195	123	6	cuda10.0	cuda10.0	VERB
ajst-19195	123	7	,	,	PUNCT
ajst-19195	123	8	cudnn7.6.5	cudnn7.6.5	PROPN
ajst-19195	123	9	.	.	PROPN
ajst-19195	123	10	hardware	hardware	NOUN
ajst-19195	123	11	environment	environment	PROPN
ajst-19195	123	12	:	:	PUNCT
ajst-19195	123	13	cpu	cpu	VERB
ajst-19195	123	14	i5	i5	NOUN
ajst-19195	123	15	-	-	PUNCT
ajst-19195	123	16	7	7	NUM
ajst-19195	123	17	generation	generation	NOUN
ajst-19195	123	18	(	(	PUNCT
ajst-19195	123	19	4	4	NUM
ajst-19195	123	20	cores	core	NOUN
ajst-19195	123	21	)	)	PUNCT
ajst-19195	123	22	,	,	PUNCT
ajst-19195	123	23	16	16	NUM
ajst-19195	123	24	g	g	PROPN
ajst-19195	123	25	memory	memory	NOUN
ajst-19195	123	26	,	,	PUNCT
ajst-19195	123	27	gpu	gpu	PROPN
ajst-19195	123	28	12	12	NUM
ajst-19195	123	29	gb	gb	PROPN
ajst-19195	123	30	nvidia	nvidia	PROPN
ajst-19195	123	31	gtx1080ti	gtx1080ti	PROPN
ajst-19195	123	32	.	.	PUNCT
ajst-19195	124	1	the	the	DET
ajst-19195	124	2	training	training	NOUN
ajst-19195	124	3	set	set	NOUN
ajst-19195	124	4	consisting	consist	VERB
ajst-19195	124	5	of	of	ADP
ajst-19195	124	6	the	the	DET
ajst-19195	124	7	brats2018	brats2018	PROPN
ajst-19195	124	8	dataset	dataset	NOUN
ajst-19195	124	9	was	be	AUX
ajst-19195	124	10	randomly	randomly	ADV
ajst-19195	124	11	divided	divide	VERB
ajst-19195	124	12	,	,	PUNCT
ajst-19195	124	13	with	with	ADP
ajst-19195	124	14	75	75	NUM
ajst-19195	124	15	%	%	NOUN
ajst-19195	124	16	as	as	ADP
ajst-19195	124	17	the	the	DET
ajst-19195	124	18	training	training	NOUN
ajst-19195	124	19	set	set	NOUN
ajst-19195	124	20	and	and	CCONJ
ajst-19195	124	21	25	25	NUM
ajst-19195	124	22	%	%	NOUN
ajst-19195	124	23	as	as	ADP
ajst-19195	124	24	the	the	DET
ajst-19195	124	25	verification	verification	NOUN
ajst-19195	124	26	set	set	NOUN
ajst-19195	124	27	.	.	PUNCT
ajst-19195	125	1	epoch	epoch	PROPN
ajst-19195	125	2	was	be	AUX
ajst-19195	125	3	10000	10000	NUM
ajst-19195	125	4	,	,	PUNCT
ajst-19195	125	5	weight	weight	NOUN
ajst-19195	125	6	_	_	PUNCT
ajst-19195	125	7	decay	decay	NOUN
ajst-19195	125	8	was	be	AUX
ajst-19195	125	9	0.0001	0.0001	NUM
ajst-19195	125	10	,	,	PUNCT
ajst-19195	125	11	early	early	ADJ
ajst-19195	125	12	stopping	stopping	NOUN
ajst-19195	125	13	was	be	AUX
ajst-19195	125	14	10	10	NUM
ajst-19195	125	15	,	,	PUNCT
ajst-19195	125	16	and	and	CCONJ
ajst-19195	125	17	training	training	NOUN
ajst-19195	125	18	was	be	AUX
ajst-19195	125	19	performed	perform	VERB
ajst-19195	125	20	using	use	VERB
ajst-19195	125	21	the	the	DET
ajst-19195	125	22	adam	adam	PROPN
ajst-19195	125	23	optimizer	optimizer	NOUN
ajst-19195	125	24	[	[	X
ajst-19195	125	25	20	20	NUM
ajst-19195	125	26	]	]	PUNCT
ajst-19195	125	27	.	.	PUNCT
ajst-19195	126	1	all	all	PRON
ajst-19195	126	2	of	of	ADP
ajst-19195	126	3	the	the	DET
ajst-19195	126	4	models	model	NOUN
ajst-19195	126	5	were	be	AUX
ajst-19195	126	6	trained	train	VERB
ajst-19195	126	7	by	by	ADP
ajst-19195	126	8	using	use	VERB
ajst-19195	126	9	the	the	DET
ajst-19195	126	10	same	same	ADJ
ajst-19195	126	11	datasets	dataset	NOUN
ajst-19195	126	12	,	,	PUNCT
ajst-19195	126	13	the	the	DET
ajst-19195	126	14	same	same	ADJ
ajst-19195	126	15	hardware	hardware	NOUN
ajst-19195	126	16	environment	environment	NOUN
ajst-19195	126	17	,	,	PUNCT
ajst-19195	126	18	and	and	CCONJ
ajst-19195	126	19	their	their	PRON
ajst-19195	126	20	optimal	optimal	ADJ
ajst-19195	126	21	parameter	parameter	NOUN
ajst-19195	126	22	settings	setting	NOUN
ajst-19195	126	23	.	.	PUNCT
ajst-19195	127	1	3.4	3.4	NUM
ajst-19195	127	2	.	.	PUNCT
ajst-19195	127	3	evaluation	evaluation	NOUN
ajst-19195	127	4	metric	metric	ADJ
ajst-19195	127	5	dice	dice	NOUN
ajst-19195	127	6	similarity	similarity	NOUN
ajst-19195	127	7	coefficient	coefficient	NOUN
ajst-19195	127	8	(	(	PUNCT
ajst-19195	127	9	dsc	dsc	NOUN
ajst-19195	127	10	)	)	PUNCT
ajst-19195	127	11	and	and	CCONJ
ajst-19195	127	12	hausdorff	hausdorff	PROPN
ajst-19195	127	13	distance	distance	NOUN
ajst-19195	127	14	(	(	PUNCT
ajst-19195	127	15	hd	hd	NOUN
ajst-19195	127	16	)	)	PUNCT
ajst-19195	127	17	coefficient	coefficient	NOUN
ajst-19195	127	18	are	be	AUX
ajst-19195	127	19	used	use	VERB
ajst-19195	127	20	to	to	PART
ajst-19195	127	21	assess	assess	VERB
ajst-19195	127	22	the	the	DET
ajst-19195	127	23	proposed	propose	VERB
ajst-19195	127	24	approach	approach	NOUN
ajst-19195	127	25	,	,	PUNCT
ajst-19195	127	26	which	which	PRON
ajst-19195	127	27	are	be	AUX
ajst-19195	127	28	the	the	DET
ajst-19195	127	29	two	two	NUM
ajst-19195	127	30	most	most	ADV
ajst-19195	127	31	commonly	commonly	ADV
ajst-19195	127	32	used	use	VERB
ajst-19195	127	33	evaluation	evaluation	NOUN
ajst-19195	127	34	metrics	metric	NOUN
ajst-19195	127	35	for	for	ADP
ajst-19195	127	36	brain	brain	NOUN
ajst-19195	127	37	tumor	tumor	NOUN
ajst-19195	127	38	segmentation	segmentation	NOUN
ajst-19195	128	1	[	[	X
ajst-19195	128	2	21	21	NUM
ajst-19195	128	3	]	]	PUNCT
ajst-19195	128	4	.	.	PUNCT
ajst-19195	129	1	dsc	dsc	PROPN
ajst-19195	129	2	is	be	AUX
ajst-19195	129	3	used	use	VERB
ajst-19195	129	4	to	to	PART
ajst-19195	129	5	evaluate	evaluate	VERB
ajst-19195	129	6	the	the	DET
ajst-19195	129	7	similarity	similarity	NOUN
ajst-19195	129	8	between	between	ADP
ajst-19195	129	9	segmentation	segmentation	NOUN
ajst-19195	129	10	prediction	prediction	NOUN
ajst-19195	129	11	and	and	CCONJ
ajst-19195	129	12	ground	ground	NOUN
ajst-19195	129	13	truth	truth	NOUN
ajst-19195	129	14	.	.	PUNCT
ajst-19195	130	1	the	the	DET
ajst-19195	130	2	calculation	calculation	NOUN
ajst-19195	130	3	formulas	formula	NOUN
ajst-19195	130	4	of	of	ADP
ajst-19195	130	5	the	the	DET
ajst-19195	130	6	evaluation	evaluation	NOUN
ajst-19195	130	7	metrics	metric	NOUN
ajst-19195	130	8	are	be	AUX
ajst-19195	130	9	as	as	SCONJ
ajst-19195	130	10	follows	follow	VERB
ajst-19195	130	11	:	:	PUNCT
ajst-19195	130	12	2	2	NUM
ajst-19195	130	13	2	2	NUM
ajst-19195	130	14	tp	tp	NOUN
ajst-19195	130	15	dsc	dsc	PROPN
ajst-19195	131	1	fn	fn	PROPN
ajst-19195	132	1	fp	fp	INTJ
ajst-19195	132	2	tp	tp	ADP
ajst-19195	132	3			PROPN
ajst-19195	132	4			ADV
ajst-19195	132	5			X
ajst-19195	132	6	(	(	PUNCT
ajst-19195	132	7	3	3	X
ajst-19195	132	8	)	)	PUNCT
ajst-19195	132	9	where	where	SCONJ
ajst-19195	132	10	tp	tp	NOUN
ajst-19195	132	11	represents	represent	VERB
ajst-19195	132	12	the	the	DET
ajst-19195	132	13	area	area	NOUN
ajst-19195	132	14	correctly	correctly	ADV
ajst-19195	132	15	detected	detect	VERB
ajst-19195	132	16	as	as	ADP
ajst-19195	132	17	a	a	DET
ajst-19195	132	18	positive	positive	ADJ
ajst-19195	132	19	sample	sample	NOUN
ajst-19195	132	20	,	,	PUNCT
ajst-19195	132	21	fp	fp	X
ajst-19195	132	22	represents	represent	VERB
ajst-19195	132	23	the	the	DET
ajst-19195	132	24	area	area	NOUN
ajst-19195	132	25	incorrectly	incorrectly	ADV
ajst-19195	132	26	detected	detect	VERB
ajst-19195	132	27	as	as	ADP
ajst-19195	132	28	a	a	DET
ajst-19195	132	29	positive	positive	ADJ
ajst-19195	132	30	sample	sample	NOUN
ajst-19195	132	31	,	,	PUNCT
ajst-19195	132	32	and	and	CCONJ
ajst-19195	132	33	fn	fn	NOUN
ajst-19195	132	34	represents	represent	VERB
ajst-19195	132	35	the	the	DET
ajst-19195	132	36	area	area	NOUN
ajst-19195	132	37	incorrectly	incorrectly	ADV
ajst-19195	132	38	detected	detect	VERB
ajst-19195	132	39	as	as	ADP
ajst-19195	132	40	a	a	DET
ajst-19195	132	41	negative	negative	ADJ
ajst-19195	132	42	sample	sample	NOUN
ajst-19195	132	43	.	.	PUNCT
ajst-19195	133	1	besides	besides	ADV
ajst-19195	133	2	,	,	PUNCT
ajst-19195	133	3	hd	hd	NOUN
ajst-19195	133	4	represents	represent	VERB
ajst-19195	133	5	the	the	DET
ajst-19195	133	6	maximum	maximum	ADJ
ajst-19195	133	7	mismatch	mismatch	NOUN
ajst-19195	133	8	between	between	ADP
ajst-19195	133	9	the	the	DET
ajst-19195	133	10	tumor	tumor	NOUN
ajst-19195	133	11	segmentation	segmentation	NOUN
ajst-19195	133	12	results	result	NOUN
ajst-19195	133	13	and	and	CCONJ
ajst-19195	133	14	the	the	DET
ajst-19195	133	15	labels	label	NOUN
ajst-19195	133	16	,	,	PUNCT
ajst-19195	133	17	and	and	CCONJ
ajst-19195	133	18	the	the	DET
ajst-19195	133	19	smaller	small	ADJ
ajst-19195	133	20	the	the	DET
ajst-19195	133	21	hd	hd	NOUN
ajst-19195	133	22	,	,	PUNCT
ajst-19195	133	23	the	the	PRON
ajst-19195	133	24	higher	high	ADJ
ajst-19195	133	25	the	the	DET
ajst-19195	133	26	accuracy	accuracy	NOUN
ajst-19195	133	27	.	.	PUNCT
ajst-19195	134	1	the	the	DET
ajst-19195	134	2	calculation	calculation	NOUN
ajst-19195	134	3	formulas	formula	NOUN
ajst-19195	134	4	of	of	ADP
ajst-19195	134	5	the	the	DET
ajst-19195	134	6	evaluation	evaluation	NOUN
ajst-19195	134	7	metrics	metric	NOUN
ajst-19195	134	8	are	be	AUX
ajst-19195	134	9	as	as	SCONJ
ajst-19195	134	10	follows	follow	VERB
ajst-19195	134	11	:	:	PUNCT
ajst-19195	134	12			PROPN
ajst-19195	134	13	max	max	PROPN
ajst-19195	134	14	max	max	PROPN
ajst-19195	134	15	min	min	PROPN
ajst-19195	134	16	,	,	PUNCT
ajst-19195	134	17	max	max	PROPN
ajst-19195	134	18	min	min	PROPN
ajst-19195	134	19	y	y	PROPN
ajst-19195	134	20	y	y	PROPN
ajst-19195	134	21	x	x	PROPN
ajst-19195	135	1	xx	xx	NUM
ajst-19195	135	2	x	x	SYM
ajst-19195	135	3	y	y	AUX
ajst-19195	135	4	y	y	PROPN
ajst-19195	135	5	hd	hd	VERB
ajst-19195	135	6	x	x	PROPN
ajst-19195	135	7	y	y	NOUN
ajst-19195	135	8	y	y	PROPN
ajst-19195	135	9	x	x	PROPN
ajst-19195	135	10			NOUN
ajst-19195	135	11			NUM
ajst-19195	135	12			PROPN
ajst-19195	135	13			PROPN
ajst-19195	135	14			PROPN
ajst-19195	135	15			NOUN
ajst-19195	135	16	(	(	PUNCT
ajst-19195	135	17	4	4	NUM
ajst-19195	135	18	)	)	PUNCT
ajst-19195	135	19	where	where	SCONJ
ajst-19195	135	20	x	x	PRON
ajst-19195	135	21	represents	represent	VERB
ajst-19195	135	22	the	the	DET
ajst-19195	135	23	true	true	ADJ
ajst-19195	135	24	result	result	NOUN
ajst-19195	135	25	image	image	NOUN
ajst-19195	135	26	and	and	CCONJ
ajst-19195	135	27	y	y	PROPN
ajst-19195	135	28	represents	represent	VERB
ajst-19195	135	29	the	the	DET
ajst-19195	135	30	predicted	predict	VERB
ajst-19195	135	31	result	result	NOUN
ajst-19195	135	32	image	image	NOUN
ajst-19195	135	33	.	.	PUNCT
ajst-19195	136	1	3.5	3.5	NUM
ajst-19195	136	2	.	.	PUNCT
ajst-19195	137	1	experimental	experimental	ADJ
ajst-19195	137	2	results	result	NOUN
ajst-19195	137	3	in	in	ADP
ajst-19195	137	4	order	order	NOUN
ajst-19195	137	5	to	to	PART
ajst-19195	137	6	evaluate	evaluate	VERB
ajst-19195	137	7	the	the	DET
ajst-19195	137	8	effectiveness	effectiveness	NOUN
ajst-19195	137	9	of	of	ADP
ajst-19195	137	10	the	the	DET
ajst-19195	137	11	proposed	propose	VERB
ajst-19195	137	12	methods	method	NOUN
ajst-19195	137	13	objectively	objectively	ADV
ajst-19195	137	14	,	,	PUNCT
ajst-19195	137	15	four	four	NUM
ajst-19195	137	16	network	network	NOUN
ajst-19195	137	17	models	model	NOUN
ajst-19195	137	18	,	,	PUNCT
ajst-19195	137	19	named	name	VERB
ajst-19195	137	20	unet++	unet++	PROPN
ajst-19195	137	21	,	,	PUNCT
ajst-19195	137	22	resunet++	resunet++	NOUN
ajst-19195	137	23	,	,	PUNCT
ajst-19195	137	24	cbam	cbam	NOUN
ajst-19195	137	25	-	-	PUNCT
ajst-19195	137	26	unet	unet	NOUN
ajst-19195	137	27	+	+	PROPN
ajst-19195	137	28	+	+	NUM
ajst-19195	137	29	and	and	CCONJ
ajst-19195	137	30	ac	ac	PROPN
ajst-19195	137	31	-	-	PUNCT
ajst-19195	137	32	resunet++	resunet++	NOUN
ajst-19195	137	33	,	,	PUNCT
ajst-19195	137	34	are	be	AUX
ajst-19195	137	35	tested	test	VERB
ajst-19195	137	36	in	in	ADP
ajst-19195	137	37	the	the	DET
ajst-19195	137	38	present	present	ADJ
ajst-19195	137	39	study	study	NOUN
ajst-19195	137	40	.	.	PUNCT
ajst-19195	138	1	the	the	DET
ajst-19195	138	2	newly	newly	ADV
ajst-19195	138	3	added	add	VERB
ajst-19195	138	4	data	datum	NOUN
ajst-19195	138	5	set	set	NOUN
ajst-19195	138	6	(	(	PUNCT
ajst-19195	138	7	49	49	NUM
ajst-19195	138	8	cases	case	NOUN
ajst-19195	138	9	of	of	ADP
ajst-19195	138	10	high	high	ADJ
ajst-19195	138	11	-	-	PUNCT
ajst-19195	138	12	grade	grade	NOUN
ajst-19195	138	13	gliomas	glioma	NOUN
ajst-19195	138	14	and	and	CCONJ
ajst-19195	138	15	1	1	NUM
ajst-19195	138	16	case	case	NOUN
ajst-19195	138	17	of	of	ADP
ajst-19195	138	18	low	low	ADJ
ajst-19195	138	19	-	-	PUNCT
ajst-19195	138	20	grade	grade	NOUN
ajst-19195	138	21	gliomas	glioma	NOUN
ajst-19195	138	22	)	)	PUNCT
ajst-19195	138	23	of	of	ADP
ajst-19195	138	24	brats	brat	NOUN
ajst-19195	138	25	2019	2019	NUM
ajst-19195	138	26	is	be	AUX
ajst-19195	138	27	used	use	VERB
ajst-19195	138	28	as	as	ADP
ajst-19195	138	29	the	the	DET
ajst-19195	138	30	test	test	NOUN
ajst-19195	138	31	set	set	NOUN
ajst-19195	138	32	.	.	PUNCT
ajst-19195	139	1	the	the	DET
ajst-19195	139	2	dsc	dsc	NOUN
ajst-19195	139	3	scores	score	NOUN
ajst-19195	139	4	of	of	ADP
ajst-19195	139	5	wt	wt	PROPN
ajst-19195	139	6	,	,	PUNCT
ajst-19195	139	7	tc	tc	NOUN
ajst-19195	139	8	253	253	NUM
ajst-19195	139	9	and	and	CCONJ
ajst-19195	139	10	et	et	NOUN
ajst-19195	139	11	regions	region	NOUN
ajst-19195	139	12	of	of	ADP
ajst-19195	139	13	brain	brain	NOUN
ajst-19195	139	14	tumors	tumor	NOUN
ajst-19195	139	15	were	be	AUX
ajst-19195	139	16	0.8418	0.8418	NUM
ajst-19195	139	17	,	,	PUNCT
ajst-19195	139	18	0.8276	0.8276	NUM
ajst-19195	139	19	,	,	PUNCT
ajst-19195	139	20	0.7712	0.7712	NUM
ajst-19195	139	21	for	for	ADP
ajst-19195	139	22	unet++	unet++	PROPN
ajst-19195	139	23	,	,	PUNCT
ajst-19195	139	24	0.8385	0.8385	NUM
ajst-19195	139	25	,	,	PUNCT
ajst-19195	139	26	0.8390	0.8390	NUM
ajst-19195	139	27	,	,	PUNCT
ajst-19195	139	28	0.7712	0.7712	NUM
ajst-19195	139	29	for	for	ADP
ajst-19195	139	30	resunet++	resunet++	NOUN
ajst-19195	139	31	,	,	PUNCT
ajst-19195	139	32	0.8508	0.8508	NUM
ajst-19195	139	33	,	,	PUNCT
ajst-19195	139	34	0.8153	0.8153	NUM
ajst-19195	139	35	,	,	PUNCT
ajst-19195	139	36	0.7822	0.7822	NOUN
ajst-19195	139	37	for	for	ADP
ajst-19195	139	38	cbam	cbam	NOUN
ajst-19195	139	39	-	-	PUNCT
ajst-19195	139	40	unet++	unet++	PROPN
ajst-19195	139	41	,	,	PUNCT
ajst-19195	139	42	and	and	CCONJ
ajst-19195	139	43	0.8521	0.8521	NUM
ajst-19195	139	44	,	,	PUNCT
ajst-19195	139	45	0.8696	0.8696	NUM
ajst-19195	139	46	,	,	PUNCT
ajst-19195	139	47	0.7868	0.7868	NUM
ajst-19195	139	48	for	for	ADP
ajst-19195	139	49	ac	ac	PROPN
ajst-19195	139	50	-	-	PUNCT
ajst-19195	139	51	resunet++	resunet++	NOUN
ajst-19195	139	52	,	,	PUNCT
ajst-19195	139	53	respectively	respectively	ADV
ajst-19195	139	54	.	.	PUNCT
ajst-19195	140	1	the	the	DET
ajst-19195	140	2	experimental	experimental	ADJ
ajst-19195	140	3	results	result	NOUN
ajst-19195	140	4	are	be	AUX
ajst-19195	140	5	shown	show	VERB
ajst-19195	140	6	in	in	ADP
ajst-19195	140	7	table	table	NOUN
ajst-19195	140	8	1	1	NUM
ajst-19195	140	9	and	and	CCONJ
ajst-19195	140	10	fig	fig	NOUN
ajst-19195	140	11	.	.	PUNCT
ajst-19195	141	1	5	5	NUM
ajst-19195	141	2	.	.	PUNCT
ajst-19195	141	3	compared	compare	VERB
ajst-19195	141	4	with	with	ADP
ajst-19195	141	5	the	the	DET
ajst-19195	141	6	unet++	unet++	PROPN
ajst-19195	141	7	network	network	NOUN
ajst-19195	141	8	,	,	PUNCT
ajst-19195	141	9	the	the	DET
ajst-19195	141	10	dsc	dsc	NOUN
ajst-19195	141	11	of	of	ADP
ajst-19195	141	12	the	the	DET
ajst-19195	141	13	ac	ac	PROPN
ajst-19195	141	14	-	-	PUNCT
ajst-19195	141	15	resunet++	resunet++	NOUN
ajst-19195	141	16	network	network	NOUN
ajst-19195	141	17	proposed	propose	VERB
ajst-19195	141	18	in	in	ADP
ajst-19195	141	19	this	this	DET
ajst-19195	141	20	paper	paper	NOUN
ajst-19195	141	21	in	in	ADP
ajst-19195	141	22	the	the	DET
ajst-19195	141	23	three	three	NUM
ajst-19195	141	24	different	different	ADJ
ajst-19195	141	25	subregions	subregion	NOUN
ajst-19195	141	26	of	of	ADP
ajst-19195	141	27	wt	wt	PROPN
ajst-19195	141	28	,	,	PUNCT
ajst-19195	141	29	tc	tc	NOUN
ajst-19195	141	30	,	,	PUNCT
ajst-19195	141	31	and	and	CCONJ
ajst-19195	141	32	et	et	NOUN
ajst-19195	141	33	increased	increase	VERB
ajst-19195	141	34	by	by	ADP
ajst-19195	141	35	1.22	1.22	NUM
ajst-19195	141	36	%	%	NOUN
ajst-19195	141	37	,	,	PUNCT
ajst-19195	141	38	5.08	5.08	NUM
ajst-19195	141	39	%	%	NOUN
ajst-19195	141	40	,	,	PUNCT
ajst-19195	141	41	and	and	CCONJ
ajst-19195	141	42	2.03	2.03	NUM
ajst-19195	141	43	%	%	NOUN
ajst-19195	141	44	,	,	PUNCT
ajst-19195	141	45	respectively	respectively	ADV
ajst-19195	141	46	.	.	PUNCT
ajst-19195	142	1	our	our	PRON
ajst-19195	142	2	results	result	NOUN
ajst-19195	142	3	show	show	VERB
ajst-19195	142	4	that	that	SCONJ
ajst-19195	142	5	the	the	DET
ajst-19195	142	6	model	model	NOUN
ajst-19195	142	7	has	have	VERB
ajst-19195	142	8	a	a	DET
ajst-19195	142	9	good	good	ADJ
ajst-19195	142	10	segmenting	segmenting	NOUN
ajst-19195	142	11	performance	performance	NOUN
ajst-19195	142	12	for	for	ADP
ajst-19195	142	13	all	all	DET
ajst-19195	142	14	regions	region	NOUN
ajst-19195	142	15	,	,	PUNCT
ajst-19195	142	16	especially	especially	ADV
ajst-19195	142	17	for	for	ADP
ajst-19195	142	18	the	the	DET
ajst-19195	142	19	tumor	tumor	NOUN
ajst-19195	142	20	core	core	NOUN
ajst-19195	142	21	area	area	NOUN
ajst-19195	142	22	,	,	PUNCT
ajst-19195	142	23	which	which	PRON
ajst-19195	142	24	gets	get	VERB
ajst-19195	142	25	the	the	DET
ajst-19195	142	26	highest	high	ADJ
ajst-19195	142	27	score	score	NOUN
ajst-19195	142	28	.	.	PUNCT
ajst-19195	143	1	in	in	ADP
ajst-19195	143	2	addition	addition	NOUN
ajst-19195	143	3	to	to	ADP
ajst-19195	143	4	the	the	DET
ajst-19195	143	5	dsc	dsc	NOUN
ajst-19195	143	6	,	,	PUNCT
ajst-19195	143	7	this	this	DET
ajst-19195	143	8	study	study	NOUN
ajst-19195	143	9	also	also	ADV
ajst-19195	143	10	took	take	VERB
ajst-19195	143	11	hausdoff	hausdoff	NOUN
ajst-19195	143	12	coefficient	coefficient	NOUN
ajst-19195	143	13	to	to	PART
ajst-19195	143	14	evaluate	evaluate	VERB
ajst-19195	143	15	the	the	DET
ajst-19195	143	16	segmentation	segmentation	NOUN
ajst-19195	143	17	.	.	PUNCT
ajst-19195	144	1	compared	compare	VERB
ajst-19195	144	2	with	with	ADP
ajst-19195	144	3	the	the	DET
ajst-19195	144	4	unet++	unet++	PROPN
ajst-19195	144	5	network	network	NOUN
ajst-19195	144	6	,	,	PUNCT
ajst-19195	144	7	the	the	DET
ajst-19195	144	8	hausdoff	hausdoff	NOUN
ajst-19195	144	9	coefficients	coefficient	NOUN
ajst-19195	144	10	of	of	ADP
ajst-19195	144	11	the	the	DET
ajst-19195	144	12	ac	ac	ADJ
ajst-19195	144	13	-	-	PUNCT
ajst-19195	144	14	resunet++	resunet++	NOUN
ajst-19195	144	15	network	network	NOUN
ajst-19195	144	16	in	in	ADP
ajst-19195	144	17	the	the	DET
ajst-19195	144	18	wt	wt	NOUN
ajst-19195	144	19	,	,	PUNCT
ajst-19195	144	20	tc	tc	PRON
ajst-19195	144	21	and	and	CCONJ
ajst-19195	144	22	et	et	NOUN
ajst-19195	144	23	increased	increase	VERB
ajst-19195	144	24	by	by	ADP
ajst-19195	144	25	1.41	1.41	NUM
ajst-19195	144	26	%	%	NOUN
ajst-19195	144	27	,	,	PUNCT
ajst-19195	144	28	9.77	9.77	NUM
ajst-19195	144	29	%	%	NOUN
ajst-19195	144	30	,	,	PUNCT
ajst-19195	144	31	and	and	CCONJ
ajst-19195	144	32	1.77	1.77	NUM
ajst-19195	144	33	%	%	NOUN
ajst-19195	144	34	,	,	PUNCT
ajst-19195	144	35	respectively	respectively	ADV
ajst-19195	144	36	.	.	PUNCT
ajst-19195	145	1	in	in	ADP
ajst-19195	145	2	order	order	NOUN
ajst-19195	145	3	to	to	PART
ajst-19195	145	4	intuitively	intuitively	ADV
ajst-19195	145	5	view	view	VERB
ajst-19195	145	6	the	the	DET
ajst-19195	145	7	segmentation	segmentation	NOUN
ajst-19195	145	8	results	result	NOUN
ajst-19195	145	9	and	and	CCONJ
ajst-19195	145	10	observe	observe	VERB
ajst-19195	145	11	the	the	DET
ajst-19195	145	12	spatial	spatial	ADJ
ajst-19195	145	13	location	location	NOUN
ajst-19195	145	14	of	of	ADP
ajst-19195	145	15	the	the	DET
ajst-19195	145	16	brain	brain	NOUN
ajst-19195	145	17	tumor	tumor	NOUN
ajst-19195	145	18	,	,	PUNCT
ajst-19195	145	19	the	the	DET
ajst-19195	145	20	segmentation	segmentation	NOUN
ajst-19195	145	21	results	result	VERB
ajst-19195	145	22	from	from	ADP
ajst-19195	145	23	one	one	NUM
ajst-19195	145	24	patient	patient	NOUN
ajst-19195	145	25	are	be	AUX
ajst-19195	145	26	visualized	visualize	VERB
ajst-19195	145	27	(	(	PUNCT
ajst-19195	145	28	fig	fig	NOUN
ajst-19195	145	29	.	.	PUNCT
ajst-19195	146	1	6	6	NUM
ajst-19195	146	2	)	)	PUNCT
ajst-19195	146	3	.	.	PUNCT
ajst-19195	147	1	the	the	DET
ajst-19195	147	2	loss	loss	NOUN
ajst-19195	147	3	rates	rate	NOUN
ajst-19195	147	4	of	of	ADP
ajst-19195	147	5	the	the	DET
ajst-19195	147	6	training	training	NOUN
ajst-19195	147	7	and	and	CCONJ
ajst-19195	147	8	test	test	NOUN
ajst-19195	147	9	sets	set	NOUN
ajst-19195	147	10	of	of	ADP
ajst-19195	147	11	the	the	DET
ajst-19195	147	12	network	network	NOUN
ajst-19195	147	13	are	be	AUX
ajst-19195	147	14	plotted	plot	VERB
ajst-19195	147	15	in	in	ADP
ajst-19195	147	16	fig	fig	NOUN
ajst-19195	147	17	.	.	PUNCT
ajst-19195	148	1	7	7	X
ajst-19195	148	2	.	.	X
ajst-19195	148	3	table	table	NOUN
ajst-19195	148	4	1	1	NUM
ajst-19195	148	5	.	.	PUNCT
ajst-19195	148	6	evaluation	evaluation	NOUN
ajst-19195	148	7	results	result	NOUN
ajst-19195	148	8	of	of	ADP
ajst-19195	148	9	four	four	NUM
ajst-19195	148	10	segmented	segment	VERB
ajst-19195	148	11	models	model	NOUN
ajst-19195	148	12	on	on	ADP
ajst-19195	148	13	the	the	DET
ajst-19195	148	14	brats	brat	NOUN
ajst-19195	148	15	2019	2019	NUM
ajst-19195	148	16	dataset	dataset	NOUN
ajst-19195	148	17	.	.	PUNCT
ajst-19195	149	1	methods	method	NOUN
ajst-19195	149	2	dsc	dsc	PROPN
ajst-19195	149	3	hd	hd	PROPN
ajst-19195	149	4	wt	wt	PROPN
ajst-19195	149	5	tc	tc	INTJ
ajst-19195	149	6	et	et	NOUN
ajst-19195	149	7	wt	wt	NOUN
ajst-19195	149	8	tc	tc	NUM
ajst-19195	149	9	et	et	NOUN
ajst-19195	149	10	unet++	unet++	ADJ
ajst-19195	149	11	0.8418	0.8418	NUM
ajst-19195	149	12	0.8276	0.8276	NUM
ajst-19195	149	13	0.7712	0.7712	NUM
ajst-19195	149	14	2.6222	2.6222	NUM
ajst-19195	149	15	1.7309	1.7309	NUM
ajst-19195	149	16	2.8039	2.8039	NUM
ajst-19195	149	17	resunet++	resunet++	NOUN
ajst-19195	149	18	0.8404	0.8404	NUM
ajst-19195	149	19	0.8414	0.8414	NUM
ajst-19195	149	20	0.7693	0.7693	NUM
ajst-19195	149	21	2.6216	2.6216	NUM
ajst-19195	149	22	1.7330	1.7330	NUM
ajst-19195	149	23	2.8288	2.8288	NUM
ajst-19195	149	24	cbam	cbam	NOUN
ajst-19195	149	25	-	-	PUNCT
ajst-19195	149	26	unet++	unet++	PROPN
ajst-19195	149	27	0.8508	0.8508	NUM
ajst-19195	149	28	0.8153	0.8153	NUM
ajst-19195	149	29	0.7822	0.7822	NUM
ajst-19195	149	30	2.6114	2.6114	NUM
ajst-19195	149	31	1.7345	1.7345	NUM
ajst-19195	149	32	2.7755	2.7755	NUM
ajst-19195	149	33	our	our	PRON
ajst-19195	149	34	0.8521	0.8521	NUM
ajst-19195	149	35	0.8696	0.8696	NUM
ajst-19195	149	36	0.7868	0.7868	NUM
ajst-19195	149	37	2.5854	2.5854	NUM
ajst-19195	149	38	1.5618	1.5618	NUM
ajst-19195	149	39	2.7544	2.7544	NUM
ajst-19195	149	40	figure	figure	NOUN
ajst-19195	149	41	5	5	NUM
ajst-19195	149	42	.	.	PUNCT
ajst-19195	150	1	the	the	DET
ajst-19195	150	2	percentages	percentage	NOUN
ajst-19195	150	3	of	of	ADP
ajst-19195	150	4	performance	performance	NOUN
ajst-19195	150	5	improvement	improvement	NOUN
ajst-19195	150	6	of	of	ADP
ajst-19195	150	7	acresunet	acresunet	NOUN
ajst-19195	150	8	+	+	NOUN
ajst-19195	150	9	+	+	ADJ
ajst-19195	150	10	in	in	ADP
ajst-19195	150	11	dsc	dsc	NOUN
ajst-19195	150	12	and	and	CCONJ
ajst-19195	150	13	hd	hd	PROPN
ajst-19195	150	14	evaluation	evaluation	NOUN
ajst-19195	150	15	index	index	NOUN
ajst-19195	150	16	compared	compare	VERB
ajst-19195	150	17	with	with	ADP
ajst-19195	150	18	unet++	unet++	ADJ
ajst-19195	150	19	figure	figure	NOUN
ajst-19195	150	20	6	6	NUM
ajst-19195	150	21	.	.	PUNCT
ajst-19195	151	1	the	the	DET
ajst-19195	151	2	brain	brain	NOUN
ajst-19195	151	3	tumor	tumor	NOUN
ajst-19195	151	4	segmentation	segmentation	NOUN
ajst-19195	151	5	results	result	NOUN
ajst-19195	151	6	in	in	ADP
ajst-19195	151	7	brats2019	brats2019	PROPN
ajst-19195	151	8	.	.	PUNCT
ajst-19195	152	1	red	red	ADJ
ajst-19195	152	2	,	,	PUNCT
ajst-19195	152	3	non	non	ADJ
ajst-19195	152	4	-	-	ADJ
ajst-19195	152	5	enhanced	enhanced	ADJ
ajst-19195	152	6	and	and	CCONJ
ajst-19195	152	7	necrotic	necrotic	ADJ
ajst-19195	152	8	tumor	tumor	NOUN
ajst-19195	152	9	areas	area	NOUN
ajst-19195	152	10	.	.	PUNCT
ajst-19195	153	1	yellow	yellow	ADJ
ajst-19195	153	2	,	,	PUNCT
ajst-19195	153	3	enhanced	enhance	VERB
ajst-19195	153	4	tumor	tumor	NOUN
ajst-19195	153	5	areas	area	NOUN
ajst-19195	153	6	.	.	PUNCT
ajst-19195	154	1	green	green	ADJ
ajst-19195	154	2	,	,	PUNCT
ajst-19195	154	3	edema	edema	PROPN
ajst-19195	154	4	areas	area	NOUN
ajst-19195	154	5	figure	figure	VERB
ajst-19195	154	6	7	7	NUM
ajst-19195	154	7	.	.	PUNCT
ajst-19195	154	8	loss	loss	NOUN
ajst-19195	154	9	graph	graph	NOUN
ajst-19195	154	10	of	of	ADP
ajst-19195	154	11	the	the	DET
ajst-19195	154	12	training	training	NOUN
ajst-19195	154	13	and	and	CCONJ
ajst-19195	154	14	validation	validation	NOUN
ajst-19195	154	15	sets	set	NOUN
ajst-19195	154	16	of	of	ADP
ajst-19195	154	17	acresunet++	acresunet++	PROPN
ajst-19195	154	18	.	.	PUNCT
ajst-19195	155	1	val_loss	val_loss	PROPN
ajst-19195	155	2	is	be	AUX
ajst-19195	155	3	represented	represent	VERB
ajst-19195	155	4	by	by	ADP
ajst-19195	155	5	a	a	DET
ajst-19195	155	6	red	red	ADJ
ajst-19195	155	7	curve	curve	NOUN
ajst-19195	155	8	that	that	PRON
ajst-19195	155	9	represents	represent	VERB
ajst-19195	155	10	the	the	DET
ajst-19195	155	11	loss	loss	NOUN
ajst-19195	155	12	change	change	NOUN
ajst-19195	155	13	of	of	ADP
ajst-19195	155	14	the	the	DET
ajst-19195	155	15	validation	validation	NOUN
ajst-19195	155	16	set	set	VERB
ajst-19195	155	17	during	during	ADP
ajst-19195	155	18	model	model	NOUN
ajst-19195	155	19	training	training	NOUN
ajst-19195	155	20	,	,	PUNCT
ajst-19195	155	21	and	and	CCONJ
ajst-19195	155	22	loss	loss	NOUN
ajst-19195	155	23	is	be	AUX
ajst-19195	155	24	represented	represent	VERB
ajst-19195	155	25	by	by	ADP
ajst-19195	155	26	a	a	DET
ajst-19195	155	27	blue	blue	ADJ
ajst-19195	155	28	curve	curve	NOUN
ajst-19195	155	29	that	that	PRON
ajst-19195	155	30	represents	represent	VERB
ajst-19195	155	31	the	the	DET
ajst-19195	155	32	loss	loss	NOUN
ajst-19195	155	33	change	change	NOUN
ajst-19195	155	34	of	of	ADP
ajst-19195	155	35	the	the	DET
ajst-19195	155	36	training	training	NOUN
ajst-19195	155	37	set	set	VERB
ajst-19195	155	38	during	during	ADP
ajst-19195	155	39	model	model	NOUN
ajst-19195	155	40	training	training	NOUN
ajst-19195	155	41	.	.	PUNCT
ajst-19195	156	1	4	4	X
ajst-19195	156	2	.	.	X
ajst-19195	156	3	conclusion	conclusion	NOUN
ajst-19195	156	4	in	in	ADP
ajst-19195	156	5	this	this	DET
ajst-19195	156	6	study	study	NOUN
ajst-19195	156	7	,	,	PUNCT
ajst-19195	156	8	we	we	PRON
ajst-19195	156	9	proposed	propose	VERB
ajst-19195	156	10	an	an	DET
ajst-19195	156	11	improved	improved	ADJ
ajst-19195	156	12	segmentation	segmentation	NOUN
ajst-19195	156	13	model	model	NOUN
ajst-19195	156	14	based	base	VERB
ajst-19195	156	15	on	on	ADP
ajst-19195	156	16	unet++	unet++	PROPN
ajst-19195	156	17	,	,	PUNCT
ajst-19195	156	18	ac	ac	ADJ
ajst-19195	156	19	-	-	PUNCT
ajst-19195	156	20	resunet++	resunet++	NOUN
ajst-19195	156	21	network	network	NOUN
ajst-19195	156	22	,	,	PUNCT
ajst-19195	156	23	which	which	PRON
ajst-19195	156	24	combines	combine	VERB
ajst-19195	156	25	residual	residual	ADJ
ajst-19195	156	26	module	module	NOUN
ajst-19195	156	27	,	,	PUNCT
ajst-19195	156	28	cbam	cbam	NOUN
ajst-19195	156	29	and	and	CCONJ
ajst-19195	156	30	aspp	aspp	NOUN
ajst-19195	156	31	module	module	NOUN
ajst-19195	156	32	.	.	PUNCT
ajst-19195	157	1	in	in	ADP
ajst-19195	157	2	the	the	DET
ajst-19195	157	3	proposed	propose	VERB
ajst-19195	157	4	network	network	NOUN
ajst-19195	157	5	,	,	PUNCT
ajst-19195	157	6	cbam	cbam	NOUN
ajst-19195	157	7	and	and	CCONJ
ajst-19195	157	8	residual	residual	ADJ
ajst-19195	157	9	module	module	NOUN
ajst-19195	157	10	were	be	AUX
ajst-19195	157	11	added	add	VERB
ajst-19195	157	12	to	to	ADP
ajst-19195	157	13	the	the	DET
ajst-19195	157	14	network	network	NOUN
ajst-19195	157	15	skip	skip	NOUN
ajst-19195	157	16	connections	connection	NOUN
ajst-19195	157	17	,	,	PUNCT
ajst-19195	157	18	enhancing	enhance	VERB
ajst-19195	157	19	the	the	DET
ajst-19195	157	20	ability	ability	NOUN
ajst-19195	157	21	of	of	ADP
ajst-19195	157	22	local	local	ADJ
ajst-19195	157	23	feature	feature	NOUN
ajst-19195	157	24	expression	expression	NOUN
ajst-19195	157	25	and	and	CCONJ
ajst-19195	157	26	small	small	ADJ
ajst-19195	157	27	feature	feature	NOUN
ajst-19195	157	28	extraction	extraction	NOUN
ajst-19195	157	29	.	.	PUNCT
ajst-19195	158	1	aspp	aspp	NOUN
ajst-19195	158	2	module	module	NOUN
ajst-19195	158	3	was	be	AUX
ajst-19195	158	4	added	add	VERB
ajst-19195	158	5	between	between	ADP
ajst-19195	158	6	encoder	encoder	NOUN
ajst-19195	158	7	and	and	CCONJ
ajst-19195	158	8	decoder	decoder	NOUN
ajst-19195	158	9	to	to	PART
ajst-19195	158	10	extract	extract	VERB
ajst-19195	158	11	effective	effective	ADJ
ajst-19195	158	12	multi	multi	ADJ
ajst-19195	158	13	-	-	ADJ
ajst-19195	158	14	scale	scale	ADJ
ajst-19195	158	15	information	information	NOUN
ajst-19195	158	16	.	.	PUNCT
ajst-19195	159	1	the	the	DET
ajst-19195	159	2	brats	brat	NOUN
ajst-19195	159	3	2018	2018	NUM
ajst-19195	159	4	and	and	CCONJ
ajst-19195	159	5	brats	brat	NOUN
ajst-19195	159	6	2019	2019	NUM
ajst-19195	159	7	datasets	dataset	NOUN
ajst-19195	159	8	were	be	AUX
ajst-19195	159	9	used	use	VERB
ajst-19195	159	10	to	to	PART
ajst-19195	159	11	evaluate	evaluate	VERB
ajst-19195	159	12	the	the	DET
ajst-19195	159	13	performance	performance	NOUN
ajst-19195	159	14	of	of	ADP
ajst-19195	159	15	the	the	DET
ajst-19195	159	16	proposed	propose	VERB
ajst-19195	159	17	network	network	NOUN
ajst-19195	159	18	.	.	PUNCT
ajst-19195	160	1	compared	compare	VERB
ajst-19195	160	2	with	with	ADP
ajst-19195	160	3	unet++	unet++	PROPN
ajst-19195	160	4	,	,	PUNCT
ajst-19195	160	5	ac	ac	PROPN
ajst-19195	160	6	-	-	PUNCT
ajst-19195	160	7	resunet++	resunet++	NOUN
ajst-19195	160	8	improves	improve	VERB
ajst-19195	160	9	the	the	DET
ajst-19195	160	10	dsc	dsc	NOUN
ajst-19195	160	11	score	score	NOUN
ajst-19195	160	12	of	of	ADP
ajst-19195	160	13	wt	wt	PROPN
ajst-19195	160	14	,	,	PUNCT
ajst-19195	160	15	tc	tc	PROPN
ajst-19195	160	16	and	and	CCONJ
ajst-19195	160	17	et	et	NOUN
ajst-19195	160	18	by	by	ADP
ajst-19195	160	19	1.22	1.22	NUM
ajst-19195	160	20	%	%	NOUN
ajst-19195	160	21	,	,	PUNCT
ajst-19195	160	22	5.08	5.08	NUM
ajst-19195	160	23	%	%	NOUN
ajst-19195	160	24	and	and	CCONJ
ajst-19195	160	25	2.03	2.03	NUM
ajst-19195	160	26	%	%	NOUN
ajst-19195	160	27	,	,	PUNCT
ajst-19195	160	28	respectively	respectively	ADV
ajst-19195	160	29	.	.	PUNCT
ajst-19195	161	1	the	the	DET
ajst-19195	161	2	results	result	NOUN
ajst-19195	161	3	confirm	confirm	VERB
ajst-19195	161	4	the	the	DET
ajst-19195	161	5	effectiveness	effectiveness	NOUN
ajst-19195	161	6	of	of	ADP
ajst-19195	161	7	our	our	PRON
ajst-19195	161	8	proposed	propose	VERB
ajst-19195	161	9	segmentation	segmentation	NOUN
ajst-19195	161	10	model	model	NOUN
ajst-19195	161	11	.	.	PUNCT
ajst-19195	162	1	references	reference	NOUN
ajst-19195	162	2	[	[	X
ajst-19195	162	3	1	1	X
ajst-19195	162	4	]	]	X
ajst-19195	162	5	magadza	magadza	PROPN
ajst-19195	162	6	t	t	PROPN
ajst-19195	162	7	,	,	PUNCT
ajst-19195	162	8	viriri	viriri	PROPN
ajst-19195	162	9	s.	s.	PROPN
ajst-19195	162	10	deep	deep	PROPN
ajst-19195	162	11	learning	learn	VERB
ajst-19195	162	12	for	for	ADP
ajst-19195	162	13	brain	brain	NOUN
ajst-19195	162	14	tumor	tumor	NOUN
ajst-19195	162	15	segmentation	segmentation	NOUN
ajst-19195	162	16	:	:	PUNCT
ajst-19195	162	17	a	a	DET
ajst-19195	162	18	survey	survey	NOUN
ajst-19195	162	19	of	of	ADP
ajst-19195	162	20	state	state	NOUN
ajst-19195	162	21	-	-	PUNCT
ajst-19195	162	22	of	of	ADP
ajst-19195	162	23	-	-	PUNCT
ajst-19195	162	24	the	the	DET
ajst-19195	162	25	-	-	PUNCT
ajst-19195	162	26	art	art	NOUN
ajst-19195	162	27	[	[	X
ajst-19195	162	28	j	j	X
ajst-19195	162	29	]	]	X
ajst-19195	162	30	.	.	PUNCT
ajst-19195	163	1	journal	journal	PROPN
ajst-19195	163	2	of	of	ADP
ajst-19195	163	3	imaging	imaging	NOUN
ajst-19195	163	4	,	,	PUNCT
ajst-19195	163	5	2021	2021	NUM
ajst-19195	163	6	,	,	PUNCT
ajst-19195	163	7	7(2).w.-k	7(2).w.-k	NUM
ajst-19195	163	8	.	.	PUNCT
ajst-19195	164	1	chen	chen	PROPN
ajst-19195	164	2	,	,	PUNCT
ajst-19195	164	3	linear	linear	ADJ
ajst-19195	164	4	networks	network	NOUN
ajst-19195	164	5	and	and	CCONJ
ajst-19195	164	6	systems	system	NOUN
ajst-19195	164	7	(	(	PUNCT
ajst-19195	164	8	book	book	NOUN
ajst-19195	164	9	style	style	NOUN
ajst-19195	164	10	)	)	PUNCT
ajst-19195	164	11	.	.	PUNCT
ajst-19195	165	1	belmont	belmont	PROPN
ajst-19195	165	2	,	,	PUNCT
ajst-19195	165	3	ca	can	AUX
ajst-19195	165	4	:	:	PUNCT
ajst-19195	165	5	wadsworth	wadsworth	NOUN
ajst-19195	165	6	,	,	PUNCT
ajst-19195	165	7	1993	1993	NUM
ajst-19195	165	8	,	,	PUNCT
ajst-19195	165	9	pp	pp	ADP
ajst-19195	165	10	.	.	PUNCT
ajst-19195	166	1	123–135	123–135	NUM
ajst-19195	166	2	.	.	PUNCT
ajst-19195	167	1	[	[	X
ajst-19195	167	2	2	2	NUM
ajst-19195	167	3	]	]	PUNCT
ajst-19195	167	4	mohan	mohan	PROPN
ajst-19195	167	5	g	g	PROPN
ajst-19195	167	6	,	,	PUNCT
ajst-19195	167	7	subashini	subashini	PROPN
ajst-19195	167	8	m	m	PROPN
ajst-19195	167	9	m.	m.	NOUN
ajst-19195	167	10	mri	mri	PROPN
ajst-19195	167	11	based	base	VERB
ajst-19195	167	12	medical	medical	ADJ
ajst-19195	167	13	image	image	NOUN
ajst-19195	167	14	analysis	analysis	NOUN
ajst-19195	167	15	:	:	PUNCT
ajst-19195	167	16	survey	survey	NOUN
ajst-19195	167	17	on	on	ADP
ajst-19195	167	18	brain	brain	NOUN
ajst-19195	167	19	tumor	tumor	NOUN
ajst-19195	167	20	grade	grade	NOUN
ajst-19195	167	21	classification	classification	NOUN
ajst-19195	167	22	[	[	X
ajst-19195	167	23	j	j	X
ajst-19195	167	24	]	]	X
ajst-19195	167	25	.	.	PUNCT
ajst-19195	168	1	biomedical	biomedical	ADJ
ajst-19195	168	2	signal	signal	NOUN
ajst-19195	168	3	processing	processing	NOUN
ajst-19195	168	4	and	and	CCONJ
ajst-19195	168	5	control	control	NOUN
ajst-19195	168	6	,	,	PUNCT
ajst-19195	168	7	2018	2018	NUM
ajst-19195	168	8	,	,	PUNCT
ajst-19195	168	9	39	39	NUM
ajst-19195	168	10	:	:	SYM
ajst-19195	168	11	139	139	NUM
ajst-19195	168	12	-	-	SYM
ajst-19195	168	13	61	61	NUM
ajst-19195	168	14	.	.	PUNCT
ajst-19195	168	15	254	254	NUM
ajst-19195	169	1	[	[	SYM
ajst-19195	169	2	3	3	NUM
ajst-19195	169	3	]	]	X
ajst-19195	169	4	tang	tang	PROPN
ajst-19195	169	5	j	j	PROPN
ajst-19195	169	6	,	,	PUNCT
ajst-19195	169	7	li	li	PROPN
ajst-19195	169	8	t	t	PROPN
ajst-19195	169	9	,	,	PUNCT
ajst-19195	169	10	shu	shu	PROPN
ajst-19195	169	11	h	h	PROPN
ajst-19195	169	12	,	,	PUNCT
ajst-19195	169	13	et	et	PROPN
ajst-19195	169	14	al	al	PROPN
ajst-19195	169	15	.	.	PUNCT
ajst-19195	170	1	variational	variational	ADJ
ajst-19195	170	2	-	-	PUNCT
ajst-19195	170	3	autoencoder	autoencoder	NOUN
ajst-19195	170	4	regularized	regularize	VERB
ajst-19195	170	5	3d	3d	NUM
ajst-19195	170	6	multiresunet	multiresunet	NOUN
ajst-19195	170	7	for	for	ADP
ajst-19195	170	8	the	the	DET
ajst-19195	170	9	brats	brat	NOUN
ajst-19195	170	10	2020	2020	NUM
ajst-19195	170	11	brain	brain	NOUN
ajst-19195	170	12	tumor	tumor	NOUN
ajst-19195	170	13	segmentation	segmentation	NOUN
ajst-19195	170	14	;	;	PUNCT
ajst-19195	170	15	proceedings	proceeding	NOUN
ajst-19195	170	16	of	of	ADP
ajst-19195	170	17	the	the	DET
ajst-19195	170	18	brainlesion	brainlesion	NOUN
ajst-19195	170	19	:	:	PUNCT
ajst-19195	170	20	glioma	glioma	NOUN
ajst-19195	170	21	,	,	PUNCT
ajst-19195	170	22	multiple	multiple	ADJ
ajst-19195	170	23	sclerosis	sclerosis	NOUN
ajst-19195	170	24	,	,	PUNCT
ajst-19195	170	25	stroke	stroke	NOUN
ajst-19195	170	26	and	and	CCONJ
ajst-19195	170	27	traumatic	traumatic	ADJ
ajst-19195	170	28	brain	brain	NOUN
ajst-19195	170	29	injuries	injury	NOUN
ajst-19195	170	30	,	,	PUNCT
ajst-19195	170	31	cham	cham	PROPN
ajst-19195	170	32	,	,	PUNCT
ajst-19195	170	33	f	f	PROPN
ajst-19195	170	34	2021//	2021//	PROPN
ajst-19195	170	35	,	,	PUNCT
ajst-19195	170	36	2021	2021	NUM
ajst-19195	171	1	[	[	X
ajst-19195	171	2	c	c	X
ajst-19195	171	3	]	]	PUNCT
ajst-19195	171	4	.	.	PUNCT
ajst-19195	172	1	springer	springer	PROPN
ajst-19195	172	2	international	international	ADJ
ajst-19195	172	3	publishing	publishing	NOUN
ajst-19195	172	4	.	.	PUNCT
ajst-19195	173	1	[	[	X
ajst-19195	173	2	4	4	X
ajst-19195	173	3	]	]	X
ajst-19195	173	4	colman	colman	PROPN
ajst-19195	173	5	j	j	PROPN
ajst-19195	173	6	,	,	PUNCT
ajst-19195	173	7	zhang	zhang	PROPN
ajst-19195	173	8	l	l	PROPN
ajst-19195	173	9	,	,	PUNCT
ajst-19195	173	10	duan	duan	PROPN
ajst-19195	173	11	w	w	PROPN
ajst-19195	173	12	,	,	PUNCT
ajst-19195	173	13	et	et	PROPN
ajst-19195	173	14	al	al	PROPN
ajst-19195	173	15	.	.	PUNCT
ajst-19195	173	16	dr	dr	PROPN
ajst-19195	173	17	-	-	PUNCT
ajst-19195	173	18	unet104	unet104	PROPN
ajst-19195	173	19	for	for	ADP
ajst-19195	173	20	multimodal	multimodal	NOUN
ajst-19195	173	21	mri	mri	NOUN
ajst-19195	173	22	brain	brain	NOUN
ajst-19195	173	23	tumor	tumor	NOUN
ajst-19195	173	24	segmentation	segmentation	NOUN
ajst-19195	173	25	;	;	PUNCT
ajst-19195	173	26	proceedings	proceeding	NOUN
ajst-19195	173	27	of	of	ADP
ajst-19195	173	28	the	the	DET
ajst-19195	173	29	brainlesion	brainlesion	NOUN
ajst-19195	173	30	:	:	PUNCT
ajst-19195	173	31	glioma	glioma	NOUN
ajst-19195	173	32	,	,	PUNCT
ajst-19195	173	33	multiple	multiple	ADJ
ajst-19195	173	34	sclerosis	sclerosis	NOUN
ajst-19195	173	35	,	,	PUNCT
ajst-19195	173	36	stroke	stroke	NOUN
ajst-19195	173	37	and	and	CCONJ
ajst-19195	173	38	traumatic	traumatic	ADJ
ajst-19195	173	39	brain	brain	NOUN
ajst-19195	173	40	injuries	injury	NOUN
ajst-19195	173	41	,	,	PUNCT
ajst-19195	173	42	cham	cham	PROPN
ajst-19195	173	43	,	,	PUNCT
ajst-19195	173	44	f	f	PROPN
ajst-19195	173	45	2021//	2021//	PROPN
ajst-19195	173	46	,	,	PUNCT
ajst-19195	173	47	2021	2021	NUM
ajst-19195	174	1	[	[	X
ajst-19195	174	2	c	c	X
ajst-19195	174	3	]	]	PUNCT
ajst-19195	174	4	.	.	PUNCT
ajst-19195	175	1	springer	springer	PROPN
ajst-19195	175	2	international	international	ADJ
ajst-19195	175	3	publishing	publishing	NOUN
ajst-19195	175	4	.	.	PUNCT
ajst-19195	176	1	[	[	X
ajst-19195	176	2	5	5	NUM
ajst-19195	176	3	]	]	PUNCT
ajst-19195	176	4	ribalta	ribalta	NOUN
ajst-19195	176	5	lorenzo	lorenzo	VERB
ajst-19195	176	6	p	p	NOUN
ajst-19195	176	7	,	,	PUNCT
ajst-19195	176	8	nalepa	nalepa	PROPN
ajst-19195	176	9	j	j	PROPN
ajst-19195	176	10	,	,	PUNCT
ajst-19195	176	11	bobek	bobek	ADJ
ajst-19195	176	12	-	-	PUNCT
ajst-19195	176	13	billewicz	billewicz	PROPN
ajst-19195	176	14	b	b	NOUN
ajst-19195	176	15	,	,	PUNCT
ajst-19195	176	16	et	et	PROPN
ajst-19195	176	17	al	al	PROPN
ajst-19195	176	18	.	.	PUNCT
ajst-19195	177	1	segmenting	segment	VERB
ajst-19195	177	2	brain	brain	NOUN
ajst-19195	177	3	tumors	tumor	NOUN
ajst-19195	177	4	from	from	ADP
ajst-19195	177	5	flair	flair	ADJ
ajst-19195	177	6	mri	mri	NOUN
ajst-19195	177	7	using	use	VERB
ajst-19195	177	8	fully	fully	ADV
ajst-19195	177	9	convolutional	convolutional	ADJ
ajst-19195	177	10	neural	neural	ADJ
ajst-19195	177	11	networks	network	NOUN
ajst-19195	178	1	[	[	X
ajst-19195	178	2	j	j	X
ajst-19195	178	3	]	]	X
ajst-19195	178	4	.	.	PUNCT
ajst-19195	179	1	computer	computer	NOUN
ajst-19195	179	2	methods	method	NOUN
ajst-19195	179	3	and	and	CCONJ
ajst-19195	179	4	programs	program	NOUN
ajst-19195	179	5	in	in	ADP
ajst-19195	179	6	biomedicine	biomedicine	NOUN
ajst-19195	179	7	,	,	PUNCT
ajst-19195	179	8	2019	2019	NUM
ajst-19195	179	9	,	,	PUNCT
ajst-19195	179	10	176	176	NUM
ajst-19195	179	11	:	:	PUNCT
ajst-19195	179	12	135	135	NUM
ajst-19195	179	13	-	-	SYM
ajst-19195	179	14	48	48	NUM
ajst-19195	179	15	.	.	PUNCT
ajst-19195	180	1	[	[	X
ajst-19195	180	2	6	6	NUM
ajst-19195	180	3	]	]	X
ajst-19195	180	4	gan	gan	PROPN
ajst-19195	180	5	x	x	NOUN
ajst-19195	180	6	,	,	PUNCT
ajst-19195	180	7	wang	wang	PROPN
ajst-19195	180	8	l	l	PROPN
ajst-19195	180	9	,	,	PUNCT
ajst-19195	180	10	chen	chen	PROPN
ajst-19195	180	11	q	q	AUX
ajst-19195	180	12	,	,	PUNCT
ajst-19195	180	13	et	et	PROPN
ajst-19195	180	14	al	al	PROPN
ajst-19195	180	15	.	.	PUNCT
ajst-19195	180	16	gau	gau	PROPN
ajst-19195	180	17	-	-	NOUN
ajst-19195	180	18	net	net	NOUN
ajst-19195	180	19	:	:	PUNCT
ajst-19195	180	20	u	u	NOUN
ajst-19195	180	21	-	-	NOUN
ajst-19195	180	22	net	net	NOUN
ajst-19195	180	23	based	base	VERB
ajst-19195	180	24	on	on	ADP
ajst-19195	180	25	global	global	ADJ
ajst-19195	180	26	attention	attention	NOUN
ajst-19195	180	27	mechanism	mechanism	NOUN
ajst-19195	180	28	for	for	ADP
ajst-19195	180	29	brain	brain	NOUN
ajst-19195	180	30	tumor	tumor	NOUN
ajst-19195	180	31	segmentation	segmentation	NOUN
ajst-19195	181	1	[	[	X
ajst-19195	181	2	j	j	X
ajst-19195	181	3	]	]	X
ajst-19195	181	4	.	.	PUNCT
ajst-19195	182	1	journal	journal	PROPN
ajst-19195	182	2	of	of	ADP
ajst-19195	182	3	physics	physics	PROPN
ajst-19195	182	4	:	:	PUNCT
ajst-19195	182	5	conference	conference	NOUN
ajst-19195	182	6	series	series	NOUN
ajst-19195	182	7	,	,	PUNCT
ajst-19195	182	8	2021	2021	NUM
ajst-19195	182	9	,	,	PUNCT
ajst-19195	182	10	1861(1	1861(1	NUM
ajst-19195	182	11	):	):	PUNCT
ajst-19195	182	12	012041	012041	NUM
ajst-19195	182	13	.	.	PUNCT
ajst-19195	183	1	[	[	X
ajst-19195	183	2	7	7	X
ajst-19195	183	3	]	]	X
ajst-19195	183	4	zhou	zhou	PROPN
ajst-19195	183	5	z	z	PROPN
ajst-19195	183	6	,	,	PUNCT
ajst-19195	183	7	rahman	rahman	PROPN
ajst-19195	183	8	siddiquee	siddiquee	PROPN
ajst-19195	183	9	m	m	VERB
ajst-19195	183	10	m	m	PROPN
ajst-19195	183	11	,	,	PUNCT
ajst-19195	183	12	tajbakhsh	tajbakhsh	PROPN
ajst-19195	183	13	n	n	CCONJ
ajst-19195	183	14	,	,	PUNCT
ajst-19195	183	15	et	et	PROPN
ajst-19195	183	16	al	al	PROPN
ajst-19195	183	17	.	.	PUNCT
ajst-19195	184	1	unet++	unet++	PROPN
ajst-19195	184	2	:	:	PUNCT
ajst-19195	184	3	a	a	DET
ajst-19195	184	4	nested	nested	ADJ
ajst-19195	184	5	u	u	ADJ
ajst-19195	184	6	-	-	ADJ
ajst-19195	184	7	net	net	ADJ
ajst-19195	184	8	architecture	architecture	NOUN
ajst-19195	184	9	for	for	ADP
ajst-19195	184	10	medical	medical	ADJ
ajst-19195	184	11	image	image	NOUN
ajst-19195	184	12	segmentation	segmentation	NOUN
ajst-19195	184	13	;	;	PUNCT
ajst-19195	184	14	proceedings	proceeding	NOUN
ajst-19195	184	15	of	of	ADP
ajst-19195	184	16	the	the	DET
ajst-19195	184	17	deep	deep	ADJ
ajst-19195	184	18	learning	learning	NOUN
ajst-19195	184	19	in	in	ADP
ajst-19195	184	20	medical	medical	ADJ
ajst-19195	184	21	image	image	NOUN
ajst-19195	184	22	analysis	analysis	NOUN
ajst-19195	184	23	and	and	CCONJ
ajst-19195	184	24	multimodal	multimodal	NOUN
ajst-19195	184	25	learning	learning	NOUN
ajst-19195	184	26	for	for	ADP
ajst-19195	184	27	clinical	clinical	ADJ
ajst-19195	184	28	decision	decision	NOUN
ajst-19195	184	29	support	support	NOUN
ajst-19195	184	30	,	,	PUNCT
ajst-19195	184	31	cham	cham	PROPN
ajst-19195	184	32	,	,	PUNCT
ajst-19195	184	33	f	f	PROPN
ajst-19195	184	34	2018//	2018//	PROPN
ajst-19195	184	35	,	,	PUNCT
ajst-19195	184	36	2018	2018	NUM
ajst-19195	185	1	[	[	X
ajst-19195	185	2	c	c	X
ajst-19195	185	3	]	]	PUNCT
ajst-19195	185	4	.	.	PUNCT
ajst-19195	186	1	springer	springer	PROPN
ajst-19195	186	2	international	international	ADJ
ajst-19195	186	3	publishing	publishing	NOUN
ajst-19195	186	4	.	.	PUNCT
ajst-19195	187	1	[	[	X
ajst-19195	187	2	8	8	NUM
ajst-19195	187	3	]	]	X
ajst-19195	187	4	chen	chen	PROPN
ajst-19195	187	5	l	l	PROPN
ajst-19195	187	6	-	-	PROPN
ajst-19195	187	7	c	c	PROPN
ajst-19195	187	8	,	,	PUNCT
ajst-19195	187	9	zhu	zhu	PROPN
ajst-19195	187	10	y	y	PROPN
ajst-19195	187	11	,	,	PUNCT
ajst-19195	187	12	papandreou	papandreou	PROPN
ajst-19195	187	13	g	g	NOUN
ajst-19195	187	14	,	,	PUNCT
ajst-19195	187	15	et	et	PROPN
ajst-19195	187	16	al	al	PROPN
ajst-19195	187	17	.	.	PROPN
ajst-19195	187	18	encoderdecoder	encoderdecoder	PROPN
ajst-19195	187	19	with	with	ADP
ajst-19195	187	20	atrous	atrous	ADJ
ajst-19195	187	21	separable	separable	ADJ
ajst-19195	187	22	convolution	convolution	NOUN
ajst-19195	187	23	for	for	ADP
ajst-19195	187	24	semantic	semantic	ADJ
ajst-19195	187	25	image	image	NOUN
ajst-19195	187	26	segmentation	segmentation	NOUN
ajst-19195	187	27	;	;	PUNCT
ajst-19195	187	28	proceedings	proceeding	NOUN
ajst-19195	187	29	of	of	ADP
ajst-19195	187	30	the	the	DET
ajst-19195	187	31	computer	computer	NOUN
ajst-19195	187	32	vision	vision	NOUN
ajst-19195	187	33	–	–	PUNCT
ajst-19195	187	34	eccv	eccv	ADV
ajst-19195	187	35	2018	2018	NUM
ajst-19195	187	36	,	,	PUNCT
ajst-19195	187	37	cham	cham	PROPN
ajst-19195	187	38	,	,	PUNCT
ajst-19195	187	39	f	f	PROPN
ajst-19195	187	40	2018//	2018//	PROPN
ajst-19195	187	41	,	,	PUNCT
ajst-19195	187	42	2018	2018	NUM
ajst-19195	188	1	[	[	X
ajst-19195	188	2	c	c	X
ajst-19195	188	3	]	]	PUNCT
ajst-19195	188	4	.	.	PUNCT
ajst-19195	189	1	springer	springer	PROPN
ajst-19195	189	2	international	international	ADJ
ajst-19195	189	3	publishing	publishing	NOUN
ajst-19195	189	4	.	.	PUNCT
ajst-19195	190	1	[	[	X
ajst-19195	190	2	9	9	X
ajst-19195	190	3	]	]	PUNCT
ajst-19195	190	4	hoorali	hoorali	PROPN
ajst-19195	190	5	f	f	PROPN
ajst-19195	190	6	,	,	PUNCT
ajst-19195	190	7	khosravi	khosravi	VERB
ajst-19195	190	8	h	h	NOUN
ajst-19195	190	9	,	,	PUNCT
ajst-19195	190	10	moradi	moradi	PROPN
ajst-19195	190	11	b.	b.	PROPN
ajst-19195	190	12	automatic	automatic	ADJ
ajst-19195	190	13	microscopic	microscopic	ADJ
ajst-19195	190	14	diagnosis	diagnosis	NOUN
ajst-19195	190	15	of	of	ADP
ajst-19195	190	16	diseases	disease	NOUN
ajst-19195	190	17	using	use	VERB
ajst-19195	190	18	an	an	DET
ajst-19195	190	19	improved	improved	ADJ
ajst-19195	190	20	unet++	unet++	ADJ
ajst-19195	190	21	architecture	architecture	NOUN
ajst-19195	190	22	[	[	X
ajst-19195	190	23	j	j	X
ajst-19195	190	24	]	]	X
ajst-19195	190	25	.	.	PUNCT
ajst-19195	191	1	tissue	tissue	NOUN
ajst-19195	191	2	&	&	CCONJ
ajst-19195	191	3	cell	cell	NOUN
ajst-19195	191	4	,	,	PUNCT
ajst-19195	191	5	2022	2022	NUM
ajst-19195	191	6	,	,	PUNCT
ajst-19195	191	7	76	76	NUM
ajst-19195	191	8	:	:	SYM
ajst-19195	191	9	101816	101816	NUM
ajst-19195	191	10	.	.	PUNCT
ajst-19195	192	1	[	[	X
ajst-19195	192	2	10	10	NUM
ajst-19195	192	3	]	]	X
ajst-19195	192	4	zhao	zhao	PROPN
ajst-19195	192	5	z	z	PROPN
ajst-19195	192	6	,	,	PUNCT
ajst-19195	192	7	chen	chen	PROPN
ajst-19195	192	8	k	k	PROPN
ajst-19195	192	9	,	,	PUNCT
ajst-19195	192	10	yamane	yamane	PROPN
ajst-19195	192	11	s.	s.	PROPN
ajst-19195	192	12	cbam	cbam	PROPN
ajst-19195	192	13	-	-	PUNCT
ajst-19195	192	14	unet++:easier	unet++:easier	PROPN
ajst-19195	192	15	to	to	PART
ajst-19195	192	16	find	find	VERB
ajst-19195	192	17	the	the	DET
ajst-19195	192	18	target	target	NOUN
ajst-19195	192	19	with	with	ADP
ajst-19195	192	20	the	the	DET
ajst-19195	192	21	attention	attention	NOUN
ajst-19195	192	22	module	module	NOUN
ajst-19195	192	23	"	"	PUNCT
ajst-19195	192	24	cbam	cbam	NOUN
ajst-19195	192	25	"	"	PUNCT
ajst-19195	192	26	;	;	PUNCT
ajst-19195	192	27	proceedings	proceeding	NOUN
ajst-19195	192	28	of	of	ADP
ajst-19195	192	29	the	the	DET
ajst-19195	192	30	2021	2021	NUM
ajst-19195	192	31	ieee	ieee	NOUN
ajst-19195	192	32	10th	10th	ADJ
ajst-19195	192	33	global	global	ADJ
ajst-19195	192	34	conference	conference	NOUN
ajst-19195	192	35	on	on	ADP
ajst-19195	192	36	consumer	consumer	NOUN
ajst-19195	192	37	electronics	electronic	NOUN
ajst-19195	192	38	(	(	PUNCT
ajst-19195	192	39	gcce	gcce	NOUN
ajst-19195	192	40	)	)	PUNCT
ajst-19195	192	41	,	,	PUNCT
ajst-19195	192	42	f	f	PROPN
ajst-19195	192	43	12	12	NUM
ajst-19195	192	44	-	-	SYM
ajst-19195	192	45	15	15	NUM
ajst-19195	192	46	oct	oct	PROPN
ajst-19195	192	47	.	.	PROPN
ajst-19195	192	48	2021	2021	NUM
ajst-19195	192	49	,	,	PUNCT
ajst-19195	192	50	2021	2021	NUM
ajst-19195	192	51	[	[	X
ajst-19195	192	52	c	c	X
ajst-19195	192	53	]	]	PUNCT
ajst-19195	192	54	.	.	PUNCT
ajst-19195	193	1	[	[	X
ajst-19195	193	2	11	11	NUM
ajst-19195	193	3	]	]	PUNCT
ajst-19195	193	4	he	he	PRON
ajst-19195	193	5	k	k	PROPN
ajst-19195	193	6	,	,	PUNCT
ajst-19195	193	7	zhang	zhang	PROPN
ajst-19195	193	8	x	x	PROPN
ajst-19195	193	9	,	,	PUNCT
ajst-19195	193	10	ren	ren	PROPN
ajst-19195	193	11	s	s	PROPN
ajst-19195	193	12	,	,	PUNCT
ajst-19195	193	13	et	et	PROPN
ajst-19195	193	14	al	al	PROPN
ajst-19195	193	15	.	.	PUNCT
ajst-19195	194	1	deep	deep	ADJ
ajst-19195	194	2	residual	residual	ADJ
ajst-19195	194	3	learning	learning	NOUN
ajst-19195	194	4	for	for	ADP
ajst-19195	194	5	image	image	NOUN
ajst-19195	194	6	recognition	recognition	NOUN
ajst-19195	195	1	[	[	X
ajst-19195	195	2	j	j	X
ajst-19195	195	3	]	]	X
ajst-19195	195	4	.	.	PUNCT
ajst-19195	195	5	2016	2016	NUM
ajst-19195	195	6	ieee	ieee	NOUN
ajst-19195	195	7	conference	conference	NOUN
ajst-19195	195	8	on	on	ADP
ajst-19195	195	9	computer	computer	NOUN
ajst-19195	195	10	vision	vision	NOUN
ajst-19195	195	11	and	and	CCONJ
ajst-19195	195	12	pattern	pattern	NOUN
ajst-19195	195	13	recognition	recognition	NOUN
ajst-19195	195	14	(	(	PUNCT
ajst-19195	195	15	cvpr	cvpr	NOUN
ajst-19195	195	16	)	)	PUNCT
ajst-19195	195	17	,	,	PUNCT
ajst-19195	195	18	2016	2016	NUM
ajst-19195	195	19	:	:	PUNCT
ajst-19195	195	20	770	770	NUM
ajst-19195	195	21	-	-	SYM
ajst-19195	195	22	8	8	NUM
ajst-19195	195	23	.	.	PUNCT
ajst-19195	196	1	[	[	X
ajst-19195	196	2	12	12	NUM
ajst-19195	196	3	]	]	X
ajst-19195	196	4	wang	wang	PROPN
ajst-19195	196	5	j	j	PROPN
ajst-19195	196	6	,	,	PUNCT
ajst-19195	196	7	gao	gao	PROPN
ajst-19195	196	8	j	j	PROPN
ajst-19195	196	9	,	,	PUNCT
ajst-19195	196	10	ren	ren	PROPN
ajst-19195	196	11	j	j	PROPN
ajst-19195	196	12	,	,	PUNCT
ajst-19195	196	13	et	et	PROPN
ajst-19195	196	14	al	al	PROPN
ajst-19195	196	15	.	.	PUNCT
ajst-19195	197	1	dfp	dfp	PROPN
ajst-19195	197	2	-	-	PUNCT
ajst-19195	197	3	resunet	resunet	ADJ
ajst-19195	197	4	:	:	PUNCT
ajst-19195	197	5	convolutional	convolutional	ADJ
ajst-19195	197	6	neural	neural	ADJ
ajst-19195	197	7	network	network	NOUN
ajst-19195	197	8	with	with	ADP
ajst-19195	197	9	a	a	DET
ajst-19195	197	10	dilated	dilate	VERB
ajst-19195	197	11	convolutional	convolutional	ADJ
ajst-19195	197	12	feature	feature	NOUN
ajst-19195	197	13	pyramid	pyramid	NOUN
ajst-19195	197	14	for	for	ADP
ajst-19195	197	15	multimodal	multimodal	ADJ
ajst-19195	197	16	brain	brain	NOUN
ajst-19195	197	17	tumor	tumor	NOUN
ajst-19195	197	18	segmentation	segmentation	NOUN
ajst-19195	198	1	[	[	X
ajst-19195	198	2	j	j	X
ajst-19195	198	3	]	]	X
ajst-19195	198	4	.	.	PUNCT
ajst-19195	199	1	computer	computer	NOUN
ajst-19195	199	2	methods	method	NOUN
ajst-19195	199	3	and	and	CCONJ
ajst-19195	199	4	programs	program	NOUN
ajst-19195	199	5	in	in	ADP
ajst-19195	199	6	biomedicine	biomedicine	NOUN
ajst-19195	199	7	,	,	PUNCT
ajst-19195	199	8	2021	2021	NUM
ajst-19195	199	9	,	,	PUNCT
ajst-19195	199	10	208	208	NUM
ajst-19195	199	11	:	:	PUNCT
ajst-19195	199	12	106208	106208	NUM
ajst-19195	199	13	.	.	PUNCT
ajst-19195	200	1	[	[	X
ajst-19195	200	2	13	13	NUM
ajst-19195	200	3	]	]	X
ajst-19195	200	4	woo	woo	NOUN
ajst-19195	200	5	s	s	PROPN
ajst-19195	200	6	,	,	PUNCT
ajst-19195	200	7	park	park	PROPN
ajst-19195	200	8	j	j	PROPN
ajst-19195	200	9	,	,	PUNCT
ajst-19195	200	10	lee	lee	PROPN
ajst-19195	200	11	j	j	PROPN
ajst-19195	200	12	-	-	PROPN
ajst-19195	200	13	y	y	PROPN
ajst-19195	200	14	,	,	PUNCT
ajst-19195	200	15	et	et	PROPN
ajst-19195	200	16	al	al	PROPN
ajst-19195	200	17	.	.	PUNCT
ajst-19195	200	18	cbam	cbam	NOUN
ajst-19195	200	19	:	:	PUNCT
ajst-19195	200	20	convolutional	convolutional	ADJ
ajst-19195	200	21	block	block	NOUN
ajst-19195	200	22	attention	attention	NOUN
ajst-19195	200	23	module	module	NOUN
ajst-19195	200	24	;	;	PUNCT
ajst-19195	200	25	proceedings	proceeding	NOUN
ajst-19195	200	26	of	of	ADP
ajst-19195	200	27	the	the	DET
ajst-19195	200	28	2018	2018	NUM
ajst-19195	200	29	european	european	ADJ
ajst-19195	200	30	conference	conference	NOUN
ajst-19195	200	31	on	on	ADP
ajst-19195	200	32	computer	computer	NOUN
ajst-19195	200	33	vision	vision	NOUN
ajst-19195	200	34	(	(	PUNCT
ajst-19195	200	35	eccv	eccv	ADV
ajst-19195	200	36	)	)	PUNCT
ajst-19195	200	37	cham	cham	PROPN
ajst-19195	200	38	,	,	PUNCT
ajst-19195	200	39	f	f	PROPN
ajst-19195	200	40	2018//	2018//	PROPN
ajst-19195	200	41	,	,	PUNCT
ajst-19195	200	42	2018	2018	NUM
ajst-19195	200	43	[	[	X
ajst-19195	200	44	c	c	X
ajst-19195	200	45	]	]	PUNCT
ajst-19195	200	46	.	.	PUNCT
ajst-19195	201	1	springer	springer	PROPN
ajst-19195	201	2	international	international	ADJ
ajst-19195	201	3	publishing	publishing	NOUN
ajst-19195	201	4	.	.	PUNCT
ajst-19195	202	1	[	[	X
ajst-19195	202	2	14	14	NUM
ajst-19195	202	3	]	]	X
ajst-19195	202	4	guan	guan	PROPN
ajst-19195	202	5	x	x	PROPN
ajst-19195	202	6	,	,	PUNCT
ajst-19195	202	7	yang	yang	PROPN
ajst-19195	202	8	g	g	PROPN
ajst-19195	202	9	,	,	PUNCT
ajst-19195	202	10	ye	ye	PROPN
ajst-19195	202	11	j	j	PROPN
ajst-19195	202	12	,	,	PUNCT
ajst-19195	202	13	et	et	PROPN
ajst-19195	202	14	al	al	PROPN
ajst-19195	202	15	.	.	PROPN
ajst-19195	202	16	3d	3d	PROPN
ajst-19195	202	17	agse	agse	PROPN
ajst-19195	202	18	-	-	PUNCT
ajst-19195	202	19	vnet	vnet	NOUN
ajst-19195	202	20	:	:	PUNCT
ajst-19195	202	21	an	an	DET
ajst-19195	202	22	automatic	automatic	ADJ
ajst-19195	202	23	brain	brain	NOUN
ajst-19195	202	24	tumor	tumor	NOUN
ajst-19195	202	25	mri	mri	NOUN
ajst-19195	202	26	data	datum	NOUN
ajst-19195	202	27	segmentation	segmentation	NOUN
ajst-19195	202	28	framework	framework	NOUN
ajst-19195	203	1	[	[	X
ajst-19195	203	2	j	j	X
ajst-19195	203	3	]	]	X
ajst-19195	203	4	.	.	PUNCT
ajst-19195	204	1	bmc	bmc	PROPN
ajst-19195	204	2	medical	medical	ADJ
ajst-19195	204	3	imaging	imaging	NOUN
ajst-19195	204	4	,	,	PUNCT
ajst-19195	204	5	2022	2022	NUM
ajst-19195	204	6	,	,	PUNCT
ajst-19195	204	7	22(1	22(1	NUM
ajst-19195	204	8	):	):	PUNCT
ajst-19195	204	9	6	6	NUM
ajst-19195	204	10	.	.	PUNCT
ajst-19195	205	1	[	[	X
ajst-19195	205	2	15	15	NUM
ajst-19195	205	3	]	]	X
ajst-19195	205	4	chen	chen	PROPN
ajst-19195	205	5	l	l	PROPN
ajst-19195	205	6	c	c	PROPN
ajst-19195	205	7	,	,	PUNCT
ajst-19195	205	8	papandreou	papandreou	ADV
ajst-19195	205	9	g	g	NOUN
ajst-19195	205	10	,	,	PUNCT
ajst-19195	205	11	kokkinos	kokkinos	PROPN
ajst-19195	205	12	i	i	PRON
ajst-19195	205	13	,	,	PUNCT
ajst-19195	205	14	et	et	PROPN
ajst-19195	205	15	al	al	PROPN
ajst-19195	205	16	.	.	PUNCT
ajst-19195	206	1	deeplab	deeplab	PROPN
ajst-19195	206	2	:	:	PUNCT
ajst-19195	206	3	semantic	semantic	ADJ
ajst-19195	206	4	image	image	NOUN
ajst-19195	206	5	segmentation	segmentation	NOUN
ajst-19195	206	6	with	with	ADP
ajst-19195	206	7	deep	deep	ADJ
ajst-19195	206	8	convolutional	convolutional	ADJ
ajst-19195	206	9	nets	net	NOUN
ajst-19195	206	10	,	,	PUNCT
ajst-19195	206	11	atrous	atrous	ADJ
ajst-19195	206	12	convolution	convolution	NOUN
ajst-19195	206	13	,	,	PUNCT
ajst-19195	206	14	and	and	CCONJ
ajst-19195	206	15	fully	fully	ADV
ajst-19195	206	16	connected	connect	VERB
ajst-19195	206	17	crfs	crf	NOUN
ajst-19195	207	1	[	[	X
ajst-19195	207	2	j	j	X
ajst-19195	207	3	]	]	X
ajst-19195	207	4	.	.	PUNCT
ajst-19195	208	1	ieee	ieee	NOUN
ajst-19195	208	2	transactions	transaction	NOUN
ajst-19195	208	3	on	on	ADP
ajst-19195	208	4	pattern	pattern	NOUN
ajst-19195	208	5	analysis	analysis	NOUN
ajst-19195	208	6	and	and	CCONJ
ajst-19195	208	7	machine	machine	NOUN
ajst-19195	208	8	intelligence	intelligence	NOUN
ajst-19195	208	9	,	,	PUNCT
ajst-19195	208	10	2018	2018	NUM
ajst-19195	208	11	,	,	PUNCT
ajst-19195	208	12	40(4	40(4	NUM
ajst-19195	208	13	):	):	PUNCT
ajst-19195	208	14	834	834	NUM
ajst-19195	208	15	-	-	SYM
ajst-19195	208	16	48	48	NUM
ajst-19195	208	17	.	.	PUNCT
ajst-19195	209	1	[	[	X
ajst-19195	209	2	16	16	NUM
ajst-19195	209	3	]	]	PUNCT
ajst-19195	209	4	jha	jha	PROPN
ajst-19195	209	5	d	d	PROPN
ajst-19195	209	6	,	,	PUNCT
ajst-19195	209	7	smedsrud	smedsrud	NOUN
ajst-19195	209	8	p	p	PROPN
ajst-19195	209	9	h	h	NOUN
ajst-19195	209	10	,	,	PUNCT
ajst-19195	209	11	riegler	riegler	NOUN
ajst-19195	209	12	m	m	PROPN
ajst-19195	209	13	a	a	PROPN
ajst-19195	209	14	,	,	PUNCT
ajst-19195	209	15	et	et	PROPN
ajst-19195	209	16	al	al	PROPN
ajst-19195	209	17	.	.	PUNCT
ajst-19195	209	18	resunet++	resunet++	PROPN
ajst-19195	209	19	:	:	PUNCT
ajst-19195	209	20	an	an	DET
ajst-19195	209	21	advanced	advanced	ADJ
ajst-19195	209	22	architecture	architecture	NOUN
ajst-19195	209	23	for	for	ADP
ajst-19195	209	24	medical	medical	ADJ
ajst-19195	209	25	image	image	NOUN
ajst-19195	209	26	segmentation	segmentation	NOUN
ajst-19195	210	1	[	[	X
ajst-19195	210	2	j	j	X
ajst-19195	210	3	]	]	X
ajst-19195	210	4	.	.	PUNCT
ajst-19195	211	1	ieee	ieee	PROPN
ajst-19195	211	2	international	international	ADJ
ajst-19195	211	3	symposium	symposium	NOUN
ajst-19195	211	4	on	on	ADP
ajst-19195	211	5	multimedia	multimedia	NOUN
ajst-19195	211	6	(	(	PUNCT
ajst-19195	211	7	ism	ism	NOUN
ajst-19195	211	8	)	)	PUNCT
ajst-19195	211	9	,	,	PUNCT
ajst-19195	211	10	2019	2019	NUM
ajst-19195	211	11	:	:	PUNCT
ajst-19195	211	12	225	225	NUM
ajst-19195	211	13	-	-	SYM
ajst-19195	211	14	2255	2255	NUM
ajst-19195	211	15	.	.	PUNCT
ajst-19195	212	1	[	[	X
ajst-19195	212	2	17	17	NUM
ajst-19195	212	3	]	]	X
ajst-19195	212	4	zhao	zhao	PROPN
ajst-19195	212	5	y	y	PROPN
ajst-19195	212	6	,	,	PUNCT
ajst-19195	212	7	liu	liu	PROPN
ajst-19195	212	8	y	y	PROPN
ajst-19195	212	9	,	,	PUNCT
ajst-19195	212	10	huang	huang	PROPN
ajst-19195	212	11	z	z	PROPN
ajst-19195	212	12	,	,	PUNCT
ajst-19195	212	13	et	et	PROPN
ajst-19195	212	14	al	al	PROPN
ajst-19195	212	15	.	.	PROPN
ajst-19195	212	16	gcaunet	gcaunet	PROPN
ajst-19195	212	17	:	:	PUNCT
ajst-19195	212	18	a	a	DET
ajst-19195	212	19	group	group	NOUN
ajst-19195	212	20	crosschannel	crosschannel	NOUN
ajst-19195	212	21	attention	attention	NOUN
ajst-19195	212	22	residual	residual	ADJ
ajst-19195	212	23	unet	unet	NOUN
ajst-19195	212	24	for	for	ADP
ajst-19195	212	25	slice	slice	NOUN
ajst-19195	212	26	based	base	VERB
ajst-19195	212	27	brain	brain	NOUN
ajst-19195	212	28	tumor	tumor	NOUN
ajst-19195	212	29	segmentation	segmentation	NOUN
ajst-19195	213	1	[	[	X
ajst-19195	213	2	j	j	X
ajst-19195	213	3	]	]	X
ajst-19195	213	4	.	.	PUNCT
ajst-19195	214	1	biomedical	biomedical	ADJ
ajst-19195	214	2	signal	signal	NOUN
ajst-19195	214	3	processing	processing	NOUN
ajst-19195	214	4	and	and	CCONJ
ajst-19195	214	5	control	control	NOUN
ajst-19195	214	6	,	,	PUNCT
ajst-19195	214	7	2021	2021	NUM
ajst-19195	214	8	,	,	PUNCT
ajst-19195	214	9	70	70	NUM
ajst-19195	214	10	:	:	SYM
ajst-19195	214	11	102958	102958	NUM
ajst-19195	214	12	.	.	PUNCT
ajst-19195	215	1	[	[	X
ajst-19195	215	2	18	18	NUM
ajst-19195	215	3	]	]	X
ajst-19195	215	4	menze	menze	PROPN
ajst-19195	215	5	b	b	PROPN
ajst-19195	215	6	h	h	PROPN
ajst-19195	215	7	,	,	PUNCT
ajst-19195	215	8	jakab	jakab	PROPN
ajst-19195	215	9	a	a	PROPN
ajst-19195	215	10	,	,	PUNCT
ajst-19195	215	11	bauer	bauer	PROPN
ajst-19195	215	12	s	s	PROPN
ajst-19195	215	13	,	,	PUNCT
ajst-19195	215	14	et	et	PROPN
ajst-19195	215	15	al	al	PROPN
ajst-19195	215	16	.	.	PUNCT
ajst-19195	216	1	the	the	DET
ajst-19195	216	2	multimodal	multimodal	ADJ
ajst-19195	216	3	brain	brain	NOUN
ajst-19195	216	4	tumor	tumor	NOUN
ajst-19195	216	5	image	image	NOUN
ajst-19195	216	6	segmentation	segmentation	NOUN
ajst-19195	216	7	benchmark	benchmark	NOUN
ajst-19195	216	8	(	(	PUNCT
ajst-19195	216	9	brats	brat	NOUN
ajst-19195	216	10	)	)	PUNCT
ajst-19195	217	1	[	[	X
ajst-19195	217	2	j	j	X
ajst-19195	217	3	]	]	X
ajst-19195	217	4	.	.	PUNCT
ajst-19195	218	1	ieee	ieee	NOUN
ajst-19195	218	2	transactions	transaction	NOUN
ajst-19195	218	3	on	on	ADP
ajst-19195	218	4	medical	medical	ADJ
ajst-19195	218	5	imaging	imaging	NOUN
ajst-19195	218	6	,	,	PUNCT
ajst-19195	218	7	2015	2015	NUM
ajst-19195	218	8	,	,	PUNCT
ajst-19195	218	9	34(10	34(10	NUM
ajst-19195	218	10	):	):	PUNCT
ajst-19195	218	11	19932024	19932024	NUM
ajst-19195	218	12	.	.	PUNCT
ajst-19195	219	1	[	[	X
ajst-19195	219	2	19	19	NUM
ajst-19195	219	3	]	]	X
ajst-19195	219	4	bakas	bakas	PROPN
ajst-19195	219	5	s	s	PROPN
ajst-19195	219	6	,	,	PUNCT
ajst-19195	219	7	akbari	akbari	PROPN
ajst-19195	219	8	h	h	PROPN
ajst-19195	219	9	,	,	PUNCT
ajst-19195	219	10	sotiras	sotira	VERB
ajst-19195	219	11	a	a	PRON
ajst-19195	219	12	,	,	PUNCT
ajst-19195	219	13	et	et	PROPN
ajst-19195	219	14	al	al	PROPN
ajst-19195	219	15	.	.	PUNCT
ajst-19195	220	1	advancing	advance	VERB
ajst-19195	220	2	the	the	DET
ajst-19195	220	3	cancer	cancer	NOUN
ajst-19195	220	4	genome	genome	NOUN
ajst-19195	220	5	atlas	atlas	PROPN
ajst-19195	220	6	glioma	glioma	NOUN
ajst-19195	220	7	mri	mri	NOUN
ajst-19195	220	8	collections	collection	NOUN
ajst-19195	220	9	with	with	ADP
ajst-19195	220	10	expert	expert	NOUN
ajst-19195	220	11	segmentation	segmentation	NOUN
ajst-19195	220	12	labels	label	NOUN
ajst-19195	220	13	and	and	CCONJ
ajst-19195	220	14	radiomic	radiomic	ADJ
ajst-19195	220	15	features	feature	VERB
ajst-19195	221	1	[	[	X
ajst-19195	221	2	j	j	X
ajst-19195	221	3	]	]	X
ajst-19195	221	4	.	.	PUNCT
ajst-19195	222	1	scientific	scientific	ADJ
ajst-19195	222	2	data	datum	NOUN
ajst-19195	222	3	,	,	PUNCT
ajst-19195	222	4	2017	2017	NUM
ajst-19195	222	5	,	,	PUNCT
ajst-19195	222	6	4(1	4(1	NOUN
ajst-19195	222	7	):	):	PUNCT
ajst-19195	222	8	170117	170117	NUM
ajst-19195	222	9	.	.	PUNCT
ajst-19195	223	1	[	[	X
ajst-19195	223	2	20	20	NUM
ajst-19195	223	3	]	]	PUNCT
ajst-19195	223	4	kingma	kingma	PROPN
ajst-19195	223	5	d	d	PROPN
ajst-19195	223	6	,	,	PUNCT
ajst-19195	223	7	ba	ba	PROPN
ajst-19195	223	8	j	j	PROPN
ajst-19195	223	9	j	j	PROPN
ajst-19195	223	10	c	c	PROPN
ajst-19195	223	11	s.	s.	PROPN
ajst-19195	223	12	adam	adam	PROPN
ajst-19195	223	13	:	:	PUNCT
ajst-19195	223	14	a	a	DET
ajst-19195	223	15	method	method	NOUN
ajst-19195	223	16	for	for	ADP
ajst-19195	223	17	stochastic	stochastic	ADJ
ajst-19195	223	18	optimization	optimization	NOUN
ajst-19195	224	1	[	[	X
ajst-19195	224	2	j	j	X
ajst-19195	224	3	]	]	X
ajst-19195	224	4	.	.	PUNCT
ajst-19195	225	1	international	international	ADJ
ajst-19195	225	2	conference	conference	NOUN
ajst-19195	225	3	on	on	ADP
ajst-19195	225	4	learning	learn	VERB
ajst-19195	225	5	representations	representation	NOUN
ajst-19195	225	6	,	,	PUNCT
ajst-19195	225	7	2014	2014	NUM
ajst-19195	225	8	.	.	PUNCT
ajst-19195	226	1	[	[	X
ajst-19195	226	2	21	21	NUM
ajst-19195	226	3	]	]	PUNCT
ajst-19195	226	4	sudre	sudre	PROPN
ajst-19195	226	5	c	c	PROPN
ajst-19195	226	6	h	h	PROPN
ajst-19195	226	7	,	,	PUNCT
ajst-19195	226	8	li	li	PROPN
ajst-19195	226	9	w	w	PROPN
ajst-19195	226	10	,	,	PUNCT
ajst-19195	226	11	vercauteren	vercauteren	PROPN
ajst-19195	226	12	t	t	PROPN
ajst-19195	226	13	,	,	PUNCT
ajst-19195	226	14	et	et	PROPN
ajst-19195	227	1	al	al	PROPN
ajst-19195	227	2	.	.	PROPN
ajst-19195	227	3	generalised	generalise	VERB
ajst-19195	227	4	dice	dice	NOUN
ajst-19195	227	5	overlap	overlap	NOUN
ajst-19195	227	6	as	as	ADP
ajst-19195	227	7	a	a	DET
ajst-19195	227	8	deep	deep	ADJ
ajst-19195	227	9	learning	learning	NOUN
ajst-19195	227	10	loss	loss	NOUN
ajst-19195	227	11	function	function	NOUN
ajst-19195	227	12	for	for	ADP
ajst-19195	227	13	highly	highly	ADV
ajst-19195	227	14	unbalanced	unbalanced	ADJ
ajst-19195	227	15	segmentations	segmentation	NOUN
ajst-19195	227	16	;	;	PUNCT
ajst-19195	227	17	proceedings	proceeding	NOUN
ajst-19195	227	18	of	of	ADP
ajst-19195	227	19	the	the	DET
ajst-19195	227	20	deep	deep	ADJ
ajst-19195	227	21	learning	learning	NOUN
ajst-19195	227	22	in	in	ADP
ajst-19195	227	23	medical	medical	ADJ
ajst-19195	227	24	image	image	NOUN
ajst-19195	227	25	analysis	analysis	NOUN
ajst-19195	227	26	and	and	CCONJ
ajst-19195	227	27	multimodal	multimodal	NOUN
ajst-19195	227	28	learning	learning	NOUN
ajst-19195	227	29	for	for	ADP
ajst-19195	227	30	clinical	clinical	ADJ
ajst-19195	227	31	decision	decision	NOUN
ajst-19195	227	32	support	support	NOUN
ajst-19195	227	33	,	,	PUNCT
ajst-19195	227	34	cham	cham	PROPN
ajst-19195	227	35	,	,	PUNCT
ajst-19195	227	36	f	f	PROPN
ajst-19195	227	37	2017//	2017//	PROPN
ajst-19195	227	38	,	,	PUNCT
ajst-19195	227	39	2017	2017	NUM
ajst-19195	228	1	[	[	X
ajst-19195	228	2	c	c	X
ajst-19195	228	3	]	]	PUNCT
ajst-19195	228	4	.	.	PUNCT
ajst-19195	229	1	springer	springer	PROPN
ajst-19195	229	2	international	international	ADJ
ajst-19195	229	3	publishing	publishing	NOUN
ajst-19195	229	4	.	.	PUNCT