id	sid	tid	token	lemma	pos
cana-5503	1	1	communications	communication	NOUN
cana-5503	1	2	on	on	ADP
cana-5503	1	3	applied	apply	VERB
cana-5503	1	4	nonlinear	nonlinear	ADJ
cana-5503	1	5	analysis	analysis	NOUN
cana-5503	1	6	issn	issn	NOUN
cana-5503	1	7	:	:	PUNCT
cana-5503	1	8	1074	1074	NUM
cana-5503	1	9	-	-	PUNCT
cana-5503	1	10	133x	133x	NUM
cana-5503	1	11	vol	vol	VERB
cana-5503	1	12	32	32	NUM
cana-5503	1	13	no	no	NOUN
cana-5503	1	14	.	.	PUNCT
cana-5503	2	1	10s	10	NOUN
cana-5503	2	2	(	(	PUNCT
cana-5503	2	3	2025	2025	NUM
cana-5503	2	4	)	)	PUNCT
cana-5503	2	5	2531	2531	NUM
cana-5503	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5503	2	7	a	a	DET
cana-5503	2	8	robust	robust	ADJ
cana-5503	2	9	deep	deep	ADJ
cana-5503	2	10	net	net	ADJ
cana-5503	2	11	method	method	NOUN
cana-5503	2	12	for	for	ADP
cana-5503	2	13	retinal	retinal	ADJ
cana-5503	2	14	image	image	NOUN
cana-5503	2	15	segmentation	segmentation	NOUN
cana-5503	2	16	dr	dr	PROPN
cana-5503	2	17	.	.	PROPN
cana-5503	2	18	sandhya	sandhya	PROPN
cana-5503	2	19	vats	vat	NOUN
cana-5503	2	20	assistant	assistant	NOUN
cana-5503	2	21	professor	professor	NOUN
cana-5503	2	22	in	in	ADP
cana-5503	2	23	computer	computer	NOUN
cana-5503	2	24	science	science	PROPN
cana-5503	2	25	department	department	PROPN
cana-5503	2	26	,	,	PUNCT
cana-5503	2	27	guru	guru	NOUN
cana-5503	2	28	nanak	nanak	PROPN
cana-5503	2	29	college	college	PROPN
cana-5503	2	30	,	,	PUNCT
cana-5503	2	31	budhlada	budhlada	PROPN
cana-5503	2	32	(	(	PUNCT
cana-5503	2	33	mansa	mansa	PROPN
cana-5503	2	34	)	)	PUNCT
cana-5503	2	35	email	email	NOUN
cana-5503	2	36	:	:	PUNCT
cana-5503	2	37	profsandhyavats@gmail.com	profsandhyavats@gmail.com	X
cana-5503	2	38	article	article	NOUN
cana-5503	2	39	history	history	NOUN
cana-5503	2	40	:	:	PUNCT
cana-5503	2	41	received	receive	VERB
cana-5503	2	42	:	:	PUNCT
cana-5503	2	43	12	12	NUM
cana-5503	2	44	-	-	SYM
cana-5503	2	45	01	01	NUM
cana-5503	2	46	-	-	PUNCT
cana-5503	2	47	2025	2025	NUM
cana-5503	2	48	revised	revise	VERB
cana-5503	2	49	:	:	PUNCT
cana-5503	2	50	15	15	NUM
cana-5503	2	51	-	-	NUM
cana-5503	2	52	02	02	NUM
cana-5503	2	53	-	-	PUNCT
cana-5503	2	54	2025	2025	NUM
cana-5503	2	55	accepted	accept	VERB
cana-5503	2	56	:	:	PUNCT
cana-5503	2	57	01	01	NUM
cana-5503	2	58	-	-	SYM
cana-5503	2	59	03	03	NUM
cana-5503	2	60	-	-	PUNCT
cana-5503	2	61	2025	2025	NUM
cana-5503	2	62	abstract	abstract	NOUN
cana-5503	2	63	:	:	PUNCT
cana-5503	2	64	segmentation	segmentation	NOUN
cana-5503	2	65	of	of	ADP
cana-5503	2	66	retinal	retinal	ADJ
cana-5503	2	67	blood	blood	NOUN
cana-5503	2	68	vessel	vessel	NOUN
cana-5503	2	69	nowadays	nowadays	ADV
cana-5503	2	70	is	be	AUX
cana-5503	2	71	one	one	NUM
cana-5503	2	72	of	of	ADP
cana-5503	2	73	the	the	DET
cana-5503	2	74	critical	critical	ADJ
cana-5503	2	75	factors	factor	NOUN
cana-5503	2	76	that	that	PRON
cana-5503	2	77	determine	determine	VERB
cana-5503	2	78	the	the	DET
cana-5503	2	79	performance	performance	NOUN
cana-5503	2	80	of	of	ADP
cana-5503	2	81	a	a	DET
cana-5503	2	82	cad	cad	NOUN
cana-5503	2	83	based	base	VERB
cana-5503	2	84	system	system	NOUN
cana-5503	2	85	.	.	PUNCT
cana-5503	3	1	segmentation	segmentation	NOUN
cana-5503	3	2	means	mean	VERB
cana-5503	3	3	extracting	extract	VERB
cana-5503	3	4	the	the	DET
cana-5503	3	5	region	region	NOUN
cana-5503	3	6	of	of	ADP
cana-5503	3	7	disease	disease	NOUN
cana-5503	3	8	from	from	ADP
cana-5503	3	9	the	the	DET
cana-5503	3	10	image	image	NOUN
cana-5503	3	11	.	.	PUNCT
cana-5503	4	1	segmentation	segmentation	NOUN
cana-5503	4	2	of	of	ADP
cana-5503	4	3	retinal	retinal	ADJ
cana-5503	4	4	blood	blood	NOUN
cana-5503	4	5	vessels	vessel	NOUN
cana-5503	4	6	'	'	PART
cana-5503	4	7	boundary	boundary	NOUN
cana-5503	4	8	is	be	AUX
cana-5503	4	9	required	require	VERB
cana-5503	4	10	to	to	PART
cana-5503	4	11	segment	segment	VERB
cana-5503	4	12	them	they	PRON
cana-5503	4	13	precisely	precisely	ADV
cana-5503	4	14	because	because	SCONJ
cana-5503	4	15	an	an	DET
cana-5503	4	16	eye	eye	NOUN
cana-5503	4	17	surgeon	surgeon	NOUN
cana-5503	4	18	would	would	AUX
cana-5503	4	19	n't	not	PART
cana-5503	4	20	be	be	AUX
cana-5503	4	21	able	able	ADJ
cana-5503	4	22	to	to	PART
cana-5503	4	23	predict	predict	VERB
cana-5503	4	24	the	the	DET
cana-5503	4	25	disease	disease	NOUN
cana-5503	4	26	area	area	NOUN
cana-5503	4	27	if	if	SCONJ
cana-5503	4	28	segmentaion	segmentaion	NOUN
cana-5503	4	29	not	not	PART
cana-5503	4	30	accurately	accurately	ADV
cana-5503	4	31	done	do	VERB
cana-5503	4	32	.	.	PUNCT
cana-5503	5	1	segmentation	segmentation	NOUN
cana-5503	5	2	in	in	ADP
cana-5503	5	3	the	the	DET
cana-5503	5	4	proposed	propose	VERB
cana-5503	5	5	method	method	NOUN
cana-5503	5	6	is	be	AUX
cana-5503	5	7	carried	carry	VERB
cana-5503	5	8	out	out	ADP
cana-5503	5	9	by	by	ADP
cana-5503	5	10	morphological	morphological	ADJ
cana-5503	5	11	operation	operation	NOUN
cana-5503	5	12	that	that	PRON
cana-5503	5	13	extracted	extract	VERB
cana-5503	5	14	the	the	DET
cana-5503	5	15	feature	feature	NOUN
cana-5503	5	16	robustly	robustly	ADV
cana-5503	5	17	and	and	CCONJ
cana-5503	5	18	ultimately	ultimately	ADV
cana-5503	5	19	distance	distance	NOUN
cana-5503	5	20	based	base	VERB
cana-5503	5	21	clustering	clustering	NOUN
cana-5503	5	22	is	be	AUX
cana-5503	5	23	applied	apply	VERB
cana-5503	5	24	to	to	PART
cana-5503	5	25	segment	segment	VERB
cana-5503	5	26	the	the	DET
cana-5503	5	27	image	image	NOUN
cana-5503	5	28	.	.	PUNCT
cana-5503	6	1	keywords	keyword	NOUN
cana-5503	6	2	:	:	PUNCT
cana-5503	6	3	segmentation	segmentation	NOUN
cana-5503	6	4	,	,	PUNCT
cana-5503	6	5	clustering	clustering	ADJ
cana-5503	6	6	,	,	PUNCT
cana-5503	6	7	morphological	morphological	ADJ
cana-5503	6	8	,	,	PUNCT
cana-5503	6	9	psnr	psnr	NOUN
cana-5503	6	10	,	,	PUNCT
cana-5503	6	11	mse	mse	PROPN
cana-5503	6	12	,	,	PUNCT
cana-5503	6	13	accuracy	accuracy	NOUN
cana-5503	6	14	.	.	PUNCT
cana-5503	7	1	introduction	introduction	NOUN
cana-5503	7	2	artificial	artificial	ADJ
cana-5503	7	3	neural	neural	ADJ
cana-5503	7	4	network	network	NOUN
cana-5503	7	5	with	with	ADP
cana-5503	7	6	over	over	ADP
cana-5503	7	7	two	two	NUM
cana-5503	7	8	hidden	hidden	ADJ
cana-5503	7	9	layers	layer	NOUN
cana-5503	7	10	are	be	AUX
cana-5503	7	11	referred	refer	VERB
cana-5503	7	12	to	to	ADP
cana-5503	7	13	as	as	ADP
cana-5503	7	14	a	a	DET
cana-5503	7	15	deep	deep	ADJ
cana-5503	7	16	neural	neural	ADJ
cana-5503	7	17	network	network	NOUN
cana-5503	7	18	.	.	PUNCT
cana-5503	8	1	there	there	PRON
cana-5503	8	2	are	be	VERB
cana-5503	8	3	different	different	ADJ
cana-5503	8	4	architectures	architecture	NOUN
cana-5503	8	5	of	of	ADP
cana-5503	8	6	deep	deep	ADJ
cana-5503	8	7	neural	neural	ADJ
cana-5503	8	8	networks	network	NOUN
cana-5503	8	9	depending	depend	VERB
cana-5503	8	10	on	on	ADP
cana-5503	8	11	types	type	NOUN
cana-5503	8	12	of	of	ADP
cana-5503	8	13	connections	connection	NOUN
cana-5503	8	14	between	between	ADP
cana-5503	8	15	layers	layer	NOUN
cana-5503	8	16	or	or	CCONJ
cana-5503	8	17	operations	operation	NOUN
cana-5503	8	18	within	within	ADP
cana-5503	8	19	a	a	DET
cana-5503	8	20	layer	layer	NOUN
cana-5503	8	21	or	or	CCONJ
cana-5503	8	22	types	type	NOUN
cana-5503	8	23	of	of	ADP
cana-5503	8	24	units	unit	NOUN
cana-5503	8	25	within	within	ADP
cana-5503	8	26	a	a	DET
cana-5503	8	27	layer	layer	NOUN
cana-5503	8	28	.	.	PUNCT
cana-5503	9	1	for	for	ADP
cana-5503	9	2	a	a	DET
cana-5503	9	3	multi	multi	ADJ
cana-5503	9	4	-	-	ADJ
cana-5503	9	5	layer	layer	ADJ
cana-5503	9	6	perceptron	perceptron	NOUN
cana-5503	9	7	,	,	PUNCT
cana-5503	9	8	there	there	PRON
cana-5503	9	9	are	be	VERB
cana-5503	9	10	feed	feed	NOUN
cana-5503	9	11	-	-	PUNCT
cana-5503	9	12	forward	forward	NOUN
cana-5503	9	13	connections	connection	NOUN
cana-5503	9	14	whereas	whereas	SCONJ
cana-5503	9	15	a	a	DET
cana-5503	9	16	recurrent	recurrent	ADJ
cana-5503	9	17	neural	neural	ADJ
cana-5503	9	18	network	network	NOUN
cana-5503	9	19	contains	contain	VERB
cana-5503	9	20	recurrent	recurrent	ADJ
cana-5503	9	21	connections	connection	NOUN
cana-5503	9	22	that	that	PRON
cana-5503	9	23	give	give	VERB
cana-5503	9	24	past	past	ADJ
cana-5503	9	25	signals	signal	NOUN
cana-5503	9	26	to	to	PART
cana-5503	9	27	process	process	VERB
cana-5503	9	28	along	along	ADP
cana-5503	9	29	with	with	ADP
cana-5503	9	30	the	the	DET
cana-5503	9	31	present	present	ADJ
cana-5503	9	32	signal	signal	NOUN
cana-5503	9	33	during	during	ADP
cana-5503	9	34	training	training	NOUN
cana-5503	9	35	.	.	PUNCT
cana-5503	10	1	a	a	DET
cana-5503	10	2	convolutional	convolutional	ADJ
cana-5503	10	3	neural	neural	ADJ
cana-5503	10	4	network	network	NOUN
cana-5503	10	5	consists	consist	VERB
cana-5503	10	6	of	of	ADP
cana-5503	10	7	convolution	convolution	NOUN
cana-5503	10	8	layers	layer	NOUN
cana-5503	10	9	that	that	PRON
cana-5503	10	10	perform	perform	VERB
cana-5503	10	11	convolution	convolution	NOUN
cana-5503	10	12	between	between	ADP
cana-5503	10	13	input	input	NOUN
cana-5503	10	14	data	datum	NOUN
cana-5503	10	15	and	and	CCONJ
cana-5503	10	16	a	a	DET
cana-5503	10	17	sequence	sequence	NOUN
cana-5503	10	18	of	of	ADP
cana-5503	10	19	feature	feature	NOUN
cana-5503	10	20	detectors	detector	NOUN
cana-5503	10	21	.	.	PUNCT
cana-5503	11	1	a	a	DET
cana-5503	11	2	deep	deep	ADJ
cana-5503	11	3	belief	belief	NOUN
cana-5503	11	4	net	net	NOUN
cana-5503	11	5	consists	consist	VERB
cana-5503	11	6	of	of	ADP
cana-5503	11	7	stochastic	stochastic	ADJ
cana-5503	11	8	units	unit	NOUN
cana-5503	11	9	and	and	CCONJ
cana-5503	11	10	there	there	PRON
cana-5503	11	11	are	be	VERB
cana-5503	11	12	connections	connection	NOUN
cana-5503	11	13	between	between	ADP
cana-5503	11	14	layers	layer	NOUN
cana-5503	11	15	from	from	ADP
cana-5503	11	16	top	top	ADJ
cana-5503	11	17	layer	layer	NOUN
cana-5503	11	18	to	to	ADP
cana-5503	11	19	bottom	bottom	ADJ
cana-5503	11	20	layer	layer	NOUN
cana-5503	11	21	.	.	PUNCT
cana-5503	12	1	these	these	DET
cana-5503	12	2	models	model	NOUN
cana-5503	12	3	have	have	AUX
cana-5503	12	4	been	be	AUX
cana-5503	12	5	used	use	VERB
cana-5503	12	6	to	to	PART
cana-5503	12	7	tackle	tackle	VERB
cana-5503	12	8	a	a	DET
cana-5503	12	9	variety	variety	NOUN
cana-5503	12	10	of	of	ADP
cana-5503	12	11	problems	problem	NOUN
cana-5503	12	12	ranging	range	VERB
cana-5503	12	13	from	from	ADP
cana-5503	12	14	image	image	NOUN
cana-5503	12	15	analysis	analysis	NOUN
cana-5503	12	16	to	to	ADP
cana-5503	12	17	natural	natural	ADJ
cana-5503	12	18	language	language	NOUN
cana-5503	12	19	processing	processing	NOUN
cana-5503	12	20	.	.	PUNCT
cana-5503	13	1	deep	deep	ADJ
cana-5503	13	2	learning	learning	NOUN
cana-5503	13	3	has	have	AUX
cana-5503	13	4	proved	prove	VERB
cana-5503	13	5	very	very	ADV
cana-5503	13	6	effective	effective	ADJ
cana-5503	13	7	in	in	ADP
cana-5503	13	8	image	image	NOUN
cana-5503	13	9	segmentation	segmentation	NOUN
cana-5503	13	10	,	,	PUNCT
cana-5503	13	11	with	with	ADP
cana-5503	13	12	very	very	ADV
cana-5503	13	13	robust	robust	ADJ
cana-5503	13	14	applications	application	NOUN
cana-5503	13	15	of	of	ADP
cana-5503	13	16	object	object	NOUN
cana-5503	13	17	,	,	PUNCT
cana-5503	13	18	human	human	ADJ
cana-5503	13	19	or	or	CCONJ
cana-5503	13	20	semantic	semantic	ADJ
cana-5503	13	21	segmentation	segmentation	NOUN
cana-5503	13	22	to	to	ADP
cana-5503	13	23	natural	natural	ADJ
cana-5503	13	24	images	image	NOUN
cana-5503	13	25	[	[	X
cana-5503	13	26	1	1	NUM
cana-5503	13	27	]	]	PUNCT
cana-5503	13	28	.	.	PUNCT
cana-5503	14	1	so	so	ADV
cana-5503	14	2	far	far	ADV
cana-5503	14	3	,	,	PUNCT
cana-5503	14	4	organ	organ	NOUN
cana-5503	14	5	segmentation	segmentation	NOUN
cana-5503	14	6	from	from	ADP
cana-5503	14	7	medical	medical	ADJ
cana-5503	14	8	images	image	NOUN
cana-5503	14	9	has	have	AUX
cana-5503	14	10	seen	see	VERB
cana-5503	14	11	relatively	relatively	ADV
cana-5503	14	12	limited	limited	ADJ
cana-5503	14	13	work	work	NOUN
cana-5503	14	14	,	,	PUNCT
cana-5503	14	15	including	include	VERB
cana-5503	14	16	brain	brain	NOUN
cana-5503	14	17	part	part	NOUN
cana-5503	14	18	segmentation	segmentation	NOUN
cana-5503	14	19	from	from	ADP
cana-5503	14	20	mri	mri	NOUN
cana-5503	14	21	images	image	NOUN
cana-5503	14	22	and	and	CCONJ
cana-5503	14	23	cell	cell	NOUN
cana-5503	14	24	segmentation	segmentation	NOUN
cana-5503	14	25	from	from	ADP
cana-5503	14	26	microscopic	microscopic	ADJ
cana-5503	14	27	images	image	NOUN
cana-5503	14	28	[	[	X
cana-5503	14	29	2	2	NUM
cana-5503	14	30	]	]	PUNCT
cana-5503	14	31	,	,	PUNCT
cana-5503	14	32	[	[	X
cana-5503	14	33	3	3	NUM
cana-5503	14	34	]	]	PUNCT
cana-5503	14	35	.	.	PUNCT
cana-5503	15	1	applications	application	NOUN
cana-5503	15	2	of	of	ADP
cana-5503	15	3	deep	deep	ADJ
cana-5503	15	4	networks	network	NOUN
cana-5503	15	5	to	to	ADP
cana-5503	15	6	retinal	retinal	ADJ
cana-5503	15	7	vessel	vessel	NOUN
cana-5503	15	8	segmentation	segmentation	NOUN
cana-5503	15	9	have	have	AUX
cana-5503	15	10	also	also	ADV
cana-5503	15	11	begun	begin	VERB
cana-5503	15	12	to	to	PART
cana-5503	15	13	emerge	emerge	VERB
cana-5503	15	14	over	over	ADP
cana-5503	15	15	the	the	DET
cana-5503	15	16	past	past	ADJ
cana-5503	15	17	few	few	ADJ
cana-5503	15	18	years	year	NOUN
cana-5503	16	1	[	[	X
cana-5503	16	2	3]–[9	3]–[9	NUM
cana-5503	16	3	]	]	X
cana-5503	16	4	.	.	PUNCT
cana-5503	17	1	a	a	DET
cana-5503	17	2	major	major	ADJ
cana-5503	17	3	strength	strength	NOUN
cana-5503	17	4	of	of	ADP
cana-5503	17	5	employing	employ	VERB
cana-5503	17	6	a	a	DET
cana-5503	17	7	deep	deep	ADJ
cana-5503	17	8	network	network	NOUN
cana-5503	17	9	in	in	ADP
cana-5503	17	10	medical	medical	ADJ
cana-5503	17	11	image	image	NOUN
cana-5503	17	12	segmentation	segmentation	NOUN
cana-5503	17	13	can	can	AUX
cana-5503	17	14	be	be	AUX
cana-5503	17	15	the	the	DET
cana-5503	17	16	adaptation	adaptation	NOUN
cana-5503	17	17	of	of	ADP
cana-5503	17	18	the	the	DET
cana-5503	17	19	technique	technique	NOUN
cana-5503	17	20	to	to	PART
cana-5503	17	21	segment	segment	VERB
cana-5503	17	22	new	new	ADJ
cana-5503	17	23	data	datum	NOUN
cana-5503	17	24	,	,	PUNCT
cana-5503	17	25	obtained	obtain	VERB
cana-5503	17	26	by	by	ADP
cana-5503	17	27	a	a	DET
cana-5503	17	28	new	new	ADJ
cana-5503	17	29	acquisition	acquisition	NOUN
cana-5503	17	30	system	system	NOUN
cana-5503	17	31	,	,	PUNCT
cana-5503	17	32	by	by	ADP
cana-5503	17	33	simply	simply	ADV
cana-5503	17	34	retuning	retune	VERB
cana-5503	17	35	the	the	DET
cana-5503	17	36	network	network	NOUN
cana-5503	17	37	.	.	PUNCT
cana-5503	18	1	by	by	ADP
cana-5503	18	2	way	way	NOUN
cana-5503	18	3	of	of	ADP
cana-5503	18	4	contrast	contrast	NOUN
cana-5503	18	5	,	,	PUNCT
cana-5503	18	6	classical	classical	ADJ
cana-5503	18	7	techniques	technique	NOUN
cana-5503	18	8	have	have	VERB
cana-5503	18	9	to	to	PART
cana-5503	18	10	undergo	undergo	VERB
cana-5503	18	11	adaptation	adaptation	NOUN
cana-5503	18	12	to	to	PART
cana-5503	18	13	segment	segment	VERB
cana-5503	18	14	new	new	ADJ
cana-5503	18	15	data	datum	NOUN
cana-5503	18	16	,	,	PUNCT
cana-5503	18	17	frequently	frequently	ADV
cana-5503	18	18	involving	involve	VERB
cana-5503	18	19	redesigning	redesigning	NOUN
cana-5503	18	20	following	follow	VERB
cana-5503	18	21	the	the	DET
cana-5503	18	22	new	new	ADJ
cana-5503	18	23	dataset	dataset	NOUN
cana-5503	18	24	or	or	CCONJ
cana-5503	18	25	trying	try	VERB
cana-5503	18	26	to	to	PART
cana-5503	18	27	find	find	VERB
cana-5503	18	28	optimal	optimal	ADJ
cana-5503	18	29	parameters	parameter	NOUN
cana-5503	18	30	.	.	PUNCT
cana-5503	19	1	on	on	ADP
cana-5503	19	2	the	the	DET
cana-5503	19	3	negative	negative	ADJ
cana-5503	19	4	side	side	NOUN
cana-5503	19	5	,	,	PUNCT
cana-5503	19	6	training	train	VERB
cana-5503	19	7	a	a	DET
cana-5503	19	8	deep	deep	ADJ
cana-5503	19	9	network	network	NOUN
cana-5503	19	10	can	can	AUX
cana-5503	19	11	prove	prove	VERB
cana-5503	19	12	to	to	PART
cana-5503	19	13	be	be	AUX
cana-5503	19	14	a	a	DET
cana-5503	19	15	problem	problem	NOUN
cana-5503	19	16	of	of	ADP
cana-5503	19	17	acquiring	acquire	VERB
cana-5503	19	18	large	large	ADJ
cana-5503	19	19	sets	set	NOUN
cana-5503	19	20	of	of	ADP
cana-5503	19	21	labeled	label	VERB
cana-5503	19	22	examples	example	NOUN
cana-5503	19	23	,	,	PUNCT
cana-5503	19	24	and	and	CCONJ
cana-5503	19	25	that	that	PRON
cana-5503	19	26	can	can	AUX
cana-5503	19	27	be	be	AUX
cana-5503	19	28	regarded	regard	VERB
cana-5503	19	29	as	as	ADP
cana-5503	19	30	the	the	DET
cana-5503	19	31	greatest	great	ADJ
cana-5503	19	32	drawback	drawback	NOUN
cana-5503	19	33	of	of	ADP
cana-5503	19	34	this	this	DET
cana-5503	19	35	technique	technique	NOUN
cana-5503	19	36	.	.	PUNCT
cana-5503	20	1	communications	communication	NOUN
cana-5503	20	2	on	on	ADP
cana-5503	20	3	applied	apply	VERB
cana-5503	20	4	nonlinear	nonlinear	ADJ
cana-5503	20	5	analysis	analysis	NOUN
cana-5503	20	6	issn	issn	NOUN
cana-5503	20	7	:	:	PUNCT
cana-5503	20	8	1074	1074	NUM
cana-5503	20	9	-	-	PUNCT
cana-5503	20	10	133x	133x	NUM
cana-5503	20	11	vol	vol	VERB
cana-5503	20	12	32	32	NUM
cana-5503	20	13	no	no	NOUN
cana-5503	20	14	.	.	PUNCT
cana-5503	21	1	10s	10	NOUN
cana-5503	21	2	(	(	PUNCT
cana-5503	21	3	2025	2025	NUM
cana-5503	21	4	)	)	PUNCT
cana-5503	21	5	2532	2532	NUM
cana-5503	22	1	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-5503	22	2	proposed	propose	VERB
cana-5503	22	3	method	method	NOUN
cana-5503	22	4	in	in	ADP
cana-5503	22	5	this	this	DET
cana-5503	22	6	work	work	NOUN
cana-5503	22	7	,	,	PUNCT
cana-5503	22	8	cross	cross	ADJ
cana-5503	22	9	-	-	NOUN
cana-5503	22	10	modality	modality	ADJ
cana-5503	22	11	learning	learning	NOUN
cana-5503	22	12	method	method	NOUN
cana-5503	22	13	is	be	AUX
cana-5503	22	14	considered	consider	VERB
cana-5503	22	15	to	to	PART
cana-5503	22	16	segment	segment	VERB
cana-5503	22	17	the	the	DET
cana-5503	22	18	vessels	vessel	NOUN
cana-5503	22	19	based	base	VERB
cana-5503	22	20	on	on	ADP
cana-5503	22	21	the	the	DET
cana-5503	22	22	fact	fact	NOUN
cana-5503	22	23	that	that	SCONJ
cana-5503	22	24	it	it	PRON
cana-5503	22	25	takes	take	VERB
cana-5503	22	26	into	into	ADP
cana-5503	22	27	consideration	consideration	NOUN
cana-5503	22	28	the	the	DET
cana-5503	22	29	cohesion	cohesion	NOUN
cana-5503	22	30	of	of	ADP
cana-5503	22	31	neighbor	neighbor	NOUN
cana-5503	22	32	pixels	pixel	NOUN
cana-5503	22	33	belonging	belong	VERB
cana-5503	22	34	to	to	ADP
cana-5503	22	35	a	a	DET
cana-5503	22	36	similar	similar	ADJ
cana-5503	22	37	class	class	NOUN
cana-5503	22	38	in	in	ADP
cana-5503	22	39	the	the	DET
cana-5503	22	40	process	process	NOUN
cana-5503	22	41	of	of	ADP
cana-5503	22	42	segmentation	segmentation	NOUN
cana-5503	22	43	.	.	PUNCT
cana-5503	23	1	further	far	ADV
cana-5503	23	2	,	,	PUNCT
cana-5503	23	3	the	the	DET
cana-5503	23	4	method	method	NOUN
cana-5503	23	5	applies	apply	VERB
cana-5503	23	6	to	to	ADP
cana-5503	23	7	the	the	DET
cana-5503	23	8	nature	nature	NOUN
cana-5503	23	9	of	of	ADP
cana-5503	23	10	the	the	DET
cana-5503	23	11	problem	problem	NOUN
cana-5503	23	12	elucidated	elucidate	VERB
cana-5503	23	13	hereinafter	hereinafter	NOUN
cana-5503	23	14	.	.	PUNCT
cana-5503	24	1	the	the	DET
cana-5503	24	2	fundus	fundus	NOUN
cana-5503	24	3	image	image	NOUN
cana-5503	24	4	patches	patch	NOUN
cana-5503	24	5	can	can	AUX
cana-5503	24	6	be	be	AUX
cana-5503	24	7	regarded	regard	VERB
cana-5503	24	8	as	as	ADP
cana-5503	24	9	noisy	noisy	ADJ
cana-5503	24	10	versions	version	NOUN
cana-5503	24	11	of	of	ADP
cana-5503	24	12	the	the	DET
cana-5503	24	13	vessel	vessel	NOUN
cana-5503	24	14	masks	mask	NOUN
cana-5503	24	15	.	.	PUNCT
cana-5503	25	1	it	it	PRON
cana-5503	25	2	is	be	AUX
cana-5503	25	3	illustrated	illustrate	VERB
cana-5503	25	4	through	through	ADP
cana-5503	25	5	a	a	DET
cana-5503	25	6	fundus	fundus	NOUN
cana-5503	25	7	image	image	NOUN
cana-5503	25	8	patch	patch	NOUN
cana-5503	25	9	and	and	CCONJ
cana-5503	25	10	its	its	PRON
cana-5503	25	11	potential	potential	ADJ
cana-5503	25	12	vessel	vessel	NOUN
cana-5503	25	13	mask	mask	NOUN
cana-5503	25	14	in	in	ADP
cana-5503	25	15	figure	figure	NOUN
cana-5503	25	16	1	1	NUM
cana-5503	25	17	.	.	PUNCT
cana-5503	25	18	figure	figure	VERB
cana-5503	25	19	1	1	NUM
cana-5503	25	20	a	a	DET
cana-5503	25	21	fundus	fundus	NOUN
cana-5503	25	22	image	image	NOUN
cana-5503	25	23	patch	patch	NOUN
cana-5503	25	24	in	in	ADP
cana-5503	25	25	the	the	DET
cana-5503	25	26	left	left	NOUN
cana-5503	25	27	and	and	CCONJ
cana-5503	25	28	its	its	PRON
cana-5503	25	29	vessel	vessel	NOUN
cana-5503	25	30	map	map	NOUN
cana-5503	25	31	in	in	ADP
cana-5503	25	32	the	the	DET
cana-5503	25	33	right	right	NOUN
cana-5503	25	34	as	as	SCONJ
cana-5503	25	35	illustrated	illustrate	VERB
cana-5503	25	36	from	from	ADP
cana-5503	25	37	the	the	DET
cana-5503	25	38	figure	figure	NOUN
cana-5503	25	39	,	,	PUNCT
cana-5503	25	40	the	the	DET
cana-5503	25	41	correspondence	correspondence	NOUN
cana-5503	25	42	between	between	ADP
cana-5503	25	43	these	these	DET
cana-5503	25	44	patches	patch	NOUN
cana-5503	25	45	of	of	ADP
cana-5503	25	46	fundus	fundus	NOUN
cana-5503	25	47	images	image	NOUN
cana-5503	25	48	and	and	CCONJ
cana-5503	25	49	their	their	PRON
cana-5503	25	50	corresponding	correspond	VERB
cana-5503	25	51	vessel	vessel	NOUN
cana-5503	25	52	masks	mask	NOUN
cana-5503	25	53	is	be	AUX
cana-5503	25	54	not	not	PART
cana-5503	25	55	that	that	ADV
cana-5503	25	56	complicated	complicated	ADJ
cana-5503	25	57	,	,	PUNCT
cana-5503	25	58	compared	compare	VERB
cana-5503	25	59	to	to	ADP
cana-5503	25	60	the	the	DET
cana-5503	25	61	correspondence	correspondence	NOUN
cana-5503	25	62	between	between	ADP
cana-5503	25	63	the	the	DET
cana-5503	25	64	samples	sample	NOUN
cana-5503	25	65	of	of	ADP
cana-5503	25	66	audio	audio	ADJ
cana-5503	25	67	and	and	CCONJ
cana-5503	25	68	visual	visual	ADJ
cana-5503	25	69	data	datum	NOUN
cana-5503	25	70	in	in	ADP
cana-5503	25	71	earlier	early	ADJ
cana-5503	25	72	applications	application	NOUN
cana-5503	25	73	of	of	ADP
cana-5503	25	74	cross	cross	ADJ
cana-5503	25	75	-	-	NOUN
cana-5503	25	76	modality	modality	ADJ
cana-5503	25	77	learning	learning	NOUN
cana-5503	25	78	[	[	X
cana-5503	25	79	10	10	NUM
cana-5503	25	80	]	]	PUNCT
cana-5503	25	81	.	.	PUNCT
cana-5503	26	1	it	it	PRON
cana-5503	26	2	is	be	AUX
cana-5503	26	3	possible	possible	ADJ
cana-5503	26	4	to	to	PART
cana-5503	26	5	have	have	VERB
cana-5503	26	6	a	a	DET
cana-5503	26	7	linear	linear	ADJ
cana-5503	26	8	correspondence	correspondence	NOUN
cana-5503	26	9	between	between	ADP
cana-5503	26	10	fundus	fundus	NOUN
cana-5503	26	11	images	image	NOUN
cana-5503	26	12	and	and	CCONJ
cana-5503	26	13	their	their	PRON
cana-5503	26	14	vessel	vessel	NOUN
cana-5503	26	15	map	map	NOUN
cana-5503	26	16	in	in	ADP
cana-5503	26	17	the	the	DET
cana-5503	26	18	case	case	NOUN
cana-5503	26	19	of	of	ADP
cana-5503	26	20	unrealistically	unrealistically	ADV
cana-5503	26	21	low	low	ADJ
cana-5503	26	22	noise	noise	NOUN
cana-5503	26	23	levels	level	NOUN
cana-5503	26	24	,	,	PUNCT
cana-5503	26	25	nearly	nearly	ADV
cana-5503	26	26	zero	zero	NUM
cana-5503	26	27	,	,	PUNCT
cana-5503	26	28	in	in	ADP
cana-5503	26	29	fundus	fundus	NOUN
cana-5503	26	30	images	image	NOUN
cana-5503	26	31	.	.	PUNCT
cana-5503	27	1	due	due	ADP
cana-5503	27	2	to	to	ADP
cana-5503	27	3	this	this	DET
cana-5503	27	4	likeness	likeness	NOUN
cana-5503	27	5	,	,	PUNCT
cana-5503	27	6	a	a	DET
cana-5503	27	7	joint	joint	ADJ
cana-5503	27	8	representation	representation	NOUN
cana-5503	27	9	learned	learn	VERB
cana-5503	27	10	among	among	ADP
cana-5503	27	11	fundus	fundus	NOUN
cana-5503	27	12	images	image	NOUN
cana-5503	27	13	and	and	CCONJ
cana-5503	27	14	their	their	PRON
cana-5503	27	15	vessel	vessel	NOUN
cana-5503	27	16	masks	mask	NOUN
cana-5503	27	17	can	can	AUX
cana-5503	27	18	respond	respond	VERB
cana-5503	27	19	to	to	ADP
cana-5503	27	20	the	the	DET
cana-5503	27	21	properties	property	NOUN
cana-5503	27	22	of	of	ADP
cana-5503	27	23	the	the	DET
cana-5503	27	24	two	two	NUM
cana-5503	27	25	data	datum	NOUN
cana-5503	27	26	modalities	modality	NOUN
cana-5503	27	27	by	by	ADP
cana-5503	27	28	emphasizing	emphasize	VERB
cana-5503	27	29	the	the	DET
cana-5503	27	30	central	central	ADJ
cana-5503	27	31	structures	structure	NOUN
cana-5503	27	32	of	of	ADP
cana-5503	27	33	concern	concern	NOUN
cana-5503	27	34	,	,	PUNCT
cana-5503	27	35	blood	blood	NOUN
cana-5503	27	36	vessels	vessel	NOUN
cana-5503	27	37	,	,	PUNCT
cana-5503	27	38	concurrently	concurrently	ADV
cana-5503	27	39	[	[	X
cana-5503	27	40	11	11	NUM
cana-5503	27	41	]	]	PUNCT
cana-5503	27	42	.	.	PUNCT
cana-5503	28	1	application	application	NOUN
cana-5503	28	2	of	of	ADP
cana-5503	28	3	this	this	DET
cana-5503	28	4	method	method	NOUN
cana-5503	28	5	can	can	AUX
cana-5503	28	6	be	be	AUX
cana-5503	28	7	done	do	VERB
cana-5503	28	8	by	by	ADP
cana-5503	28	9	a	a	DET
cana-5503	28	10	generative	generative	ADJ
cana-5503	28	11	learning	learning	NOUN
cana-5503	28	12	process	process	NOUN
cana-5503	28	13	,	,	PUNCT
cana-5503	28	14	for	for	ADP
cana-5503	28	15	example	example	NOUN
cana-5503	28	16	by	by	ADP
cana-5503	28	17	employing	employ	VERB
cana-5503	28	18	a	a	DET
cana-5503	28	19	generative	generative	ADJ
cana-5503	28	20	morphological	morphological	ADJ
cana-5503	28	21	operation	operation	NOUN
cana-5503	28	22	.	.	PUNCT
cana-5503	29	1	there	there	PRON
cana-5503	29	2	are	be	VERB
cana-5503	29	3	two	two	NUM
cana-5503	29	4	explanations	explanation	NOUN
cana-5503	29	5	of	of	ADP
cana-5503	29	6	why	why	SCONJ
cana-5503	29	7	a	a	DET
cana-5503	29	8	generative	generative	ADJ
cana-5503	29	9	learning	learning	NOUN
cana-5503	29	10	method	method	NOUN
cana-5503	29	11	is	be	AUX
cana-5503	29	12	chosen	choose	VERB
cana-5503	29	13	.	.	PUNCT
cana-5503	30	1	the	the	DET
cana-5503	30	2	first	first	ADJ
cana-5503	30	3	reason	reason	NOUN
cana-5503	30	4	is	be	AUX
cana-5503	30	5	that	that	SCONJ
cana-5503	30	6	both	both	CCONJ
cana-5503	30	7	cross	cross	ADJ
cana-5503	30	8	-	-	ADJ
cana-5503	30	9	modality	modality	ADJ
cana-5503	30	10	learning	learning	NOUN
cana-5503	30	11	and	and	CCONJ
cana-5503	30	12	generative	generative	ADJ
cana-5503	30	13	learning	learning	NOUN
cana-5503	30	14	need	need	VERB
cana-5503	30	15	a	a	DET
cana-5503	30	16	proper	proper	ADJ
cana-5503	30	17	representation	representation	NOUN
cana-5503	30	18	of	of	ADP
cana-5503	30	19	the	the	DET
cana-5503	30	20	input	input	NOUN
cana-5503	30	21	.	.	PUNCT
cana-5503	31	1	the	the	DET
cana-5503	31	2	second	second	ADJ
cana-5503	31	3	reason	reason	NOUN
cana-5503	31	4	is	be	AUX
cana-5503	31	5	that	that	SCONJ
cana-5503	31	6	the	the	DET
cana-5503	31	7	learned	learn	VERB
cana-5503	31	8	feature	feature	NOUN
cana-5503	31	9	from	from	ADP
cana-5503	31	10	the	the	DET
cana-5503	31	11	generative	generative	ADJ
cana-5503	31	12	training	training	NOUN
cana-5503	31	13	of	of	ADP
cana-5503	31	14	a	a	DET
cana-5503	31	15	dbn	dbn	NOUN
cana-5503	31	16	,	,	PUNCT
cana-5503	31	17	also	also	ADV
cana-5503	31	18	known	know	VERB
cana-5503	31	19	as	as	ADP
cana-5503	31	20	pre	pre	ADJ
cana-5503	31	21	-	-	NOUN
cana-5503	31	22	training	training	NOUN
cana-5503	31	23	,	,	PUNCT
cana-5503	31	24	can	can	AUX
cana-5503	31	25	be	be	AUX
cana-5503	31	26	manipulated	manipulate	VERB
cana-5503	31	27	to	to	PART
cana-5503	31	28	gain	gain	VERB
cana-5503	31	29	helpful	helpful	ADJ
cana-5503	31	30	feature	feature	NOUN
cana-5503	31	31	in	in	ADP
cana-5503	31	32	the	the	DET
cana-5503	31	33	context	context	NOUN
cana-5503	31	34	of	of	ADP
cana-5503	31	35	cross	cross	ADJ
cana-5503	31	36	-	-	NOUN
cana-5503	31	37	modality	modality	ADJ
cana-5503	31	38	learning	learning	NOUN
cana-5503	31	39	[	[	X
cana-5503	31	40	12	12	NUM
cana-5503	31	41	]	]	PUNCT
cana-5503	31	42	.	.	PUNCT
cana-5503	31	43	.	.	PUNCT
cana-5503	32	1	figure	figure	NOUN
cana-5503	32	2	2	2	NUM
cana-5503	32	3	proposed	propose	VERB
cana-5503	32	4	method	method	NOUN
cana-5503	32	5	input	input	NOUN
cana-5503	32	6	images	image	NOUN
cana-5503	32	7	dataset	dataset	VERB
cana-5503	32	8	channel	channel	NOUN
cana-5503	32	9	wise	wise	ADJ
cana-5503	32	10	seperation	seperation	NOUN
cana-5503	32	11	for	for	ADP
cana-5503	32	12	noise	noise	NOUN
cana-5503	32	13	reduction	reduction	NOUN
cana-5503	32	14	learning	learning	NOUN
cana-5503	32	15	based	base	VERB
cana-5503	32	16	morphological	morphological	ADJ
cana-5503	32	17	operations	operation	NOUN
cana-5503	32	18	k	k	ADJ
cana-5503	32	19	-	-	ADJ
cana-5503	32	20	mean	mean	ADJ
cana-5503	32	21	classfier	classfier	NOUN
cana-5503	32	22	enhancement	enhancement	NOUN
cana-5503	32	23	filter	filter	NOUN
cana-5503	32	24	segmented	segment	VERB
cana-5503	32	25	image	image	NOUN
cana-5503	32	26	communications	communication	NOUN
cana-5503	32	27	on	on	ADP
cana-5503	32	28	applied	apply	VERB
cana-5503	32	29	nonlinear	nonlinear	ADJ
cana-5503	32	30	analysis	analysis	NOUN
cana-5503	32	31	issn	issn	NOUN
cana-5503	32	32	:	:	PUNCT
cana-5503	32	33	1074	1074	NUM
cana-5503	32	34	-	-	PUNCT
cana-5503	32	35	133x	133x	NUM
cana-5503	32	36	vol	vol	VERB
cana-5503	32	37	32	32	NUM
cana-5503	32	38	no	no	NOUN
cana-5503	32	39	.	.	PUNCT
cana-5503	33	1	10s	10	NOUN
cana-5503	33	2	(	(	PUNCT
cana-5503	33	3	2025	2025	NUM
cana-5503	33	4	)	)	PUNCT
cana-5503	33	5	2533	2533	NUM
cana-5503	34	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-5503	34	2	morphological	morphological	ADJ
cana-5503	34	3	operations	operation	NOUN
cana-5503	34	4	assist	assist	VERB
cana-5503	34	5	in	in	ADP
cana-5503	34	6	smoothen	smoothen	ADV
cana-5503	34	7	the	the	DET
cana-5503	34	8	images	image	NOUN
cana-5503	34	9	and	and	CCONJ
cana-5503	34	10	extract	extract	VERB
cana-5503	34	11	the	the	DET
cana-5503	34	12	feature	feature	NOUN
cana-5503	34	13	from	from	ADP
cana-5503	34	14	the	the	DET
cana-5503	34	15	image	image	NOUN
cana-5503	34	16	.	.	PUNCT
cana-5503	35	1	the	the	DET
cana-5503	35	2	feature	feature	NOUN
cana-5503	35	3	extraction	extraction	NOUN
cana-5503	35	4	is	be	AUX
cana-5503	35	5	carried	carry	VERB
cana-5503	35	6	out	out	ADP
cana-5503	35	7	to	to	PART
cana-5503	35	8	maintain	maintain	VERB
cana-5503	35	9	the	the	DET
cana-5503	35	10	original	original	ADJ
cana-5503	35	11	and	and	CCONJ
cana-5503	35	12	the	the	DET
cana-5503	35	13	actual	actual	ADJ
cana-5503	35	14	expected	expect	VERB
cana-5503	35	15	shape	shape	NOUN
cana-5503	35	16	of	of	ADP
cana-5503	35	17	the	the	DET
cana-5503	35	18	retinal	retinal	ADJ
cana-5503	35	19	blood	blood	NOUN
cana-5503	35	20	vessel	vessel	NOUN
cana-5503	35	21	.	.	PUNCT
cana-5503	36	1	the	the	DET
cana-5503	36	2	different	different	ADJ
cana-5503	36	3	operations	operation	NOUN
cana-5503	36	4	are	be	AUX
cana-5503	36	5	employed	employ	VERB
cana-5503	36	6	like	like	ADP
cana-5503	36	7	dilation	dilation	NOUN
cana-5503	36	8	and	and	CCONJ
cana-5503	36	9	erosion	erosion	NOUN
cana-5503	36	10	operations	operation	NOUN
cana-5503	36	11	are	be	AUX
cana-5503	36	12	employed	employ	VERB
cana-5503	36	13	combinations	combination	NOUN
cana-5503	36	14	to	to	PART
cana-5503	36	15	execute	execute	VERB
cana-5503	36	16	the	the	DET
cana-5503	36	17	edges	edge	NOUN
cana-5503	36	18	detection	detection	NOUN
cana-5503	36	19	after	after	SCONJ
cana-5503	36	20	the	the	DET
cana-5503	36	21	threshold	threshold	NOUN
cana-5503	36	22	is	be	AUX
cana-5503	36	23	predicted	predict	VERB
cana-5503	36	24	dynamically	dynamically	ADV
cana-5503	36	25	.	.	PUNCT
cana-5503	37	1	the	the	DET
cana-5503	37	2	dilation	dilation	NOUN
cana-5503	37	3	process	process	NOUN
cana-5503	37	4	is	be	AUX
cana-5503	37	5	applied	apply	VERB
cana-5503	37	6	to	to	PART
cana-5503	37	7	isolate	isolate	VERB
cana-5503	37	8	the	the	DET
cana-5503	37	9	pixels	pixel	NOUN
cana-5503	37	10	from	from	ADP
cana-5503	37	11	one	one	NUM
cana-5503	37	12	another	another	DET
cana-5503	37	13	.	.	PUNCT
cana-5503	38	1	for	for	ADP
cana-5503	38	2	all	all	DET
cana-5503	38	3	the	the	DET
cana-5503	38	4	clip	clip	NOUN
cana-5503	38	5	window	window	NOUN
cana-5503	38	6	similar	similar	ADJ
cana-5503	38	7	pixels	pixel	NOUN
cana-5503	38	8	the	the	DET
cana-5503	38	9	1	1	NUM
cana-5503	38	10	’s	’s	PART
cana-5503	38	11	matrix	matrix	NOUN
cana-5503	38	12	is	be	AUX
cana-5503	38	13	created	create	VERB
cana-5503	38	14	and	and	CCONJ
cana-5503	38	15	none	none	NOUN
cana-5503	38	16	of	of	ADP
cana-5503	38	17	them	they	PRON
cana-5503	38	18	is	be	AUX
cana-5503	38	19	created	create	VERB
cana-5503	38	20	like	like	ADP
cana-5503	38	21	matrix	matrix	NOUN
cana-5503	38	22	of	of	ADP
cana-5503	38	23	0	0	NUM
cana-5503	38	24	’s	’	NOUN
cana-5503	38	25	by	by	ADP
cana-5503	38	26	which	which	PRON
cana-5503	38	27	the	the	DET
cana-5503	38	28	boundaries	boundary	NOUN
cana-5503	38	29	can	can	AUX
cana-5503	38	30	be	be	AUX
cana-5503	38	31	predicated	predicate	VERB
cana-5503	38	32	.	.	PUNCT
cana-5503	39	1	the	the	DET
cana-5503	39	2	process	process	NOUN
cana-5503	39	3	of	of	ADP
cana-5503	39	4	erosion	erosion	NOUN
cana-5503	39	5	will	will	AUX
cana-5503	39	6	eliminate	eliminate	VERB
cana-5503	39	7	the	the	DET
cana-5503	39	8	redundant	redundant	ADJ
cana-5503	39	9	boundary	boundary	ADJ
cana-5503	39	10	pixels	pixel	NOUN
cana-5503	39	11	to	to	PART
cana-5503	39	12	left	left	VERB
cana-5503	39	13	user	user	NOUN
cana-5503	39	14	with	with	ADP
cana-5503	39	15	clear	clear	ADJ
cana-5503	39	16	idea	idea	NOUN
cana-5503	39	17	of	of	ADP
cana-5503	39	18	the	the	DET
cana-5503	39	19	boundary	boundary	NOUN
cana-5503	39	20	and	and	CCONJ
cana-5503	39	21	dimensions	dimension	NOUN
cana-5503	39	22	.	.	PUNCT
cana-5503	40	1	the	the	DET
cana-5503	40	2	quality	quality	NOUN
cana-5503	40	3	of	of	ADP
cana-5503	40	4	the	the	DET
cana-5503	40	5	image	image	NOUN
cana-5503	40	6	will	will	AUX
cana-5503	40	7	be	be	AUX
cana-5503	40	8	measured	measure	VERB
cana-5503	40	9	based	base	VERB
cana-5503	40	10	on	on	ADP
cana-5503	40	11	the	the	DET
cana-5503	40	12	mse	mse	NOUN
cana-5503	40	13	and	and	CCONJ
cana-5503	40	14	psnr	psnr	NOUN
cana-5503	40	15	.	.	PUNCT
cana-5503	41	1	the	the	DET
cana-5503	41	2	mse	mse	PROPN
cana-5503	41	3	is	be	AUX
cana-5503	41	4	mean	mean	ADJ
cana-5503	41	5	square	square	ADJ
cana-5503	41	6	error	error	NOUN
cana-5503	41	7	which	which	PRON
cana-5503	41	8	is	be	AUX
cana-5503	41	9	calculated	calculate	VERB
cana-5503	41	10	after	after	ADP
cana-5503	41	11	subtracting	subtract	VERB
cana-5503	41	12	the	the	DET
cana-5503	41	13	final	final	ADJ
cana-5503	41	14	image	image	NOUN
cana-5503	41	15	from	from	ADP
cana-5503	41	16	original	original	ADJ
cana-5503	41	17	[	[	X
cana-5503	41	18	2	2	NUM
cana-5503	41	19	]	]	PUNCT
cana-5503	41	20	,	,	PUNCT
cana-5503	41	21	[	[	X
cana-5503	41	22	13	13	NUM
cana-5503	41	23	]	]	PUNCT
cana-5503	41	24	,	,	PUNCT
cana-5503	41	25	[	[	X
cana-5503	41	26	14	14	NUM
cana-5503	41	27	]	]	PUNCT
cana-5503	41	28	.	.	PUNCT
cana-5503	42	1	the	the	DET
cana-5503	42	2	psnr	psnr	NOUN
cana-5503	42	3	value	value	NOUN
cana-5503	42	4	is	be	AUX
cana-5503	42	5	calculated	calculate	VERB
cana-5503	42	6	by	by	ADP
cana-5503	42	7	:	:	PUNCT
cana-5503	42	8	psnr	psnr	NOUN
cana-5503	42	9	=	=	NOUN
cana-5503	42	10	10log10	10log10	NUM
cana-5503	43	1	[	[	X
cana-5503	43	2	i	i	NOUN
cana-5503	43	3	2	2	NUM
cana-5503	43	4	/	/	SYM
cana-5503	43	5	mse	mse	PROPN
cana-5503	43	6	]	]	PUNCT
cana-5503	43	7	…	…	PUNCT
cana-5503	43	8	…	…	PUNCT
cana-5503	43	9	..	..	PUNCT
cana-5503	43	10	(	(	PUNCT
cana-5503	43	11	1	1	X
cana-5503	43	12	)	)	PUNCT
cana-5503	43	13	where	where	SCONJ
cana-5503	43	14	i	i	PRON
cana-5503	43	15	ranges	range	VERB
cana-5503	43	16	from	from	ADP
cana-5503	43	17	0	0	NUM
cana-5503	43	18	to	to	ADP
cana-5503	43	19	255	255	NUM
cana-5503	43	20	.	.	PUNCT
cana-5503	44	1	results	result	NOUN
cana-5503	44	2	and	and	CCONJ
cana-5503	44	3	discussion	discussion	NOUN
cana-5503	44	4	the	the	DET
cana-5503	44	5	proposed	propose	VERB
cana-5503	44	6	network	network	NOUN
cana-5503	44	7	's	's	PART
cana-5503	44	8	performance	performance	NOUN
cana-5503	44	9	is	be	AUX
cana-5503	44	10	tested	test	VERB
cana-5503	44	11	on	on	ADP
cana-5503	44	12	the	the	DET
cana-5503	44	13	clinical	clinical	ADJ
cana-5503	44	14	dataset	dataset	NOUN
cana-5503	44	15	.	.	PUNCT
cana-5503	45	1	the	the	DET
cana-5503	45	2	proposed	propose	VERB
cana-5503	45	3	method	method	NOUN
cana-5503	45	4	's	's	PART
cana-5503	45	5	segmentation	segmentation	NOUN
cana-5503	45	6	performance	performance	NOUN
cana-5503	45	7	will	will	AUX
cana-5503	45	8	first	first	ADV
cana-5503	45	9	be	be	AUX
cana-5503	45	10	inspected	inspect	VERB
cana-5503	45	11	on	on	ADP
cana-5503	45	12	the	the	DET
cana-5503	45	13	best	good	ADJ
cana-5503	45	14	case	case	NOUN
cana-5503	45	15	and	and	CCONJ
cana-5503	45	16	the	the	DET
cana-5503	45	17	worst	bad	ADJ
cana-5503	45	18	case	case	NOUN
cana-5503	45	19	images	image	NOUN
cana-5503	45	20	,	,	PUNCT
cana-5503	45	21	and	and	CCONJ
cana-5503	45	22	then	then	ADV
cana-5503	45	23	compared	compare	VERB
cana-5503	45	24	to	to	ADP
cana-5503	45	25	that	that	PRON
cana-5503	45	26	of	of	ADP
cana-5503	45	27	the	the	DET
cana-5503	45	28	state	state	NOUN
cana-5503	45	29	of	of	ADP
cana-5503	45	30	the	the	DET
cana-5503	45	31	art	art	NOUN
cana-5503	45	32	techniques	technique	NOUN
cana-5503	45	33	.	.	PUNCT
cana-5503	46	1	table	table	NOUN
cana-5503	46	2	i	i	PRON
cana-5503	46	3	represents	represent	VERB
cana-5503	46	4	the	the	DET
cana-5503	46	5	overall	overall	ADJ
cana-5503	46	6	performance	performance	NOUN
cana-5503	46	7	of	of	ADP
cana-5503	46	8	the	the	DET
cana-5503	46	9	network	network	NOUN
cana-5503	46	10	proposed	propose	VERB
cana-5503	46	11	by	by	ADP
cana-5503	46	12	us	we	PRON
cana-5503	46	13	on	on	ADP
cana-5503	46	14	the	the	DET
cana-5503	46	15	clinical	clinical	ADJ
cana-5503	46	16	dataset	dataset	NOUN
cana-5503	46	17	with	with	ADP
cana-5503	46	18	regards	regard	NOUN
cana-5503	46	19	to	to	ADP
cana-5503	46	20	evaluation	evaluation	NOUN
cana-5503	46	21	parameters	parameter	NOUN
cana-5503	46	22	.	.	PUNCT
cana-5503	47	1	it	it	PRON
cana-5503	47	2	also	also	ADV
cana-5503	47	3	reflects	reflect	VERB
cana-5503	47	4	the	the	DET
cana-5503	47	5	best	good	ADJ
cana-5503	47	6	and	and	CCONJ
cana-5503	47	7	the	the	DET
cana-5503	47	8	worst	bad	ADJ
cana-5503	47	9	performances	performance	NOUN
cana-5503	47	10	based	base	VERB
cana-5503	47	11	on	on	ADP
cana-5503	47	12	the	the	DET
cana-5503	47	13	highest	high	ADJ
cana-5503	47	14	and	and	CCONJ
cana-5503	47	15	lowest	low	ADJ
cana-5503	47	16	accuracies	accuracy	NOUN
cana-5503	47	17	.	.	PUNCT
cana-5503	48	1	as	as	SCONJ
cana-5503	48	2	seen	see	VERB
cana-5503	48	3	from	from	ADP
cana-5503	48	4	the	the	DET
cana-5503	48	5	table	table	NOUN
cana-5503	48	6	,	,	PUNCT
cana-5503	48	7	there	there	PRON
cana-5503	48	8	is	be	VERB
cana-5503	48	9	not	not	PART
cana-5503	48	10	that	that	ADV
cana-5503	48	11	large	large	ADJ
cana-5503	48	12	a	a	DET
cana-5503	48	13	difference	difference	NOUN
cana-5503	48	14	between	between	ADP
cana-5503	48	15	best	good	ADJ
cana-5503	48	16	case	case	NOUN
cana-5503	48	17	and	and	CCONJ
cana-5503	48	18	worst	bad	ADJ
cana-5503	48	19	case	case	NOUN
cana-5503	48	20	performance	performance	NOUN
cana-5503	48	21	metrics	metric	NOUN
cana-5503	48	22	based	base	VERB
cana-5503	48	23	on	on	ADP
cana-5503	48	24	accuracy	accuracy	NOUN
cana-5503	48	25	.	.	PUNCT
cana-5503	49	1	the	the	DET
cana-5503	49	2	proposed	propose	VERB
cana-5503	49	3	network	network	NOUN
cana-5503	49	4	achieved	achieve	VERB
cana-5503	49	5	its	its	PRON
cana-5503	49	6	best	good	ADJ
cana-5503	49	7	and	and	CCONJ
cana-5503	49	8	the	the	DET
cana-5503	49	9	worst	bad	ADJ
cana-5503	49	10	performances	performance	NOUN
cana-5503	49	11	respectively	respectively	ADV
cana-5503	49	12	on	on	ADP
cana-5503	49	13	the	the	DET
cana-5503	49	14	19th	19th	NOUN
cana-5503	49	15	and	and	CCONJ
cana-5503	49	16	the	the	DET
cana-5503	49	17	3rd	3rd	ADJ
cana-5503	49	18	images	image	NOUN
cana-5503	49	19	.	.	PUNCT
cana-5503	50	1	these	these	DET
cana-5503	50	2	images	image	NOUN
cana-5503	50	3	also	also	ADV
cana-5503	50	4	correspond	correspond	VERB
cana-5503	50	5	to	to	ADP
cana-5503	50	6	the	the	DET
cana-5503	50	7	best	good	ADJ
cana-5503	50	8	and	and	CCONJ
cana-5503	50	9	the	the	DET
cana-5503	50	10	worst	bad	ADJ
cana-5503	50	11	performances	performance	NOUN
cana-5503	50	12	of	of	ADP
cana-5503	50	13	recent	recent	ADJ
cana-5503	50	14	studies	study	NOUN
cana-5503	50	15	employing	employ	VERB
cana-5503	50	16	supervised	supervised	ADJ
cana-5503	50	17	algorithms	algorithm	NOUN
cana-5503	50	18	[	[	X
cana-5503	50	19	7	7	NUM
cana-5503	50	20	]	]	PUNCT
cana-5503	50	21	,	,	PUNCT
cana-5503	50	22	[	[	X
cana-5503	50	23	15	15	NUM
cana-5503	50	24	]	]	PUNCT
cana-5503	50	25	,	,	PUNCT
cana-5503	50	26	[	[	X
cana-5503	50	27	16	16	NUM
cana-5503	50	28	]	]	PUNCT
cana-5503	50	29	.	.	PUNCT
cana-5503	51	1	the	the	DET
cana-5503	51	2	average	average	ADJ
cana-5503	51	3	threshold	threshold	NOUN
cana-5503	51	4	value	value	NOUN
cana-5503	51	5	in	in	ADP
cana-5503	51	6	binearization	binearization	NOUN
cana-5503	51	7	of	of	ADP
cana-5503	51	8	these	these	DET
cana-5503	51	9	vessel	vessel	NOUN
cana-5503	51	10	probability	probability	NOUN
cana-5503	51	11	maps	map	NOUN
cana-5503	51	12	emerged	emerge	VERB
cana-5503	51	13	to	to	PART
cana-5503	51	14	be	be	AUX
cana-5503	51	15	0:1305_0:0432	0:1305_0:0432	PROPN
cana-5503	51	16	(	(	PUNCT
cana-5503	51	17	mean	mean	VERB
cana-5503	51	18	_	_	DET
cana-5503	51	19	standard	standard	ADJ
cana-5503	51	20	deviation	deviation	NOUN
cana-5503	51	21	)	)	PUNCT
cana-5503	51	22	.	.	PUNCT
cana-5503	52	1	simulated	simulate	VERB
cana-5503	52	2	vessel	vessel	NOUN
cana-5503	52	3	probability	probability	NOUN
cana-5503	52	4	maps	map	NOUN
cana-5503	52	5	and	and	CCONJ
cana-5503	52	6	binary	binary	ADJ
cana-5503	52	7	vessel	vessel	NOUN
cana-5503	52	8	maps	map	NOUN
cana-5503	52	9	of	of	ADP
cana-5503	52	10	these	these	DET
cana-5503	52	11	images	image	NOUN
cana-5503	52	12	may	may	AUX
cana-5503	52	13	be	be	AUX
cana-5503	52	14	obtained	obtain	VERB
cana-5503	52	15	by	by	ADP
cana-5503	52	16	visual	visual	ADJ
cana-5503	52	17	observation	observation	NOUN
cana-5503	52	18	from	from	ADP
cana-5503	52	19	figure	figure	NOUN
cana-5503	52	20	3	3	NUM
cana-5503	52	21	.	.	PUNCT
cana-5503	52	22	figure	figure	VERB
cana-5503	52	23	3	3	NUM
cana-5503	52	24	channel	channel	NOUN
cana-5503	52	25	wise	wise	ADJ
cana-5503	52	26	segmentation	segmentation	NOUN
cana-5503	52	27	in	in	ADP
cana-5503	52	28	figure3	figure3	PROPN
cana-5503	52	29	,	,	PUNCT
cana-5503	52	30	optic	optic	ADJ
cana-5503	52	31	disc	disc	NOUN
cana-5503	52	32	discrimination	discrimination	NOUN
cana-5503	52	33	from	from	ADP
cana-5503	52	34	blood	blood	NOUN
cana-5503	52	35	vessels	vessel	NOUN
cana-5503	52	36	in	in	ADP
cana-5503	52	37	both	both	CCONJ
cana-5503	52	38	best	good	ADJ
cana-5503	52	39	and	and	CCONJ
cana-5503	52	40	worst	bad	ADJ
cana-5503	52	41	case	case	NOUN
cana-5503	52	42	binary	binary	ADJ
cana-5503	52	43	maps	map	NOUN
cana-5503	52	44	is	be	AUX
cana-5503	52	45	done	do	VERB
cana-5503	52	46	well	well	ADV
cana-5503	52	47	,	,	PUNCT
cana-5503	52	48	notwithstanding	notwithstanding	ADP
cana-5503	52	49	the	the	DET
cana-5503	52	50	resemblance	resemblance	NOUN
cana-5503	52	51	of	of	ADP
cana-5503	52	52	its	its	PRON
cana-5503	52	53	border	border	NOUN
cana-5503	52	54	to	to	ADP
cana-5503	52	55	blood	blood	NOUN
cana-5503	52	56	vessels	vessel	NOUN
cana-5503	52	57	in	in	ADP
cana-5503	52	58	terms	term	NOUN
cana-5503	52	59	of	of	ADP
cana-5503	52	60	levels	level	NOUN
cana-5503	52	61	of	of	ADP
cana-5503	52	62	contrast	contrast	NOUN
cana-5503	52	63	.	.	PUNCT
cana-5503	53	1	again	again	ADV
cana-5503	53	2	,	,	PUNCT
cana-5503	53	3	in	in	ADP
cana-5503	53	4	cases	case	NOUN
cana-5503	53	5	of	of	ADP
cana-5503	53	6	uniform	uniform	ADJ
cana-5503	53	7	illumination	illumination	NOUN
cana-5503	53	8	over	over	ADP
cana-5503	53	9	fundus	fundus	NOUN
cana-5503	53	10	images	image	NOUN
cana-5503	53	11	and	and	CCONJ
cana-5503	53	12	poor	poor	ADJ
cana-5503	53	13	blood	blood	NOUN
cana-5503	53	14	vessel	vessel	NOUN
cana-5503	53	15	contrast	contrast	NOUN
cana-5503	53	16	,	,	PUNCT
cana-5503	53	17	there	there	PRON
cana-5503	53	18	also	also	ADV
cana-5503	53	19	does	do	AUX
cana-5503	53	20	not	not	PART
cana-5503	53	21	appear	appear	VERB
cana-5503	53	22	to	to	PART
cana-5503	53	23	be	be	AUX
cana-5503	53	24	any	any	DET
cana-5503	53	25	disruption	disruption	NOUN
cana-5503	53	26	of	of	ADP
cana-5503	53	27	even	even	ADV
cana-5503	53	28	small	small	ADJ
cana-5503	53	29	blood	blood	NOUN
cana-5503	53	30	vessels	vessel	NOUN
cana-5503	53	31	detection	detection	NOUN
cana-5503	53	32	.	.	PUNCT
cana-5503	54	1	conversely	conversely	ADV
cana-5503	54	2	,	,	PUNCT
cana-5503	54	3	the	the	DET
cana-5503	54	4	proposed	propose	VERB
cana-5503	54	5	network	network	NOUN
cana-5503	54	6	appears	appear	VERB
cana-5503	54	7	to	to	PART
cana-5503	54	8	be	be	AUX
cana-5503	54	9	at	at	ADP
cana-5503	54	10	times	time	NOUN
cana-5503	54	11	deceived	deceive	VERB
cana-5503	54	12	by	by	ADP
cana-5503	54	13	pathologies	pathology	NOUN
cana-5503	54	14	in	in	ADP
cana-5503	54	15	fundus	fundus	NOUN
cana-5503	54	16	images	image	NOUN
cana-5503	54	17	and	and	CCONJ
cana-5503	54	18	can	can	AUX
cana-5503	54	19	at	at	ADP
cana-5503	54	20	times	time	NOUN
cana-5503	54	21	treat	treat	VERB
cana-5503	54	22	them	they	PRON
cana-5503	54	23	communications	communication	NOUN
cana-5503	54	24	on	on	ADP
cana-5503	54	25	applied	apply	VERB
cana-5503	54	26	nonlinear	nonlinear	ADJ
cana-5503	54	27	analysis	analysis	NOUN
cana-5503	54	28	issn	issn	NOUN
cana-5503	54	29	:	:	PUNCT
cana-5503	54	30	1074	1074	NUM
cana-5503	54	31	-	-	PUNCT
cana-5503	54	32	133x	133x	NUM
cana-5503	54	33	vol	vol	VERB
cana-5503	54	34	32	32	NUM
cana-5503	54	35	no	no	NOUN
cana-5503	54	36	.	.	PUNCT
cana-5503	55	1	10s	10	NOUN
cana-5503	55	2	(	(	PUNCT
cana-5503	55	3	2025	2025	NUM
cana-5503	55	4	)	)	PUNCT
cana-5503	55	5	2534	2534	NUM
cana-5503	55	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5503	55	7	as	as	ADP
cana-5503	55	8	part	part	NOUN
cana-5503	55	9	of	of	ADP
cana-5503	55	10	blood	blood	NOUN
cana-5503	55	11	vessels	vessel	NOUN
cana-5503	55	12	.	.	PUNCT
cana-5503	56	1	this	this	PRON
cana-5503	56	2	can	can	AUX
cana-5503	56	3	be	be	AUX
cana-5503	56	4	appreciated	appreciate	VERB
cana-5503	56	5	by	by	ADP
cana-5503	56	6	the	the	DET
cana-5503	56	7	red	red	ADJ
cana-5503	56	8	circular	circular	ADJ
cana-5503	56	9	area	area	NOUN
cana-5503	56	10	in	in	ADP
cana-5503	56	11	the	the	DET
cana-5503	56	12	binary	binary	ADJ
cana-5503	56	13	vessel	vessel	NOUN
cana-5503	56	14	map	map	NOUN
cana-5503	56	15	of	of	ADP
cana-5503	56	16	the	the	DET
cana-5503	56	17	worst	bad	ADJ
cana-5503	56	18	case	case	NOUN
cana-5503	56	19	in	in	ADP
cana-5503	56	20	the	the	DET
cana-5503	56	21	same	same	ADJ
cana-5503	56	22	figure	figure	NOUN
cana-5503	56	23	.	.	PUNCT
cana-5503	57	1	the	the	DET
cana-5503	57	2	proposed	propose	VERB
cana-5503	57	3	network	network	NOUN
cana-5503	57	4	was	be	AUX
cana-5503	57	5	also	also	ADV
cana-5503	57	6	found	find	VERB
cana-5503	57	7	to	to	PART
cana-5503	57	8	errantly	errantly	ADV
cana-5503	57	9	treat	treat	VERB
cana-5503	57	10	a	a	DET
cana-5503	57	11	portion	portion	NOUN
cana-5503	57	12	of	of	ADP
cana-5503	57	13	cotton	cotton	NOUN
cana-5503	57	14	wool	wool	NOUN
cana-5503	57	15	spots	spot	NOUN
cana-5503	57	16	.	.	PUNCT
cana-5503	58	1	though	though	SCONJ
cana-5503	58	2	these	these	DET
cana-5503	58	3	responses	response	NOUN
cana-5503	58	4	are	be	AUX
cana-5503	58	5	weaker	weak	ADJ
cana-5503	58	6	than	than	ADP
cana-5503	58	7	or	or	CCONJ
cana-5503	58	8	nearly	nearly	ADV
cana-5503	58	9	equal	equal	ADJ
cana-5503	58	10	to	to	ADP
cana-5503	58	11	the	the	DET
cana-5503	58	12	responses	response	NOUN
cana-5503	58	13	of	of	ADP
cana-5503	58	14	neighborhood	neighborhood	NOUN
cana-5503	58	15	capillaries	capillary	NOUN
cana-5503	58	16	in	in	ADP
cana-5503	58	17	the	the	DET
cana-5503	58	18	corresponding	corresponding	ADJ
cana-5503	58	19	probability	probability	NOUN
cana-5503	58	20	map	map	NOUN
cana-5503	58	21	,	,	PUNCT
cana-5503	58	22	some	some	DET
cana-5503	58	23	pathologic	pathologic	ADJ
cana-5503	58	24	responses	response	NOUN
cana-5503	58	25	appear	appear	VERB
cana-5503	58	26	in	in	ADP
cana-5503	58	27	the	the	DET
cana-5503	58	28	end	end	NOUN
cana-5503	58	29	binary	binary	NOUN
cana-5503	58	30	map	map	NOUN
cana-5503	58	31	due	due	ADP
cana-5503	58	32	to	to	ADP
cana-5503	58	33	extremely	extremely	ADV
cana-5503	58	34	low	low	ADJ
cana-5503	58	35	threshold	threshold	NOUN
cana-5503	58	36	.	.	PUNCT
cana-5503	59	1	also	also	ADV
cana-5503	59	2	,	,	PUNCT
cana-5503	59	3	readers	reader	NOUN
cana-5503	59	4	must	must	AUX
cana-5503	59	5	keep	keep	VERB
cana-5503	59	6	in	in	ADP
cana-5503	59	7	mind	mind	NOUN
cana-5503	59	8	that	that	SCONJ
cana-5503	59	9	the	the	DET
cana-5503	59	10	clinical	clinical	ADJ
cana-5503	59	11	dataset	dataset	NOUN
cana-5503	59	12	predominantly	predominantly	ADV
cana-5503	59	13	has	have	VERB
cana-5503	59	14	healthy	healthy	ADJ
cana-5503	59	15	fundus	fundus	NOUN
cana-5503	59	16	images	image	NOUN
cana-5503	59	17	,	,	PUNCT
cana-5503	59	18	so	so	SCONJ
cana-5503	59	19	it	it	PRON
cana-5503	59	20	could	could	AUX
cana-5503	59	21	also	also	ADV
cana-5503	59	22	be	be	AUX
cana-5503	59	23	a	a	DET
cana-5503	59	24	contributor	contributor	NOUN
cana-5503	59	25	to	to	ADP
cana-5503	59	26	network	network	NOUN
cana-5503	59	27	's	's	PART
cana-5503	59	28	poor	poor	ADJ
cana-5503	59	29	performance	performance	NOUN
cana-5503	59	30	over	over	ADP
cana-5503	59	31	pathologic	pathologic	ADJ
cana-5503	59	32	images	image	NOUN
cana-5503	59	33	.	.	PUNCT
cana-5503	60	1	the	the	DET
cana-5503	60	2	proposed	propose	VERB
cana-5503	60	3	network	network	NOUN
cana-5503	60	4	's	's	PART
cana-5503	60	5	performance	performance	NOUN
cana-5503	60	6	generated	generate	VERB
cana-5503	60	7	bigger	big	ADJ
cana-5503	60	8	auc	auc	NOUN
cana-5503	60	9	value	value	NOUN
cana-5503	60	10	,	,	PUNCT
cana-5503	60	11	outperforming	outperform	VERB
cana-5503	60	12	the	the	DET
cana-5503	60	13	performances	performance	NOUN
cana-5503	60	14	of	of	ADP
cana-5503	60	15	the	the	DET
cana-5503	60	16	state	state	NOUN
cana-5503	60	17	of	of	ADP
cana-5503	60	18	the	the	DET
cana-5503	60	19	art	art	NOUN
cana-5503	60	20	deep	deep	ADJ
cana-5503	60	21	network	network	NOUN
cana-5503	60	22	proposals	proposal	NOUN
cana-5503	60	23	[	[	X
cana-5503	60	24	3	3	NUM
cana-5503	60	25	]	]	PUNCT
cana-5503	60	26	,	,	PUNCT
cana-5503	60	27	[	[	X
cana-5503	60	28	17]–[19	17]–[19	NUM
cana-5503	60	29	]	]	X
cana-5503	60	30	.	.	PUNCT
cana-5503	61	1	for	for	ADP
cana-5503	61	2	the	the	DET
cana-5503	61	3	rest	rest	NOUN
cana-5503	61	4	of	of	ADP
cana-5503	61	5	the	the	DET
cana-5503	61	6	evaluation	evaluation	NOUN
cana-5503	61	7	measures	measure	NOUN
cana-5503	61	8	,	,	PUNCT
cana-5503	61	9	the	the	DET
cana-5503	61	10	proposed	propose	VERB
cana-5503	61	11	method	method	NOUN
cana-5503	61	12	's	's	PART
cana-5503	61	13	performance	performance	NOUN
cana-5503	61	14	compares	compare	VERB
cana-5503	61	15	favorably	favorably	ADV
cana-5503	61	16	to	to	ADP
cana-5503	61	17	the	the	DET
cana-5503	61	18	performances	performance	NOUN
cana-5503	61	19	of	of	ADP
cana-5503	61	20	the	the	DET
cana-5503	61	21	earlier	early	ADJ
cana-5503	61	22	methods	method	NOUN
cana-5503	61	23	.	.	PUNCT
cana-5503	62	1	among	among	ADP
cana-5503	62	2	them	they	PRON
cana-5503	62	3	,	,	PUNCT
cana-5503	62	4	author	author	NOUN
cana-5503	62	5	in	in	ADP
cana-5503	62	6	[	[	X
cana-5503	62	7	20	20	NUM
cana-5503	62	8	]	]	PUNCT
cana-5503	62	9	comes	come	VERB
cana-5503	62	10	closer	close	ADV
cana-5503	62	11	to	to	ADP
cana-5503	62	12	the	the	DET
cana-5503	62	13	proposed	propose	VERB
cana-5503	62	14	method	method	NOUN
cana-5503	62	15	:	:	PUNCT
cana-5503	62	16	both	both	PRON
cana-5503	62	17	employed	employ	VERB
cana-5503	62	18	a	a	DET
cana-5503	62	19	cross	cross	ADJ
cana-5503	62	20	-	-	ADJ
cana-5503	62	21	modality	modality	ADJ
cana-5503	62	22	learning	learning	NOUN
cana-5503	62	23	strategy	strategy	NOUN
cana-5503	62	24	in	in	ADP
cana-5503	62	25	vasculature	vasculature	NOUN
cana-5503	62	26	segmentation	segmentation	NOUN
cana-5503	62	27	,	,	PUNCT
cana-5503	62	28	and	and	CCONJ
cana-5503	62	29	also	also	ADV
cana-5503	62	30	employed	employ	VERB
cana-5503	62	31	fully	fully	ADV
cana-5503	62	32	connected	connect	VERB
cana-5503	62	33	networks	network	NOUN
cana-5503	62	34	.	.	PUNCT
cana-5503	63	1	but	but	CCONJ
cana-5503	63	2	how	how	SCONJ
cana-5503	63	3	the	the	DET
cana-5503	63	4	methods	method	NOUN
cana-5503	63	5	are	be	AUX
cana-5503	63	6	trained	train	VERB
cana-5503	63	7	differ	differ	VERB
cana-5503	63	8	.	.	PUNCT
cana-5503	64	1	in	in	ADP
cana-5503	64	2	proposed	propose	VERB
cana-5503	64	3	network	network	NOUN
cana-5503	64	4	weights	weight	NOUN
cana-5503	64	5	in	in	ADP
cana-5503	64	6	each	each	DET
cana-5503	64	7	layer	layer	NOUN
cana-5503	64	8	are	be	AUX
cana-5503	64	9	initialized	initialize	VERB
cana-5503	64	10	with	with	ADP
cana-5503	64	11	weights	weight	NOUN
cana-5503	64	12	learned	learn	VERB
cana-5503	64	13	with	with	ADP
cana-5503	64	14	the	the	DET
cana-5503	64	15	probabilistic	probabilistic	ADJ
cana-5503	64	16	training	training	NOUN
cana-5503	64	17	of	of	ADP
cana-5503	64	18	rbms	rbms	NOUN
cana-5503	64	19	.	.	PUNCT
cana-5503	65	1	however	however	ADV
cana-5503	65	2	,	,	PUNCT
cana-5503	65	3	li	li	PROPN
cana-5503	65	4	et	et	PROPN
cana-5503	65	5	al	al	PROPN
cana-5503	65	6	.	.	PROPN
cana-5503	65	7	's	's	PART
cana-5503	65	8	network	network	NOUN
cana-5503	65	9	is	be	AUX
cana-5503	65	10	a	a	DET
cana-5503	65	11	standard	standard	ADJ
cana-5503	65	12	fully	fully	ADV
cana-5503	65	13	connected	connected	ADJ
cana-5503	65	14	network	network	NOUN
cana-5503	65	15	with	with	ADP
cana-5503	65	16	modification	modification	NOUN
cana-5503	65	17	,	,	PUNCT
cana-5503	65	18	where	where	SCONJ
cana-5503	65	19	the	the	DET
cana-5503	65	20	first	first	ADJ
cana-5503	65	21	layer	layer	NOUN
cana-5503	65	22	of	of	ADP
cana-5503	65	23	their	their	PRON
cana-5503	65	24	network	network	NOUN
cana-5503	65	25	is	be	AUX
cana-5503	65	26	initialized	initialize	VERB
cana-5503	65	27	by	by	ADP
cana-5503	65	28	the	the	DET
cana-5503	65	29	weights	weight	NOUN
cana-5503	65	30	learned	learn	VERB
cana-5503	65	31	by	by	ADP
cana-5503	65	32	training	train	VERB
cana-5503	65	33	a	a	DET
cana-5503	65	34	de	de	ADJ
cana-5503	65	35	-	-	ADJ
cana-5503	65	36	noising	noising	ADJ
cana-5503	65	37	auto	auto	NOUN
cana-5503	65	38	encoder	encoder	NOUN
cana-5503	65	39	.	.	PUNCT
cana-5503	66	1	the	the	DET
cana-5503	66	2	rest	rest	NOUN
cana-5503	66	3	of	of	ADP
cana-5503	66	4	the	the	DET
cana-5503	66	5	second	second	ADJ
cana-5503	66	6	and	and	CCONJ
cana-5503	66	7	third	third	ADJ
cana-5503	66	8	layers	layer	NOUN
cana-5503	66	9	were	be	AUX
cana-5503	66	10	initialized	initialize	VERB
cana-5503	66	11	by	by	ADP
cana-5503	66	12	sampling	sample	VERB
cana-5503	66	13	from	from	ADP
cana-5503	66	14	a	a	DET
cana-5503	66	15	normal	normal	ADJ
cana-5503	66	16	.	.	PUNCT
cana-5503	67	1	in	in	ADP
cana-5503	67	2	addition	addition	NOUN
cana-5503	67	3	,	,	PUNCT
cana-5503	67	4	the	the	DET
cana-5503	67	5	number	number	NOUN
cana-5503	67	6	of	of	ADP
cana-5503	67	7	hidden	hidden	ADJ
cana-5503	67	8	layers	layer	NOUN
cana-5503	67	9	employed	employ	VERB
cana-5503	67	10	in	in	ADP
cana-5503	67	11	the	the	DET
cana-5503	67	12	networks	network	NOUN
cana-5503	67	13	varies	vary	VERB
cana-5503	67	14	.	.	PUNCT
cana-5503	68	1	figure	figure	VERB
cana-5503	68	2	4	4	NUM
cana-5503	68	3	blood	blood	NOUN
cana-5503	68	4	vessels	vessel	NOUN
cana-5503	68	5	segmentation	segmentation	NOUN
cana-5503	68	6	from	from	ADP
cana-5503	68	7	ground	ground	NOUN
cana-5503	68	8	truth	truth	NOUN
cana-5503	68	9	image	image	NOUN
cana-5503	68	10	table	table	NOUN
cana-5503	68	11	i	i	PRON
cana-5503	68	12	best	well	ADV
cana-5503	68	13	,	,	PUNCT
cana-5503	68	14	average	average	ADJ
cana-5503	68	15	and	and	CCONJ
cana-5503	68	16	worst	bad	ADJ
cana-5503	68	17	performance	performance	NOUN
cana-5503	68	18	of	of	ADP
cana-5503	68	19	segmentation	segmentation	NOUN
cana-5503	68	20	using	use	VERB
cana-5503	68	21	proposed	propose	VERB
cana-5503	68	22	method	method	NOUN
cana-5503	68	23	on	on	ADP
cana-5503	68	24	clinical	clinical	ADJ
cana-5503	68	25	dataset	dataset	NOUN
cana-5503	68	26	auc	auc	NOUN
cana-5503	68	27	accuracy	accuracy	NOUN
cana-5503	68	28	sensitivity	sensitivity	NOUN
cana-5503	68	29	specificity	specificity	NOUN
cana-5503	68	30	mean	mean	VERB
cana-5503	68	31	0.98	0.98	NUM
cana-5503	68	32	%	%	NOUN
cana-5503	68	33	0.93	0.93	NUM
cana-5503	68	34	%	%	NOUN
cana-5503	68	35	0.78	0.78	NUM
cana-5503	68	36	%	%	NOUN
cana-5503	68	37	0.98	0.98	NUM
cana-5503	68	38	%	%	NOUN
cana-5503	68	39	max	max	NOUN
cana-5503	68	40	0.98	0.98	NUM
cana-5503	68	41	%	%	NOUN
cana-5503	68	42	0.96	0.96	NUM
cana-5503	68	43	%	%	NOUN
cana-5503	68	44	0.79	0.79	NUM
cana-5503	68	45	%	%	NOUN
cana-5503	68	46	0.98	0.98	NUM
cana-5503	68	47	%	%	NOUN
cana-5503	68	48	min	min	NOUN
cana-5503	68	49	0.97	0.97	NUM
cana-5503	68	50	%	%	NOUN
cana-5503	68	51	0.94	0.94	NUM
cana-5503	68	52	%	%	NOUN
cana-5503	68	53	0.74	0.74	NUM
cana-5503	68	54	%	%	NOUN
cana-5503	68	55	0.97	0.97	NUM
cana-5503	68	56	%	%	NOUN
cana-5503	68	57	communications	communication	NOUN
cana-5503	68	58	on	on	ADP
cana-5503	68	59	applied	apply	VERB
cana-5503	68	60	nonlinear	nonlinear	ADJ
cana-5503	68	61	analysis	analysis	NOUN
cana-5503	68	62	issn	issn	NOUN
cana-5503	68	63	:	:	PUNCT
cana-5503	68	64	1074	1074	NUM
cana-5503	68	65	-	-	PUNCT
cana-5503	68	66	133x	133x	NUM
cana-5503	68	67	vol	vol	VERB
cana-5503	68	68	32	32	NUM
cana-5503	68	69	no	no	NOUN
cana-5503	68	70	.	.	PUNCT
cana-5503	69	1	10s	10	NOUN
cana-5503	69	2	(	(	PUNCT
cana-5503	69	3	2025	2025	NUM
cana-5503	69	4	)	)	PUNCT
cana-5503	69	5	2535	2535	NUM
cana-5503	69	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5503	69	7	table	table	NOUN
cana-5503	69	8	ii	ii	PROPN
cana-5503	69	9	psnr	psnr	NOUN
cana-5503	69	10	values	value	NOUN
cana-5503	69	11	of	of	ADP
cana-5503	69	12	proposed	propose	VERB
cana-5503	69	13	and	and	CCONJ
cana-5503	69	14	existing	exist	VERB
cana-5503	69	15	methods	method	NOUN
cana-5503	69	16	method	method	VERB
cana-5503	69	17	psnr	psnr	NOUN
cana-5503	69	18	value	value	NOUN
cana-5503	69	19	dunet	dunet	NOUN
cana-5503	69	20	[	[	X
cana-5503	69	21	21	21	NUM
cana-5503	69	22	]	]	SYM
cana-5503	69	23	31	31	NUM
cana-5503	69	24	median	median	NOUN
cana-5503	69	25	and	and	CCONJ
cana-5503	69	26	clahe	clahe	NOUN
cana-5503	70	1	[	[	X
cana-5503	70	2	22	22	NUM
cana-5503	70	3	]	]	SYM
cana-5503	70	4	33	33	NUM
cana-5503	70	5	distance	distance	NOUN
cana-5503	70	6	[	[	X
cana-5503	70	7	23	23	NUM
cana-5503	70	8	]	]	SYM
cana-5503	70	9	32	32	NUM
cana-5503	70	10	clustering	cluster	VERB
cana-5503	70	11	[	[	X
cana-5503	70	12	24	24	NUM
cana-5503	70	13	]	]	SYM
cana-5503	70	14	29	29	NUM
cana-5503	70	15	proposed	propose	VERB
cana-5503	70	16	method	method	NOUN
cana-5503	70	17	52	52	NUM
cana-5503	70	18	conclusion	conclusion	NOUN
cana-5503	70	19	in	in	ADP
cana-5503	70	20	recent	recent	ADJ
cana-5503	70	21	times	time	NOUN
cana-5503	70	22	,	,	PUNCT
cana-5503	70	23	deep	deep	ADJ
cana-5503	70	24	learning	learning	NOUN
cana-5503	70	25	methods	method	NOUN
cana-5503	70	26	have	have	AUX
cana-5503	70	27	shown	show	VERB
cana-5503	70	28	better	well	ADJ
cana-5503	70	29	performances	performance	NOUN
cana-5503	70	30	than	than	ADP
cana-5503	70	31	other	other	ADJ
cana-5503	70	32	methods	method	NOUN
cana-5503	70	33	[	[	X
cana-5503	70	34	33	33	NUM
cana-5503	70	35	]	]	PUNCT
cana-5503	70	36	.	.	PUNCT
cana-5503	71	1	as	as	ADP
cana-5503	71	2	a	a	DET
cana-5503	71	3	consequence	consequence	NOUN
cana-5503	71	4	,	,	PUNCT
cana-5503	71	5	i	i	PRON
cana-5503	71	6	employ	employ	VERB
cana-5503	71	7	a	a	DET
cana-5503	71	8	deep	deep	ADJ
cana-5503	71	9	network	network	NOUN
cana-5503	71	10	to	to	ADP
cana-5503	71	11	segment	segment	NOUN
cana-5503	71	12	vasculature	vasculature	NOUN
cana-5503	71	13	.	.	PUNCT
cana-5503	72	1	while	while	SCONJ
cana-5503	72	2	the	the	DET
cana-5503	72	3	overall	overall	ADJ
cana-5503	72	4	trend	trend	NOUN
cana-5503	72	5	in	in	ADP
cana-5503	72	6	vasculature	vasculature	NOUN
cana-5503	72	7	segmentation	segmentation	NOUN
cana-5503	72	8	is	be	AUX
cana-5503	72	9	to	to	PART
cana-5503	72	10	classify	classify	VERB
cana-5503	72	11	each	each	DET
cana-5503	72	12	pixel	pixel	NOUN
cana-5503	72	13	in	in	ADP
cana-5503	72	14	a	a	DET
cana-5503	72	15	fundus	fundus	NOUN
cana-5503	72	16	image	image	NOUN
cana-5503	72	17	into	into	ADP
cana-5503	72	18	a	a	DET
cana-5503	72	19	vessel	vessel	NOUN
cana-5503	72	20	pixel	pixel	NOUN
cana-5503	72	21	and	and	CCONJ
cana-5503	72	22	a	a	DET
cana-5503	72	23	non	non	ADJ
cana-5503	72	24	-	-	ADJ
cana-5503	72	25	vessel	vessel	ADJ
cana-5503	72	26	pixel	pixel	NOUN
cana-5503	72	27	,	,	PUNCT
cana-5503	72	28	consideration	consideration	NOUN
cana-5503	72	29	of	of	ADP
cana-5503	72	30	spatial	spatial	ADJ
cana-5503	72	31	connectivity	connectivity	NOUN
cana-5503	72	32	of	of	ADP
cana-5503	72	33	label	label	NOUN
cana-5503	72	34	pixels	pixel	NOUN
cana-5503	72	35	in	in	ADP
cana-5503	72	36	network	network	NOUN
cana-5503	72	37	output	output	NOUN
cana-5503	72	38	has	have	AUX
cana-5503	72	39	been	be	AUX
cana-5503	72	40	seen	see	VERB
cana-5503	72	41	to	to	PART
cana-5503	72	42	enhance	enhance	VERB
cana-5503	72	43	the	the	DET
cana-5503	72	44	quality	quality	NOUN
cana-5503	72	45	of	of	ADP
cana-5503	72	46	segmentations	segmentation	NOUN
cana-5503	72	47	[	[	X
cana-5503	72	48	36	36	NUM
cana-5503	72	49	]	]	PUNCT
cana-5503	72	50	.	.	PUNCT
cana-5503	73	1	the	the	DET
cana-5503	73	2	spatial	spatial	ADJ
cana-5503	73	3	connectivity	connectivity	NOUN
cana-5503	73	4	of	of	ADP
cana-5503	73	5	label	label	NOUN
cana-5503	73	6	pixels	pixel	NOUN
cana-5503	73	7	is	be	AUX
cana-5503	73	8	in	in	ADP
cana-5503	73	9	consideration	consideration	NOUN
cana-5503	73	10	in	in	ADP
cana-5503	73	11	this	this	DET
cana-5503	73	12	thesis	thesis	NOUN
cana-5503	73	13	by	by	ADP
cana-5503	73	14	producing	produce	VERB
cana-5503	73	15	vessel	vessel	NOUN
cana-5503	73	16	masks	mask	NOUN
cana-5503	73	17	of	of	ADP
cana-5503	73	18	input	input	NOUN
cana-5503	73	19	image	image	NOUN
cana-5503	73	20	patches	patch	VERB
cana-5503	73	21	upon	upon	SCONJ
cana-5503	73	22	being	be	AUX
cana-5503	73	23	compliant	compliant	ADJ
cana-5503	73	24	to	to	ADP
cana-5503	73	25	the	the	DET
cana-5503	73	26	cross	cross	ADJ
cana-5503	73	27	-	-	ADJ
cana-5503	73	28	modality	modality	ADJ
cana-5503	73	29	learning	learning	NOUN
cana-5503	73	30	method	method	NOUN
cana-5503	73	31	.	.	PUNCT
cana-5503	74	1	to	to	PART
cana-5503	74	2	make	make	VERB
cana-5503	74	3	the	the	DET
cana-5503	74	4	feature	feature	NOUN
cana-5503	74	5	extraction	extraction	NOUN
cana-5503	74	6	of	of	ADP
cana-5503	74	7	the	the	DET
cana-5503	74	8	proposed	propose	VERB
cana-5503	74	9	more	more	ADV
cana-5503	74	10	spatially	spatially	ADV
cana-5503	74	11	connected	connect	VERB
cana-5503	74	12	,	,	PUNCT
cana-5503	74	13	the	the	DET
cana-5503	74	14	proposed	propose	VERB
cana-5503	74	15	feature	feature	NOUN
cana-5503	74	16	extraction	extraction	NOUN
cana-5503	74	17	is	be	AUX
cana-5503	74	18	improved	improve	VERB
cana-5503	74	19	using	use	VERB
cana-5503	74	20	a	a	DET
cana-5503	74	21	de	de	NOUN
cana-5503	74	22	-	-	NOUN
cana-5503	74	23	noising	noising	NOUN
cana-5503	74	24	,	,	PUNCT
cana-5503	74	25	which	which	PRON
cana-5503	74	26	was	be	AUX
cana-5503	74	27	found	find	VERB
cana-5503	74	28	to	to	PART
cana-5503	74	29	yield	yield	VERB
cana-5503	74	30	more	more	ADJ
cana-5503	74	31	at	at	ADP
cana-5503	74	32	probability	probability	NOUN
cana-5503	74	33	responses	response	NOUN
cana-5503	74	34	to	to	PART
cana-5503	74	35	vasculature	vasculature	VERB
cana-5503	74	36	to	to	ADP
cana-5503	74	37	image	image	NOUN
cana-5503	74	38	background	background	NOUN
cana-5503	74	39	.	.	PUNCT
cana-5503	75	1	while	while	SCONJ
cana-5503	75	2	the	the	DET
cana-5503	75	3	impact	impact	NOUN
cana-5503	75	4	of	of	ADP
cana-5503	75	5	this	this	PRON
cana-5503	75	6	is	be	AUX
cana-5503	75	7	not	not	PART
cana-5503	75	8	to	to	PART
cana-5503	75	9	be	be	AUX
cana-5503	75	10	regarded	regard	VERB
cana-5503	75	11	as	as	ADP
cana-5503	75	12	an	an	DET
cana-5503	75	13	improvement	improvement	NOUN
cana-5503	75	14	in	in	ADP
cana-5503	75	15	terms	term	NOUN
cana-5503	75	16	of	of	ADP
cana-5503	75	17	segmentation	segmentation	NOUN
cana-5503	75	18	where	where	SCONJ
cana-5503	75	19	over	over	ADP
cana-5503	75	20	a	a	DET
cana-5503	75	21	threshold	threshold	NOUN
cana-5503	75	22	probabilities	probability	NOUN
cana-5503	75	23	are	be	AUX
cana-5503	75	24	tagged	tag	VERB
cana-5503	75	25	the	the	DET
cana-5503	75	26	same	same	ADJ
cana-5503	75	27	class	class	NOUN
cana-5503	75	28	,	,	PUNCT
cana-5503	75	29	the	the	DET
cana-5503	75	30	same	same	ADJ
cana-5503	75	31	impact	impact	NOUN
cana-5503	75	32	can	can	AUX
cana-5503	75	33	prove	prove	VERB
cana-5503	75	34	to	to	PART
cana-5503	75	35	be	be	AUX
cana-5503	75	36	beneficial	beneficial	ADJ
cana-5503	75	37	to	to	ADP
cana-5503	75	38	the	the	DET
cana-5503	75	39	robustness	robustness	NOUN
cana-5503	75	40	of	of	ADP
cana-5503	75	41	the	the	DET
cana-5503	75	42	proposed	propose	VERB
cana-5503	75	43	tracking	tracking	NOUN
cana-5503	75	44	method	method	NOUN
cana-5503	75	45	.	.	PUNCT
cana-5503	76	1	the	the	DET
cana-5503	76	2	upgraded	upgrade	VERB
cana-5503	76	3	segmentation	segmentation	NOUN
cana-5503	76	4	is	be	AUX
cana-5503	76	5	also	also	ADV
cana-5503	76	6	found	find	VERB
cana-5503	76	7	to	to	PART
cana-5503	76	8	be	be	AUX
cana-5503	76	9	adaptable	adaptable	ADJ
cana-5503	76	10	to	to	ADP
cana-5503	76	11	a	a	DET
cana-5503	76	12	range	range	NOUN
cana-5503	76	13	of	of	ADP
cana-5503	76	14	applications	application	NOUN
cana-5503	76	15	by	by	ADP
cana-5503	76	16	making	make	VERB
cana-5503	76	17	minimal	minimal	ADJ
cana-5503	76	18	changes	change	NOUN
cana-5503	76	19	to	to	ADP
cana-5503	76	20	its	its	PRON
cana-5503	76	21	architecture	architecture	NOUN
cana-5503	76	22	and	and	CCONJ
cana-5503	76	23	not	not	PART
cana-5503	76	24	altering	alter	VERB
cana-5503	76	25	significantly	significantly	ADV
cana-5503	76	26	the	the	DET
cana-5503	76	27	method	method	NOUN
cana-5503	76	28	of	of	ADP
cana-5503	76	29	network	network	NOUN
cana-5503	76	30	training	training	NOUN
cana-5503	76	31	.	.	PUNCT
cana-5503	77	1	the	the	DET
cana-5503	77	2	network	network	NOUN
cana-5503	77	3	performed	perform	VERB
cana-5503	77	4	equally	equally	ADV
cana-5503	77	5	or	or	CCONJ
cana-5503	77	6	better	well	ADJ
cana-5503	77	7	on	on	ADP
cana-5503	77	8	the	the	DET
cana-5503	77	9	low	low	ADJ
cana-5503	77	10	resolution	resolution	NOUN
cana-5503	77	11	image	image	NOUN
cana-5503	77	12	segmentation	segmentation	NOUN
cana-5503	77	13	when	when	SCONJ
cana-5503	77	14	applied	apply	VERB
cana-5503	77	15	directly	directly	ADV
cana-5503	77	16	,	,	PUNCT
cana-5503	77	17	compared	compare	VERB
cana-5503	77	18	to	to	ADP
cana-5503	77	19	similar	similar	ADJ
cana-5503	77	20	techniques	technique	NOUN
cana-5503	77	21	.	.	PUNCT
cana-5503	78	1	table	table	NOUN
cana-5503	78	2	iii	iii	NOUN
cana-5503	78	3	performance	performance	NOUN
cana-5503	78	4	of	of	ADP
cana-5503	78	5	segmentation	segmentation	NOUN
cana-5503	78	6	on	on	ADP
cana-5503	78	7	used	use	VERB
cana-5503	78	8	clinical	clinical	ADJ
cana-5503	78	9	dataset	dataset	NOUN
cana-5503	78	10	category	category	NOUN
cana-5503	78	11	accuracy	accuracy	NOUN
cana-5503	78	12	matched	match	VERB
cana-5503	78	13	[	[	X
cana-5503	78	14	25	25	NUM
cana-5503	78	15	]	]	SYM
cana-5503	78	16	94.84	94.84	NUM
cana-5503	78	17	%	%	NOUN
cana-5503	78	18	filter	filter	NOUN
cana-5503	79	1	[	[	X
cana-5503	79	2	24	24	NUM
cana-5503	79	3	]	]	PUNCT
cana-5503	79	4	93.41	93.41	NUM
cana-5503	79	5	%	%	NOUN
cana-5503	79	6	adaptive	adaptive	ADJ
cana-5503	79	7	[	[	X
cana-5503	79	8	13	13	NUM
cana-5503	79	9	]	]	SYM
cana-5503	79	10	93.79	93.79	NUM
cana-5503	79	11	%	%	NOUN
cana-5503	79	12	multiscale	multiscale	NOUN
cana-5503	79	13	[	[	X
cana-5503	79	14	26	26	NUM
cana-5503	79	15	]	]	SYM
cana-5503	79	16	92.90	92.90	NUM
cana-5503	79	17	%	%	NOUN
cana-5503	79	18	pattern	pattern	NOUN
cana-5503	79	19	classification	classification	NOUN
cana-5503	79	20	[	[	X
cana-5503	79	21	25	25	NUM
cana-5503	79	22	]	]	SYM
cana-5503	79	23	94.79	94.79	NUM
cana-5503	79	24	%	%	NOUN
cana-5503	79	25	communications	communication	NOUN
cana-5503	79	26	on	on	ADP
cana-5503	79	27	applied	apply	VERB
cana-5503	79	28	nonlinear	nonlinear	ADJ
cana-5503	79	29	analysis	analysis	NOUN
cana-5503	79	30	issn	issn	NOUN
cana-5503	79	31	:	:	PUNCT
cana-5503	79	32	1074	1074	NUM
cana-5503	79	33	-	-	PUNCT
cana-5503	79	34	133x	133x	NUM
cana-5503	79	35	vol	vol	VERB
cana-5503	79	36	32	32	NUM
cana-5503	79	37	no	no	NOUN
cana-5503	79	38	.	.	PUNCT
cana-5503	80	1	10s	10	NOUN
cana-5503	80	2	(	(	PUNCT
cana-5503	80	3	2025	2025	NUM
cana-5503	80	4	)	)	PUNCT
cana-5503	80	5	2536	2536	NUM
cana-5503	80	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5503	80	7	filter	filter	NOUN
cana-5503	80	8	based	base	VERB
cana-5503	80	9	method	method	NOUN
cana-5503	80	10	[	[	X
cana-5503	80	11	27	27	NUM
cana-5503	80	12	]	]	SYM
cana-5503	80	13	95.28	95.28	NUM
cana-5503	80	14	%	%	NOUN
cana-5503	80	15	image	image	NOUN
cana-5503	80	16	features	feature	NOUN
cana-5503	80	17	based	base	VERB
cana-5503	80	18	[	[	X
cana-5503	80	19	28	28	NUM
cana-5503	80	20	]	]	PUNCT
cana-5503	80	21	94.88	94.88	NUM
cana-5503	80	22	%	%	NOUN
cana-5503	80	23	proposed	propose	VERB
cana-5503	80	24	method	method	NOUN
cana-5503	80	25	98.15	98.15	NUM
cana-5503	80	26	%	%	NOUN
cana-5503	80	27	conclusion	conclusion	NOUN
cana-5503	80	28	day	day	NOUN
cana-5503	80	29	by	by	ADP
cana-5503	80	30	day	day	NOUN
cana-5503	80	31	,	,	PUNCT
cana-5503	80	32	the	the	DET
cana-5503	80	33	number	number	NOUN
cana-5503	80	34	of	of	ADP
cana-5503	80	35	patients	patient	NOUN
cana-5503	80	36	and	and	CCONJ
cana-5503	80	37	the	the	DET
cana-5503	80	38	requirement	requirement	NOUN
cana-5503	80	39	of	of	ADP
cana-5503	80	40	the	the	DET
cana-5503	80	41	vessel	vessel	NOUN
cana-5503	80	42	segmentation	segmentation	NOUN
cana-5503	80	43	are	be	AUX
cana-5503	80	44	rising	rise	VERB
cana-5503	80	45	.	.	PUNCT
cana-5503	81	1	the	the	DET
cana-5503	81	2	reason	reason	NOUN
cana-5503	81	3	is	be	AUX
cana-5503	81	4	to	to	PART
cana-5503	81	5	precisely	precisely	ADV
cana-5503	81	6	segment	segment	VERB
cana-5503	81	7	the	the	DET
cana-5503	81	8	disease	disease	NOUN
cana-5503	81	9	boundaries	boundary	NOUN
cana-5503	81	10	to	to	PART
cana-5503	81	11	act	act	VERB
cana-5503	81	12	and	and	CCONJ
cana-5503	81	13	treat	treat	VERB
cana-5503	81	14	the	the	DET
cana-5503	81	15	patient	patient	NOUN
cana-5503	81	16	accordingly	accordingly	ADV
cana-5503	81	17	.	.	PUNCT
cana-5503	82	1	the	the	DET
cana-5503	82	2	blood	blood	NOUN
cana-5503	82	3	vessels	vessel	NOUN
cana-5503	82	4	are	be	AUX
cana-5503	82	5	segmented	segment	VERB
cana-5503	82	6	by	by	ADP
cana-5503	82	7	the	the	DET
cana-5503	82	8	rgb	rgb	PROPN
cana-5503	82	9	segmentation	segmentation	NOUN
cana-5503	82	10	first	first	ADV
cana-5503	82	11	and	and	CCONJ
cana-5503	82	12	converting	convert	VERB
cana-5503	82	13	the	the	DET
cana-5503	82	14	image	image	NOUN
cana-5503	82	15	into	into	ADP
cana-5503	82	16	grey	grey	ADJ
cana-5503	82	17	scale	scale	NOUN
cana-5503	82	18	.	.	PUNCT
cana-5503	83	1	the	the	DET
cana-5503	83	2	images	image	NOUN
cana-5503	83	3	are	be	AUX
cana-5503	83	4	processed	process	VERB
cana-5503	83	5	by	by	ADP
cana-5503	83	6	the	the	DET
cana-5503	83	7	morphological	morphological	ADJ
cana-5503	83	8	operations	operation	NOUN
cana-5503	83	9	to	to	PART
cana-5503	83	10	isolate	isolate	VERB
cana-5503	83	11	the	the	DET
cana-5503	83	12	features	feature	NOUN
cana-5503	83	13	by	by	ADP
cana-5503	83	14	which	which	PRON
cana-5503	83	15	our	our	PRON
cana-5503	83	16	proposed	propose	VERB
cana-5503	83	17	methodology	methodology	NOUN
cana-5503	83	18	will	will	AUX
cana-5503	83	19	segment	segment	VERB
cana-5503	83	20	the	the	DET
cana-5503	83	21	retinal	retinal	ADJ
cana-5503	83	22	blood	blood	NOUN
cana-5503	83	23	vessels	vessel	NOUN
cana-5503	83	24	precisely	precisely	ADV
cana-5503	83	25	.	.	PUNCT
cana-5503	84	1	the	the	DET
cana-5503	84	2	clustering	clustering	NOUN
cana-5503	84	3	based	base	VERB
cana-5503	84	4	on	on	ADP
cana-5503	84	5	distance	distance	NOUN
cana-5503	84	6	is	be	AUX
cana-5503	84	7	employed	employ	VERB
cana-5503	84	8	to	to	PART
cana-5503	84	9	categorize	categorize	VERB
cana-5503	84	10	the	the	DET
cana-5503	84	11	pixels	pixel	NOUN
cana-5503	84	12	based	base	VERB
cana-5503	84	13	on	on	ADP
cana-5503	84	14	the	the	DET
cana-5503	84	15	location	location	NOUN
cana-5503	84	16	,	,	PUNCT
cana-5503	84	17	area	area	NOUN
cana-5503	84	18	and	and	CCONJ
cana-5503	84	19	intensity	intensity	NOUN
cana-5503	84	20	to	to	PART
cana-5503	84	21	assign	assign	VERB
cana-5503	84	22	each	each	DET
cana-5503	84	23	pixel	pixel	NOUN
cana-5503	84	24	to	to	ADP
cana-5503	84	25	the	the	DET
cana-5503	84	26	proper	proper	ADJ
cana-5503	84	27	cluster	cluster	NOUN
cana-5503	84	28	.	.	PUNCT
cana-5503	85	1	the	the	DET
cana-5503	85	2	proposed	propose	VERB
cana-5503	85	3	methodology	methodology	NOUN
cana-5503	85	4	has	have	AUX
cana-5503	85	5	demonstrated	demonstrate	VERB
cana-5503	85	6	the	the	DET
cana-5503	85	7	precision	precision	NOUN
cana-5503	85	8	of	of	ADP
cana-5503	85	9	greater	great	ADJ
cana-5503	85	10	than	than	ADP
cana-5503	85	11	98	98	NUM
cana-5503	85	12	%	%	NOUN
cana-5503	85	13	and	and	CCONJ
cana-5503	85	14	the	the	DET
cana-5503	85	15	images	image	NOUN
cana-5503	85	16	are	be	AUX
cana-5503	85	17	improved	improve	VERB
cana-5503	85	18	as	as	ADP
cana-5503	85	19	the	the	DET
cana-5503	85	20	psnr	psnr	NOUN
cana-5503	85	21	value	value	NOUN
cana-5503	85	22	greater	great	ADJ
cana-5503	85	23	than	than	ADP
cana-5503	85	24	50	50	NUM
cana-5503	85	25	.	.	PUNCT
cana-5503	86	1	the	the	DET
cana-5503	86	2	proposed	propose	VERB
cana-5503	86	3	methodology	methodology	NOUN
cana-5503	86	4	is	be	AUX
cana-5503	86	5	effective	effective	ADJ
cana-5503	86	6	in	in	ADP
cana-5503	86	7	comparison	comparison	NOUN
cana-5503	86	8	to	to	ADP
cana-5503	86	9	several	several	ADJ
cana-5503	86	10	available	available	ADJ
cana-5503	86	11	algorithms	algorithm	NOUN
cana-5503	86	12	.	.	PUNCT
cana-5503	87	1	the	the	DET
cana-5503	87	2	authors	author	NOUN
cana-5503	87	3	can	can	AUX
cana-5503	87	4	categorize	categorize	VERB
cana-5503	87	5	the	the	DET
cana-5503	87	6	images	image	NOUN
cana-5503	87	7	based	base	VERB
cana-5503	87	8	on	on	ADP
cana-5503	87	9	the	the	DET
cana-5503	87	10	segmented	segment	VERB
cana-5503	87	11	retinal	retinal	ADJ
cana-5503	87	12	blood	blood	NOUN
cana-5503	87	13	vessels	vessel	NOUN
cana-5503	87	14	images	image	NOUN
cana-5503	87	15	in	in	ADP
cana-5503	87	16	the	the	DET
cana-5503	87	17	future	future	NOUN
cana-5503	87	18	.	.	PUNCT
cana-5503	88	1	references	reference	NOUN
cana-5503	88	2	[	[	X
cana-5503	88	3	1	1	NUM
cana-5503	88	4	]	]	X
cana-5503	88	5	zhou	zhou	X
cana-5503	88	6	,	,	PUNCT
cana-5503	88	7	y.	y.	PROPN
cana-5503	88	8	,	,	PUNCT
cana-5503	88	9	chia	chia	PROPN
cana-5503	88	10	,	,	PUNCT
cana-5503	88	11	m.a	m.a	PROPN
cana-5503	88	12	.	.	PROPN
cana-5503	88	13	,	,	PUNCT
cana-5503	88	14	wagner	wagner	PROPN
cana-5503	88	15	,	,	PUNCT
cana-5503	88	16	s.k	s.k	PROPN
cana-5503	88	17	.	.	PROPN
cana-5503	88	18	et	et	PROPN
cana-5503	88	19	al	al	PROPN
cana-5503	88	20	.	.	PUNCT
cana-5503	89	1	a	a	DET
cana-5503	89	2	foundation	foundation	NOUN
cana-5503	89	3	model	model	NOUN
cana-5503	89	4	for	for	ADP
cana-5503	89	5	generalizable	generalizable	ADJ
cana-5503	89	6	disease	disease	NOUN
cana-5503	89	7	detection	detection	NOUN
cana-5503	89	8	from	from	ADP
cana-5503	89	9	retinal	retinal	ADJ
cana-5503	89	10	images	image	NOUN
cana-5503	89	11	.	.	PUNCT
cana-5503	90	1	nature	nature	NOUN
cana-5503	90	2	622	622	NUM
cana-5503	90	3	,	,	PUNCT
cana-5503	90	4	156–163	156–163	NUM
cana-5503	90	5	(	(	PUNCT
cana-5503	90	6	2023	2023	NUM
cana-5503	90	7	)	)	PUNCT
cana-5503	90	8	.	.	PUNCT
cana-5503	91	1	https://doi.org/10.1038/s41586023-06555-x	https://doi.org/10.1038/s41586023-06555-x	PROPN
cana-5503	91	2	.	.	PUNCT
cana-5503	92	1	[	[	X
cana-5503	92	2	2	2	NUM
cana-5503	92	3	]	]	PUNCT
cana-5503	92	4	m.	m.	NOUN
cana-5503	92	5	m.	m.	PROPN
cana-5503	92	6	abdelsalam	abdelsalam	PROPN
cana-5503	92	7	,	,	PUNCT
cana-5503	92	8	“	"	PUNCT
cana-5503	92	9	effective	effective	ADJ
cana-5503	92	10	blood	blood	NOUN
cana-5503	92	11	vessels	vessel	NOUN
cana-5503	92	12	reconstruction	reconstruction	NOUN
cana-5503	92	13	methodology	methodology	NOUN
cana-5503	92	14	for	for	ADP
cana-5503	92	15	early	early	ADJ
cana-5503	92	16	detection	detection	NOUN
cana-5503	92	17	and	and	CCONJ
cana-5503	92	18	classification	classification	NOUN
cana-5503	92	19	of	of	ADP
cana-5503	92	20	diabetic	diabetic	ADJ
cana-5503	92	21	retinopathy	retinopathy	NOUN
cana-5503	92	22	using	use	VERB
cana-5503	92	23	octa	octa	NOUN
cana-5503	92	24	images	image	NOUN
cana-5503	92	25	by	by	ADP
cana-5503	92	26	artificial	artificial	ADJ
cana-5503	92	27	neural	neural	ADJ
cana-5503	92	28	network	network	NOUN
cana-5503	92	29	,	,	PUNCT
cana-5503	92	30	”	"	PUNCT
cana-5503	92	31	informatics	informatic	NOUN
cana-5503	92	32	med	me	VERB
cana-5503	92	33	.	.	PUNCT
cana-5503	93	1	unlocked	unlock	VERB
cana-5503	93	2	,	,	PUNCT
cana-5503	93	3	vol	vol	NOUN
cana-5503	93	4	.	.	PROPN
cana-5503	93	5	20	20	NUM
cana-5503	93	6	,	,	PUNCT
cana-5503	93	7	p.	p.	NOUN
cana-5503	93	8	100390	100390	NUM
cana-5503	93	9	,	,	PUNCT
cana-5503	93	10	2020	2020	NUM
cana-5503	93	11	.	.	PUNCT
cana-5503	94	1	[	[	X
cana-5503	94	2	3	3	NUM
cana-5503	94	3	]	]	X
cana-5503	94	4	n.	n.	PROPN
cana-5503	94	5	e.	e.	PROPN
cana-5503	94	6	m.	m.	PROPN
cana-5503	94	7	khalifa	khalifa	PROPN
cana-5503	94	8	,	,	PUNCT
cana-5503	94	9	m.	m.	PROPN
cana-5503	94	10	loey	loey	PROPN
cana-5503	94	11	,	,	PUNCT
cana-5503	94	12	m.	m.	PROPN
cana-5503	94	13	h.	h.	PROPN
cana-5503	94	14	n.	n.	PROPN
cana-5503	94	15	taha	taha	PROPN
cana-5503	94	16	,	,	PUNCT
cana-5503	94	17	and	and	CCONJ
cana-5503	94	18	h.	h.	PROPN
cana-5503	94	19	n.	n.	PROPN
cana-5503	94	20	e.	e.	PROPN
cana-5503	94	21	t.	t.	PROPN
cana-5503	94	22	mohamed	mohamed	PROPN
cana-5503	94	23	,	,	PUNCT
cana-5503	94	24	“	"	PUNCT
cana-5503	94	25	deep	deep	ADJ
cana-5503	94	26	transfer	transfer	NOUN
cana-5503	94	27	learning	learning	NOUN
cana-5503	94	28	models	model	NOUN
cana-5503	94	29	for	for	ADP
cana-5503	94	30	medical	medical	ADJ
cana-5503	94	31	diabetic	diabetic	ADJ
cana-5503	94	32	retinopathy	retinopathy	ADJ
cana-5503	94	33	detection	detection	NOUN
cana-5503	94	34	,	,	PUNCT
cana-5503	94	35	”	"	PUNCT
cana-5503	94	36	acta	acta	PROPN
cana-5503	94	37	inform	inform	NOUN
cana-5503	94	38	.	.	PUNCT
cana-5503	95	1	medica	medica	ADJ
cana-5503	95	2	,	,	PUNCT
cana-5503	95	3	vol	vol	NOUN
cana-5503	95	4	.	.	PROPN
cana-5503	95	5	27	27	NUM
cana-5503	95	6	,	,	PUNCT
cana-5503	95	7	no	no	INTJ
cana-5503	95	8	.	.	NOUN
cana-5503	95	9	5	5	NUM
cana-5503	95	10	,	,	PUNCT
cana-5503	95	11	pp	pp	ADJ
cana-5503	95	12	.	.	PUNCT
cana-5503	96	1	327	327	NUM
cana-5503	96	2	–	–	PUNCT
cana-5503	96	3	332	332	NUM
cana-5503	96	4	,	,	PUNCT
cana-5503	96	5	2019	2019	NUM
cana-5503	96	6	.	.	PUNCT
cana-5503	97	1	[	[	X
cana-5503	97	2	4	4	X
cana-5503	97	3	]	]	X
cana-5503	97	4	h.	h.	PROPN
cana-5503	97	5	takahashi	takahashi	PROPN
cana-5503	97	6	,	,	PUNCT
cana-5503	97	7	h.	h.	PROPN
cana-5503	97	8	tampo	tampo	PROPN
cana-5503	97	9	,	,	PUNCT
cana-5503	97	10	y.	y.	PROPN
cana-5503	97	11	arai	arai	PROPN
cana-5503	97	12	,	,	PUNCT
cana-5503	97	13	y.	y.	PROPN
cana-5503	97	14	inoue	inoue	PROPN
cana-5503	97	15	,	,	PUNCT
cana-5503	97	16	and	and	CCONJ
cana-5503	97	17	h.	h.	PROPN
cana-5503	97	18	kawashima	kawashima	PROPN
cana-5503	97	19	,	,	PUNCT
cana-5503	97	20	“	"	PUNCT
cana-5503	97	21	applying	apply	VERB
cana-5503	97	22	artificial	artificial	ADJ
cana-5503	97	23	intelligence	intelligence	NOUN
cana-5503	97	24	to	to	PART
cana-5503	97	25	disease	disease	NOUN
cana-5503	97	26	staging	staging	NOUN
cana-5503	97	27	:	:	PUNCT
cana-5503	97	28	deep	deep	ADJ
cana-5503	97	29	learning	learning	NOUN
cana-5503	97	30	for	for	ADP
cana-5503	97	31	improved	improved	ADJ
cana-5503	97	32	staging	staging	NOUN
cana-5503	97	33	of	of	ADP
cana-5503	97	34	diabetic	diabetic	ADJ
cana-5503	97	35	retinopathy	retinopathy	NOUN
cana-5503	97	36	,	,	PUNCT
cana-5503	97	37	”	"	PUNCT
cana-5503	97	38	plos	plos	PROPN
cana-5503	97	39	one	one	NUM
cana-5503	97	40	,	,	PUNCT
cana-5503	97	41	vol	vol	NOUN
cana-5503	97	42	.	.	PROPN
cana-5503	97	43	12	12	NUM
cana-5503	97	44	,	,	PUNCT
cana-5503	97	45	no	no	INTJ
cana-5503	97	46	.	.	NOUN
cana-5503	97	47	6	6	NUM
cana-5503	97	48	,	,	PUNCT
cana-5503	97	49	pp	pp	ADJ
cana-5503	97	50	.	.	PUNCT
cana-5503	98	1	1–11	1–11	PROPN
cana-5503	98	2	,	,	PUNCT
cana-5503	98	3	2017	2017	NUM
cana-5503	98	4	.	.	PUNCT
cana-5503	99	1	[	[	X
cana-5503	99	2	5	5	X
cana-5503	99	3	]	]	PUNCT
cana-5503	99	4	k.	k.	PROPN
cana-5503	99	5	xu	xu	PROPN
cana-5503	99	6	,	,	PUNCT
cana-5503	99	7	d.	d.	PROPN
cana-5503	99	8	feng	feng	PROPN
cana-5503	99	9	,	,	PUNCT
cana-5503	99	10	and	and	CCONJ
cana-5503	99	11	h.	h.	PROPN
cana-5503	99	12	mi	mi	PROPN
cana-5503	99	13	,	,	PUNCT
cana-5503	99	14	“	"	PUNCT
cana-5503	99	15	deep	deep	ADJ
cana-5503	99	16	convolutional	convolutional	ADJ
cana-5503	99	17	neural	neural	ADJ
cana-5503	99	18	network	network	NOUN
cana-5503	99	19	-	-	PUNCT
cana-5503	99	20	based	base	VERB
cana-5503	99	21	early	early	ADJ
cana-5503	99	22	automated	automate	VERB
cana-5503	99	23	detection	detection	NOUN
cana-5503	99	24	of	of	ADP
cana-5503	99	25	diabetic	diabetic	ADJ
cana-5503	99	26	retinopathy	retinopathy	NOUN
cana-5503	99	27	using	use	VERB
cana-5503	99	28	fundus	fundus	NOUN
cana-5503	99	29	image	image	NOUN
cana-5503	99	30	,	,	PUNCT
cana-5503	99	31	”	"	PUNCT
cana-5503	99	32	molecules	molecule	NOUN
cana-5503	99	33	,	,	PUNCT
cana-5503	99	34	vol	vol	NOUN
cana-5503	99	35	.	.	PROPN
cana-5503	99	36	22	22	NUM
cana-5503	99	37	,	,	PUNCT
cana-5503	99	38	no	no	INTJ
cana-5503	99	39	.	.	NOUN
cana-5503	99	40	12	12	NUM
cana-5503	99	41	,	,	PUNCT
cana-5503	99	42	2017	2017	NUM
cana-5503	99	43	.	.	PUNCT
cana-5503	100	1	[	[	X
cana-5503	100	2	6	6	NUM
cana-5503	100	3	]	]	PUNCT
cana-5503	100	4	s.	s.	PROPN
cana-5503	100	5	masood	masood	PROPN
cana-5503	100	6	,	,	PUNCT
cana-5503	100	7	t.	t.	PROPN
cana-5503	100	8	luthra	luthra	PROPN
cana-5503	100	9	,	,	PUNCT
cana-5503	100	10	h.	h.	PROPN
cana-5503	100	11	sundriyal	sundriyal	PROPN
cana-5503	100	12	,	,	PUNCT
cana-5503	100	13	and	and	CCONJ
cana-5503	100	14	m.	m.	NOUN
cana-5503	100	15	ahmed	ahmed	PROPN
cana-5503	100	16	,	,	PUNCT
cana-5503	100	17	“	"	PUNCT
cana-5503	100	18	identification	identification	NOUN
cana-5503	100	19	of	of	ADP
cana-5503	100	20	diabetic	diabetic	ADJ
cana-5503	100	21	retinopathy	retinopathy	NOUN
cana-5503	100	22	in	in	ADP
cana-5503	100	23	eye	eye	NOUN
cana-5503	100	24	images	image	NOUN
cana-5503	100	25	using	use	VERB
cana-5503	100	26	transfer	transfer	NOUN
cana-5503	100	27	learning	learning	NOUN
cana-5503	100	28	,	,	PUNCT
cana-5503	100	29	”	"	PUNCT
cana-5503	100	30	proceeding	proceed	VERB
cana-5503	100	31	ieee	ieee	NOUN
cana-5503	100	32	int	int	PROPN
cana-5503	100	33	.	.	PUNCT
cana-5503	100	34	conf	conf	PROPN
cana-5503	100	35	.	.	PUNCT
cana-5503	101	1	comput	comput	NOUN
cana-5503	101	2	.	.	PUNCT
cana-5503	102	1	commun	commun	PROPN
cana-5503	102	2	.	.	PUNCT
cana-5503	103	1	autom	autom	PROPN
cana-5503	103	2	.	.	PUNCT
cana-5503	104	1	iccca	iccca	PROPN
cana-5503	104	2	2017	2017	NUM
cana-5503	104	3	,	,	PUNCT
cana-5503	104	4	vol	vol	NOUN
cana-5503	104	5	.	.	NOUN
cana-5503	104	6	2017	2017	NUM
cana-5503	104	7	-	-	PUNCT
cana-5503	104	8	janua	janua	NOUN
cana-5503	104	9	,	,	PUNCT
cana-5503	104	10	no	no	INTJ
cana-5503	104	11	.	.	PUNCT
cana-5503	105	1	may	may	AUX
cana-5503	105	2	2017	2017	NUM
cana-5503	105	3	,	,	PUNCT
cana-5503	105	4	pp	pp	ADJ
cana-5503	105	5	.	.	PUNCT
cana-5503	106	1	1183–1187	1183–1187	NUM
cana-5503	106	2	,	,	PUNCT
cana-5503	106	3	2017	2017	NUM
cana-5503	106	4	.	.	PUNCT
cana-5503	107	1	[	[	X
cana-5503	107	2	7	7	X
cana-5503	107	3	]	]	X
cana-5503	107	4	h.	h.	PROPN
cana-5503	107	5	pratt	pratt	PROPN
cana-5503	107	6	,	,	PUNCT
cana-5503	107	7	f.	f.	PROPN
cana-5503	107	8	coenen	coenen	PROPN
cana-5503	107	9	,	,	PUNCT
cana-5503	107	10	d.	d.	PROPN
cana-5503	107	11	m.	m.	PROPN
cana-5503	107	12	broadbent	broadbent	PROPN
cana-5503	107	13	,	,	PUNCT
cana-5503	107	14	s.	s.	PROPN
cana-5503	107	15	p.	p.	PROPN
cana-5503	107	16	harding	harding	PROPN
cana-5503	107	17	,	,	PUNCT
cana-5503	107	18	and	and	CCONJ
cana-5503	107	19	y.	y.	PROPN
cana-5503	107	20	zheng	zheng	PROPN
cana-5503	107	21	,	,	PUNCT
cana-5503	107	22	“	"	PUNCT
cana-5503	107	23	convolutional	convolutional	ADJ
cana-5503	107	24	neural	neural	ADJ
cana-5503	107	25	networks	network	NOUN
cana-5503	107	26	for	for	ADP
cana-5503	107	27	diabetic	diabetic	ADJ
cana-5503	107	28	retinopathy	retinopathy	NOUN
cana-5503	107	29	,	,	PUNCT
cana-5503	107	30	”	"	PUNCT
cana-5503	107	31	procedia	procedia	NOUN
cana-5503	107	32	comput	comput	NOUN
cana-5503	107	33	.	.	PUNCT
cana-5503	108	1	sci	sci	PROPN
cana-5503	108	2	.	.	PROPN
cana-5503	108	3	,	,	PUNCT
cana-5503	108	4	vol	vol	NOUN
cana-5503	108	5	.	.	PROPN
cana-5503	108	6	90	90	NUM
cana-5503	108	7	,	,	PUNCT
cana-5503	108	8	no	no	INTJ
cana-5503	108	9	.	.	PUNCT
cana-5503	109	1	july	july	PROPN
cana-5503	109	2	,	,	PUNCT
cana-5503	109	3	pp	pp	ADP
cana-5503	109	4	.	.	PUNCT
cana-5503	110	1	200–205	200–205	NUM
cana-5503	110	2	,	,	PUNCT
cana-5503	110	3	communications	communication	NOUN
cana-5503	110	4	on	on	ADP
cana-5503	110	5	applied	apply	VERB
cana-5503	110	6	nonlinear	nonlinear	ADJ
cana-5503	110	7	analysis	analysis	NOUN
cana-5503	110	8	issn	issn	NOUN
cana-5503	110	9	:	:	PUNCT
cana-5503	110	10	1074	1074	NUM
cana-5503	110	11	-	-	PUNCT
cana-5503	110	12	133x	133x	NUM
cana-5503	110	13	vol	vol	VERB
cana-5503	110	14	32	32	NUM
cana-5503	110	15	no	no	NOUN
cana-5503	110	16	.	.	PUNCT
cana-5503	111	1	10s	10	NOUN
cana-5503	111	2	(	(	PUNCT
cana-5503	111	3	2025	2025	NUM
cana-5503	111	4	)	)	PUNCT
cana-5503	111	5	2537	2537	NUM
cana-5503	111	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5503	111	7	2016	2016	NUM
cana-5503	111	8	.	.	PUNCT
cana-5503	112	1	[	[	X
cana-5503	112	2	8	8	NUM
cana-5503	112	3	]	]	X
cana-5503	112	4	g.	g.	PROPN
cana-5503	112	5	a.	a.	PROPN
cana-5503	112	6	carrijo	carrijo	PROPN
cana-5503	112	7	,	,	PUNCT
cana-5503	112	8	c.	c.	PROPN
cana-5503	112	9	de	de	PROPN
cana-5503	112	10	fátima	fátima	PROPN
cana-5503	112	11	dos	dos	PROPN
cana-5503	112	12	santos	santos	PROPN
cana-5503	112	13	cardoso	cardoso	PROPN
cana-5503	112	14	,	,	PUNCT
cana-5503	112	15	j.	j.	PROPN
cana-5503	112	16	c.	c.	PROPN
cana-5503	112	17	ferreira	ferreira	PROPN
cana-5503	112	18	,	,	PUNCT
cana-5503	112	19	p.	p.	PROPN
cana-5503	112	20	m.	m.	PROPN
cana-5503	112	21	sousa	sousa	PROPN
cana-5503	112	22	,	,	PUNCT
cana-5503	112	23	and	and	CCONJ
cana-5503	112	24	a.	a.	PROPN
cana-5503	112	25	c.	c.	PROPN
cana-5503	112	26	patrocínio	patrocínio	PROPN
cana-5503	112	27	,	,	PUNCT
cana-5503	112	28	“	"	PUNCT
cana-5503	112	29	image	image	NOUN
cana-5503	112	30	enhancement	enhancement	NOUN
cana-5503	112	31	for	for	ADP
cana-5503	112	32	blood	blood	NOUN
cana-5503	112	33	vessel	vessel	NOUN
cana-5503	112	34	detection	detection	NOUN
cana-5503	112	35	via	via	ADP
cana-5503	112	36	a	a	DET
cana-5503	112	37	neural	neural	ADJ
cana-5503	112	38	network	network	NOUN
cana-5503	112	39	using	use	VERB
cana-5503	112	40	clahe	clahe	PROPN
cana-5503	112	41	and	and	CCONJ
cana-5503	112	42	wiener	wiener	NOUN
cana-5503	112	43	filter	filter	NOUN
cana-5503	112	44	,	,	PUNCT
cana-5503	112	45	”	"	PUNCT
cana-5503	112	46	ieee	ieee	NOUN
cana-5503	112	47	res	re	NOUN
cana-5503	112	48	.	.	PROPN
cana-5503	112	49	biomed	biome	VERB
cana-5503	112	50	.	.	PUNCT
cana-5503	113	1	eng	eng	PROPN
cana-5503	113	2	.	.	PROPN
cana-5503	113	3	,	,	PUNCT
cana-5503	113	4	vol	vol	NOUN
cana-5503	113	5	.	.	PROPN
cana-5503	114	1	36	36	NUM
cana-5503	114	2	,	,	PUNCT
cana-5503	114	3	no	no	INTJ
cana-5503	114	4	.	.	NOUN
cana-5503	114	5	2	2	NUM
cana-5503	114	6	,	,	PUNCT
cana-5503	114	7	pp	pp	ADJ
cana-5503	114	8	.	.	PUNCT
cana-5503	115	1	107–119	107–119	NUM
cana-5503	115	2	,	,	PUNCT
cana-5503	115	3	2020	2020	NUM
cana-5503	115	4	.	.	PUNCT
cana-5503	116	1	[	[	X
cana-5503	116	2	9	9	NUM
cana-5503	116	3	]	]	X
cana-5503	116	4	r.	r.	PROPN
cana-5503	116	5	agarwal	agarwal	PROPN
cana-5503	116	6	,	,	PUNCT
cana-5503	116	7	a.	a.	NOUN
cana-5503	116	8	mahamuni	mahamuni	PROPN
cana-5503	116	9	,	,	PUNCT
cana-5503	116	10	n.	n.	PROPN
cana-5503	116	11	gautam	gautam	PROPN
cana-5503	116	12	,	,	PUNCT
cana-5503	116	13	p.	p.	NOUN
cana-5503	116	14	awachar	awachar	PROPN
cana-5503	116	15	,	,	PUNCT
cana-5503	116	16	and	and	CCONJ
cana-5503	116	17	p.	p.	PROPN
cana-5503	116	18	sagar	sagar	NOUN
cana-5503	116	19	,	,	PUNCT
cana-5503	116	20	“	"	PUNCT
cana-5503	116	21	detection	detection	NOUN
cana-5503	116	22	of	of	ADP
cana-5503	116	23	diabetic	diabetic	ADJ
cana-5503	116	24	retinopathy	retinopathy	NOUN
cana-5503	116	25	using	use	VERB
cana-5503	116	26	convolutional	convolutional	ADJ
cana-5503	116	27	neural	neural	ADJ
cana-5503	116	28	network	network	NOUN
cana-5503	116	29	,	,	PUNCT
cana-5503	116	30	”	"	PUNCT
cana-5503	116	31	int	int	NOUN
cana-5503	116	32	.	.	PUNCT
cana-5503	117	1	j.	j.	PROPN
cana-5503	117	2	recent	recent	ADJ
cana-5503	117	3	technol	technol	PROPN
cana-5503	117	4	.	.	PUNCT
cana-5503	118	1	eng	eng	PROPN
cana-5503	118	2	.	.	PROPN
cana-5503	118	3	,	,	PUNCT
cana-5503	118	4	vol	vol	NOUN
cana-5503	118	5	.	.	PROPN
cana-5503	118	6	8	8	NUM
cana-5503	118	7	,	,	PUNCT
cana-5503	118	8	no	no	INTJ
cana-5503	118	9	.	.	NOUN
cana-5503	118	10	4	4	NUM
cana-5503	118	11	,	,	PUNCT
cana-5503	118	12	pp	pp	ADJ
cana-5503	118	13	.	.	PUNCT
cana-5503	119	1	1957–1960	1957–1960	NUM
cana-5503	119	2	,	,	PUNCT
cana-5503	119	3	2019	2019	NUM
cana-5503	119	4	.	.	PUNCT
cana-5503	120	1	[	[	X
cana-5503	120	2	10	10	NUM
cana-5503	120	3	]	]	PUNCT
cana-5503	120	4	k.	k.	PROPN
cana-5503	121	1	kipli	kipli	PROPN
cana-5503	121	2	et	et	PROPN
cana-5503	121	3	al	al	PROPN
cana-5503	121	4	.	.	PROPN
cana-5503	121	5	,	,	PUNCT
cana-5503	121	6	“	"	PUNCT
cana-5503	121	7	morphological	morphological	ADJ
cana-5503	121	8	and	and	CCONJ
cana-5503	121	9	otsu	otsu	NOUN
cana-5503	121	10	’s	’s	PART
cana-5503	121	11	thresholding	thresholding	NOUN
cana-5503	121	12	-	-	PUNCT
cana-5503	121	13	based	base	VERB
cana-5503	121	14	retinal	retinal	ADJ
cana-5503	121	15	blood	blood	NOUN
cana-5503	121	16	vessel	vessel	NOUN
cana-5503	121	17	segmentation	segmentation	NOUN
cana-5503	121	18	for	for	ADP
cana-5503	121	19	detection	detection	NOUN
cana-5503	121	20	of	of	ADP
cana-5503	121	21	retinopathy	retinopathy	ADJ
cana-5503	121	22	,	,	PUNCT
cana-5503	121	23	”	"	PUNCT
cana-5503	121	24	int	int	NOUN
cana-5503	121	25	.	.	PUNCT
cana-5503	122	1	j.	j.	PROPN
cana-5503	122	2	eng	eng	PROPN
cana-5503	122	3	.	.	PROPN
cana-5503	123	1	technol	technol	PROPN
cana-5503	123	2	.	.	PROPN
cana-5503	123	3	,	,	PUNCT
cana-5503	123	4	vol	vol	NOUN
cana-5503	123	5	.	.	PROPN
cana-5503	124	1	7	7	NUM
cana-5503	124	2	,	,	PUNCT
cana-5503	124	3	no	no	INTJ
cana-5503	124	4	.	.	NOUN
cana-5503	124	5	3	3	NUM
cana-5503	124	6	,	,	PUNCT
cana-5503	124	7	pp	pp	ADJ
cana-5503	124	8	.	.	PUNCT
cana-5503	125	1	16–20	16–20	NUM
cana-5503	125	2	,	,	PUNCT
cana-5503	125	3	2018	2018	NUM
cana-5503	125	4	.	.	PUNCT
cana-5503	126	1	[	[	X
cana-5503	126	2	11	11	NUM
cana-5503	126	3	]	]	X
cana-5503	126	4	u.	u.	PROPN
cana-5503	126	5	k.	k.	PROPN
cana-5503	126	6	lopes	lopes	PROPN
cana-5503	126	7	and	and	CCONJ
cana-5503	126	8	j.	j.	PROPN
cana-5503	126	9	f.	f.	PROPN
cana-5503	126	10	valiati	valiati	PROPN
cana-5503	126	11	,	,	PUNCT
cana-5503	126	12	“	"	PUNCT
cana-5503	126	13	pre	pre	ADJ
cana-5503	126	14	-	-	ADJ
cana-5503	126	15	trained	train	VERB
cana-5503	126	16	convolutional	convolutional	ADJ
cana-5503	126	17	neural	neural	ADJ
cana-5503	126	18	networks	network	NOUN
cana-5503	126	19	as	as	ADP
cana-5503	126	20	feature	feature	NOUN
cana-5503	126	21	extractors	extractor	NOUN
cana-5503	126	22	for	for	ADP
cana-5503	126	23	tuberculosis	tuberculosis	NOUN
cana-5503	126	24	detection	detection	NOUN
cana-5503	126	25	,	,	PUNCT
cana-5503	126	26	”	"	PUNCT
cana-5503	126	27	comput	comput	NOUN
cana-5503	126	28	.	.	PUNCT
cana-5503	127	1	biol	biol	PROPN
cana-5503	127	2	.	.	PUNCT
cana-5503	128	1	med	med	PROPN
cana-5503	128	2	.	.	PROPN
cana-5503	128	3	,	,	PUNCT
cana-5503	128	4	vol	vol	NOUN
cana-5503	128	5	.	.	PROPN
cana-5503	128	6	89	89	NUM
cana-5503	128	7	,	,	PUNCT
cana-5503	128	8	no	no	INTJ
cana-5503	128	9	.	.	PUNCT
cana-5503	129	1	august	august	PROPN
cana-5503	129	2	,	,	PUNCT
cana-5503	129	3	pp	pp	ADP
cana-5503	129	4	.	.	PUNCT
cana-5503	130	1	135–143	135–143	NUM
cana-5503	130	2	,	,	PUNCT
cana-5503	130	3	2017	2017	NUM
cana-5503	130	4	.	.	PUNCT
cana-5503	131	1	[	[	X
cana-5503	131	2	12	12	NUM
cana-5503	131	3	]	]	X
cana-5503	131	4	c.	c.	PROPN
cana-5503	131	5	x	x	PROPN
cana-5503	131	6	-	-	PUNCT
cana-5503	131	7	ray	ray	NOUN
cana-5503	131	8	,	,	PUNCT
cana-5503	131	9	t.	t.	PROPN
cana-5503	131	10	rahman	rahman	PROPN
cana-5503	131	11	,	,	PUNCT
cana-5503	131	12	m.	m.	PROPN
cana-5503	131	13	e.	e.	PROPN
cana-5503	131	14	h.	h.	PROPN
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cana-5503	131	16	,	,	PUNCT
cana-5503	131	17	and	and	CCONJ
cana-5503	131	18	a.	a.	NOUN
cana-5503	131	19	khandakar	khandakar	NOUN
cana-5503	131	20	,	,	PUNCT
cana-5503	131	21	“	"	PUNCT
cana-5503	131	22	transfer	transfer	NOUN
cana-5503	131	23	learning	learning	NOUN
cana-5503	131	24	with	with	ADP
cana-5503	131	25	deep	deep	ADJ
cana-5503	131	26	convolutional	convolutional	ADJ
cana-5503	131	27	neural	neural	ADJ
cana-5503	131	28	network	network	NOUN
cana-5503	131	29	(	(	PUNCT
cana-5503	131	30	cnn	cnn	PROPN
cana-5503	131	31	)	)	PUNCT
cana-5503	131	32	for	for	ADP
cana-5503	131	33	pneumonia	pneumonia	NOUN
cana-5503	131	34	detection	detection	NOUN
cana-5503	131	35	using	use	VERB
cana-5503	131	36	chest	chest	NOUN
cana-5503	131	37	x	x	NOUN
cana-5503	131	38	-	-	NOUN
cana-5503	131	39	ray	ray	NOUN
cana-5503	131	40	,	,	PUNCT
cana-5503	131	41	”	"	PUNCT
cana-5503	131	42	mdpi	mdpi	PROPN
cana-5503	131	43	appl	appl	PROPN
cana-5503	131	44	.	.	PUNCT
cana-5503	132	1	sci	sci	PROPN
cana-5503	132	2	.	.	PROPN
cana-5503	132	3	,	,	PUNCT
cana-5503	132	4	vol	vol	NOUN
cana-5503	132	5	.	.	PUNCT
cana-5503	133	1	may	may	AUX
cana-5503	133	2	,	,	PUNCT
cana-5503	133	3	no	no	INTJ
cana-5503	133	4	.	.	NOUN
cana-5503	133	5	10	10	NUM
cana-5503	133	6	,	,	PUNCT
cana-5503	133	7	2020	2020	NUM
cana-5503	133	8	.	.	PUNCT
cana-5503	134	1	[	[	X
cana-5503	134	2	13	13	NUM
cana-5503	134	3	]	]	X
cana-5503	134	4	erwin	erwin	PROPN
cana-5503	134	5	and	and	CCONJ
cana-5503	134	6	d.	d.	PROPN
cana-5503	134	7	r.	r.	PROPN
cana-5503	134	8	ningsih	ningsih	PROPN
cana-5503	134	9	,	,	PUNCT
cana-5503	134	10	“	"	PUNCT
cana-5503	134	11	improving	improve	VERB
cana-5503	134	12	retinal	retinal	ADJ
cana-5503	134	13	image	image	NOUN
cana-5503	134	14	quality	quality	NOUN
cana-5503	134	15	using	use	VERB
cana-5503	134	16	the	the	DET
cana-5503	134	17	contrast	contrast	NOUN
cana-5503	134	18	stretching	stretching	NOUN
cana-5503	134	19	,	,	PUNCT
cana-5503	134	20	histogram	histogram	NOUN
cana-5503	134	21	equalization	equalization	NOUN
cana-5503	134	22	,	,	PUNCT
cana-5503	134	23	and	and	CCONJ
cana-5503	134	24	clahe	clahe	NOUN
cana-5503	134	25	methods	method	NOUN
cana-5503	134	26	with	with	ADP
cana-5503	134	27	median	median	ADJ
cana-5503	134	28	filters	filter	NOUN
cana-5503	134	29	,	,	PUNCT
cana-5503	134	30	”	"	PUNCT
cana-5503	134	31	i.j	i.j	PROPN
cana-5503	134	32	.	.	PROPN
cana-5503	134	33	image	image	NOUN
cana-5503	134	34	,	,	PUNCT
cana-5503	134	35	graph	graph	NOUN
cana-5503	134	36	.	.	PUNCT
cana-5503	134	37	signal	signal	NOUN
cana-5503	134	38	process	process	NOUN
cana-5503	134	39	.	.	PUNCT
cana-5503	134	40	,	,	PUNCT
cana-5503	134	41	vol	vol	NOUN
cana-5503	134	42	.	.	PROPN
cana-5503	134	43	2	2	NUM
cana-5503	134	44	,	,	PUNCT
cana-5503	134	45	no	no	INTJ
cana-5503	134	46	.	.	PUNCT
cana-5503	135	1	april	april	PROPN
cana-5503	135	2	,	,	PUNCT
cana-5503	135	3	pp	pp	X
cana-5503	135	4	.	.	PUNCT
cana-5503	136	1	30–41	30–41	NUM
cana-5503	136	2	,	,	PUNCT
cana-5503	136	3	2020	2020	NUM
cana-5503	136	4	.	.	PUNCT
cana-5503	137	1	[	[	X
cana-5503	137	2	14	14	NUM
cana-5503	137	3	]	]	X
cana-5503	137	4	i.	i.	PROPN
cana-5503	137	5	qureshi	qureshi	PROPN
cana-5503	137	6	,	,	PUNCT
cana-5503	137	7	j.	j.	PROPN
cana-5503	137	8	ma	ma	PROPN
cana-5503	137	9	,	,	PUNCT
cana-5503	137	10	and	and	CCONJ
cana-5503	137	11	k.	k.	PROPN
cana-5503	137	12	shaheed	shaheed	PROPN
cana-5503	137	13	,	,	PUNCT
cana-5503	137	14	“	"	PUNCT
cana-5503	137	15	a	a	DET
cana-5503	137	16	hybrid	hybrid	NOUN
cana-5503	137	17	proposed	propose	VERB
cana-5503	137	18	fundus	fundus	NOUN
cana-5503	137	19	image	image	NOUN
cana-5503	137	20	enhancement	enhancement	NOUN
cana-5503	137	21	framework	framework	NOUN
cana-5503	137	22	for	for	ADP
cana-5503	137	23	diabetic	diabetic	ADJ
cana-5503	137	24	retinopathy	retinopathy	NOUN
cana-5503	137	25	,	,	PUNCT
cana-5503	137	26	”	"	PUNCT
cana-5503	137	27	mdpi	mdpi	ADJ
cana-5503	137	28	algorithms	algorithm	NOUN
cana-5503	137	29	,	,	PUNCT
cana-5503	137	30	vol	vol	NOUN
cana-5503	137	31	.	.	PROPN
cana-5503	137	32	14	14	NUM
cana-5503	137	33	,	,	PUNCT
cana-5503	137	34	no	no	INTJ
cana-5503	137	35	.	.	PUNCT
cana-5503	138	1	january	january	PROPN
cana-5503	138	2	,	,	PUNCT
cana-5503	138	3	pp	pp	X
cana-5503	138	4	.	.	PUNCT
cana-5503	139	1	1–17	1–17	NOUN
cana-5503	139	2	,	,	PUNCT
cana-5503	139	3	2019	2019	NUM
cana-5503	139	4	.	.	PUNCT
cana-5503	140	1	[	[	X
cana-5503	140	2	15	15	NUM
cana-5503	140	3	]	]	X
cana-5503	140	4	f.	f.	PROPN
cana-5503	140	5	sadikoglu	sadikoglu	PROPN
cana-5503	140	6	and	and	CCONJ
cana-5503	140	7	s.	s.	PROPN
cana-5503	140	8	uzelaltinbulat	uzelaltinbulat	PROPN
cana-5503	140	9	,	,	PUNCT
cana-5503	140	10	“	"	PUNCT
cana-5503	140	11	biometric	biometric	ADJ
cana-5503	140	12	retina	retina	NOUN
cana-5503	140	13	identification	identification	NOUN
cana-5503	140	14	based	base	VERB
cana-5503	140	15	on	on	ADP
cana-5503	140	16	neural	neural	ADJ
cana-5503	140	17	network	network	NOUN
cana-5503	140	18	,	,	PUNCT
cana-5503	140	19	”	"	PUNCT
cana-5503	140	20	procedia	procedia	NOUN
cana-5503	140	21	comput	comput	NOUN
cana-5503	140	22	.	.	PUNCT
cana-5503	141	1	sci	sci	PROPN
cana-5503	141	2	.	.	PROPN
cana-5503	141	3	,	,	PUNCT
cana-5503	141	4	vol	vol	NOUN
cana-5503	141	5	.	.	PROPN
cana-5503	142	1	102	102	NUM
cana-5503	142	2	,	,	PUNCT
cana-5503	142	3	no	no	INTJ
cana-5503	142	4	.	.	PUNCT
cana-5503	143	1	august	august	PROPN
cana-5503	143	2	,	,	PUNCT
cana-5503	143	3	pp	pp	ADJ
cana-5503	143	4	.	.	PUNCT
cana-5503	144	1	26–33	26–33	NUM
cana-5503	144	2	,	,	PUNCT
cana-5503	144	3	2016	2016	NUM
cana-5503	144	4	.	.	PUNCT
cana-5503	145	1	[	[	X
cana-5503	145	2	16	16	NUM
cana-5503	145	3	]	]	X
cana-5503	145	4	w.	w.	PROPN
cana-5503	145	5	l.	l.	PROPN
cana-5503	145	6	alyoubi	alyoubi	PROPN
cana-5503	145	7	,	,	PUNCT
cana-5503	145	8	w.	w.	PROPN
cana-5503	145	9	m.	m.	PROPN
cana-5503	145	10	shalash	shalash	PROPN
cana-5503	145	11	,	,	PUNCT
cana-5503	145	12	and	and	CCONJ
cana-5503	145	13	m.	m.	PROPN
cana-5503	145	14	f.	f.	PROPN
cana-5503	145	15	abulkhair	abulkhair	PROPN
cana-5503	145	16	,	,	PUNCT
cana-5503	145	17	“	"	PUNCT
cana-5503	145	18	diabetic	diabetic	ADJ
cana-5503	145	19	retinopathy	retinopathy	ADJ
cana-5503	145	20	detection	detection	NOUN
cana-5503	145	21	through	through	ADP
cana-5503	145	22	deep	deep	ADJ
cana-5503	145	23	learning	learning	NOUN
cana-5503	145	24	techniques	technique	NOUN
cana-5503	145	25	:	:	PUNCT
cana-5503	145	26	a	a	DET
cana-5503	145	27	review	review	NOUN
cana-5503	145	28	,	,	PUNCT
cana-5503	145	29	”	"	PUNCT
cana-5503	145	30	informatics	informatic	NOUN
cana-5503	145	31	med	me	VERB
cana-5503	145	32	.	.	PUNCT
cana-5503	146	1	unlocked	unlock	VERB
cana-5503	146	2	,	,	PUNCT
cana-5503	146	3	vol	vol	NOUN
cana-5503	146	4	.	.	PROPN
cana-5503	146	5	20	20	NUM
cana-5503	146	6	,	,	PUNCT
cana-5503	146	7	no	no	INTJ
cana-5503	146	8	.	.	PUNCT
cana-5503	146	9	june	june	PROPN
cana-5503	146	10	,	,	PUNCT
cana-5503	146	11	p.	p.	NOUN
cana-5503	146	12	100377	100377	NUM
cana-5503	146	13	,	,	PUNCT
cana-5503	146	14	2020	2020	NUM
cana-5503	146	15	.	.	PUNCT
cana-5503	147	1	[	[	X
cana-5503	147	2	17	17	NUM
cana-5503	147	3	]	]	PUNCT
cana-5503	147	4	a.	a.	NOUN
cana-5503	147	5	colomer	colomer	PROPN
cana-5503	147	6	,	,	PUNCT
cana-5503	147	7	j.	j.	PROPN
cana-5503	147	8	igual	igual	PROPN
cana-5503	147	9	,	,	PUNCT
cana-5503	147	10	and	and	CCONJ
cana-5503	147	11	v.	v.	ADP
cana-5503	147	12	naranjo	naranjo	PROPN
cana-5503	147	13	,	,	PUNCT
cana-5503	147	14	“	"	PUNCT
cana-5503	147	15	detection	detection	NOUN
cana-5503	147	16	of	of	ADP
cana-5503	147	17	early	early	ADJ
cana-5503	147	18	signs	sign	NOUN
cana-5503	147	19	of	of	ADP
cana-5503	147	20	diabetic	diabetic	ADJ
cana-5503	147	21	retinopathy	retinopathy	NOUN
cana-5503	147	22	based	base	VERB
cana-5503	147	23	on	on	ADP
cana-5503	147	24	textural	textural	ADJ
cana-5503	147	25	and	and	CCONJ
cana-5503	147	26	morphological	morphological	ADJ
cana-5503	147	27	information	information	NOUN
cana-5503	147	28	in	in	ADP
cana-5503	147	29	fundus	fundus	NOUN
cana-5503	147	30	images	image	NOUN
cana-5503	147	31	,	,	PUNCT
cana-5503	147	32	”	"	PUNCT
cana-5503	147	33	sensors	sensor	NOUN
cana-5503	147	34	(	(	PUNCT
cana-5503	147	35	switzerland	switzerland	PROPN
cana-5503	147	36	)	)	PUNCT
cana-5503	147	37	,	,	PUNCT
cana-5503	147	38	vol	vol	NOUN
cana-5503	147	39	.	.	PROPN
cana-5503	147	40	20	20	NUM
cana-5503	147	41	,	,	PUNCT
cana-5503	147	42	no	no	INTJ
cana-5503	147	43	.	.	NOUN
cana-5503	147	44	4	4	NUM
cana-5503	147	45	,	,	PUNCT
cana-5503	147	46	pp	pp	ADJ
cana-5503	147	47	.	.	PUNCT
cana-5503	148	1	1–21	1–21	NOUN
cana-5503	148	2	,	,	PUNCT
cana-5503	148	3	2020	2020	NUM
cana-5503	148	4	.	.	PUNCT
cana-5503	149	1	[	[	X
cana-5503	149	2	18	18	NUM
cana-5503	149	3	]	]	PUNCT
cana-5503	149	4	m.	m.	NOUN
cana-5503	149	5	mateen	mateen	PROPN
cana-5503	149	6	,	,	PUNCT
cana-5503	149	7	j.	j.	PROPN
cana-5503	149	8	wen	wen	PROPN
cana-5503	149	9	,	,	PUNCT
cana-5503	149	10	n.	n.	PROPN
cana-5503	149	11	nasrullah	nasrullah	PROPN
cana-5503	149	12	,	,	PUNCT
cana-5503	149	13	s.	s.	PROPN
cana-5503	149	14	sun	sun	PROPN
cana-5503	149	15	,	,	PUNCT
cana-5503	149	16	and	and	CCONJ
cana-5503	149	17	s.	s.	PROPN
cana-5503	149	18	hayat	hayat	PROPN
cana-5503	149	19	,	,	PUNCT
cana-5503	149	20	“	"	PUNCT
cana-5503	149	21	exudate	exudate	ADJ
cana-5503	149	22	detection	detection	NOUN
cana-5503	149	23	for	for	ADP
cana-5503	149	24	diabetic	diabetic	ADJ
cana-5503	149	25	retinopathy	retinopathy	NOUN
cana-5503	149	26	using	use	VERB
cana-5503	149	27	pretrained	pretraine	VERB
cana-5503	149	28	convolutional	convolutional	ADJ
cana-5503	149	29	neural	neural	ADJ
cana-5503	149	30	networks	network	NOUN
cana-5503	149	31	,	,	PUNCT
cana-5503	149	32	”	"	PUNCT
cana-5503	149	33	hindwai	hindwai	PROPN
cana-5503	149	34	complex	complex	NOUN
cana-5503	149	35	.	.	PUNCT
cana-5503	149	36	,	,	PUNCT
cana-5503	149	37	vol	vol	NOUN
cana-5503	149	38	.	.	PUNCT
cana-5503	149	39	2020	2020	NUM
cana-5503	149	40	,	,	PUNCT
cana-5503	149	41	no	no	INTJ
cana-5503	149	42	.	.	PUNCT
cana-5503	150	1	april	april	PROPN
cana-5503	150	2	,	,	PUNCT
cana-5503	150	3	pp	pp	PROPN
cana-5503	150	4	.	.	PUNCT
cana-5503	151	1	1–11	1–11	PROPN
cana-5503	151	2	,	,	PUNCT
cana-5503	151	3	2020	2020	NUM
cana-5503	151	4	.	.	PUNCT
cana-5503	152	1	[	[	X
cana-5503	152	2	19	19	NUM
cana-5503	152	3	]	]	X
cana-5503	152	4	s.	s.	PROPN
cana-5503	152	5	m.	m.	PROPN
cana-5503	152	6	s.	s.	PROPN
cana-5503	152	7	islam	islam	PROPN
cana-5503	152	8	,	,	PUNCT
cana-5503	152	9	m.	m.	PROPN
cana-5503	152	10	m.	m.	PROPN
cana-5503	152	11	hasan	hasan	PROPN
cana-5503	152	12	,	,	PUNCT
cana-5503	152	13	and	and	CCONJ
cana-5503	152	14	s.	s.	PROPN
cana-5503	152	15	abdullah	abdullah	PROPN
cana-5503	152	16	,	,	PUNCT
cana-5503	152	17	“	"	PUNCT
cana-5503	152	18	deep	deep	ADJ
cana-5503	152	19	learning	learning	NOUN
cana-5503	152	20	based	base	VERB
cana-5503	152	21	early	early	ADJ
cana-5503	152	22	detection	detection	NOUN
cana-5503	152	23	and	and	CCONJ
cana-5503	152	24	grading	grading	NOUN
cana-5503	152	25	of	of	ADP
cana-5503	152	26	diabetic	diabetic	ADJ
cana-5503	152	27	retinopathy	retinopathy	NOUN
cana-5503	152	28	using	use	VERB
cana-5503	152	29	retinal	retinal	ADJ
cana-5503	152	30	fundus	fundus	NOUN
cana-5503	152	31	images	image	NOUN
cana-5503	152	32	,	,	PUNCT
cana-5503	152	33	”	"	PUNCT
cana-5503	152	34	arxiv	arxiv	NOUN
cana-5503	152	35	,	,	PUNCT
cana-5503	152	36	vol	vol	NOUN
cana-5503	152	37	.	.	PROPN
cana-5503	152	38	23	23	NUM
cana-5503	152	39	,	,	PUNCT
cana-5503	152	40	no	no	INTJ
cana-5503	152	41	.	.	PUNCT
cana-5503	152	42	december	december	PROPN
cana-5503	152	43	,	,	PUNCT
cana-5503	152	44	pp	pp	ADP
cana-5503	152	45	.	.	PUNCT
cana-5503	153	1	1–13	1–13	NOUN
cana-5503	153	2	,	,	PUNCT
cana-5503	153	3	2018	2018	NUM
cana-5503	153	4	.	.	PUNCT
cana-5503	154	1	[	[	X
cana-5503	154	2	20	20	NUM
cana-5503	154	3	]	]	PUNCT
cana-5503	154	4	a.	a.	NOUN
cana-5503	154	5	bhupati	bhupati	NOUN
cana-5503	154	6	,	,	PUNCT
cana-5503	154	7	“	"	PUNCT
cana-5503	154	8	transfer	transfer	NOUN
cana-5503	154	9	learning	learning	NOUN
cana-5503	154	10	for	for	ADP
cana-5503	154	11	detection	detection	NOUN
cana-5503	154	12	of	of	ADP
cana-5503	154	13	diabetic	diabetic	ADJ
cana-5503	154	14	retinopathy	retinopathy	ADJ
cana-5503	154	15	disease	disease	NOUN
cana-5503	154	16	research	research	NOUN
cana-5503	154	17	project	project	NOUN
cana-5503	154	18	msc	msc	PROPN
cana-5503	154	19	data	data	PROPN
cana-5503	154	20	analytics	analytic	NOUN
cana-5503	154	21	alekhya	alekhya	VERB
cana-5503	154	22	bhupati	bhupati	ADJ
cana-5503	154	23	student	student	NOUN
cana-5503	155	1	i	i	PROPN
cana-5503	155	2	d	d	PROPN
cana-5503	155	3	 	 	SPACE
cana-5503	155	4	:	:	PUNCT
cana-5503	155	5	x18132634	x18132634	PROPN
cana-5503	155	6	school	school	NOUN
cana-5503	155	7	of	of	ADP
cana-5503	155	8	computing	compute	VERB
cana-5503	155	9	national	national	PROPN
cana-5503	155	10	college	college	PROPN
cana-5503	155	11	of	of	ADP
cana-5503	155	12	ireland	ireland	PROPN
cana-5503	155	13	supervisor	supervisor	NOUN
cana-5503	155	14	 	 	SPACE
cana-5503	155	15	:	:	PUNCT
cana-5503	156	1	dr	dr	PROPN
cana-5503	156	2	.	.	PROPN
cana-5503	157	1	catherine	catherine	PROPN
cana-5503	157	2	mulwa	mulwa	PROPN
cana-5503	157	3	,	,	PUNCT
cana-5503	157	4	”	"	PUNCT
cana-5503	157	5	no	no	INTJ
cana-5503	157	6	.	.	PUNCT
cana-5503	158	1	may	may	AUX
cana-5503	158	2	,	,	PUNCT
cana-5503	158	3	2020	2020	NUM
cana-5503	158	4	.	.	PUNCT
cana-5503	159	1	[	[	X
cana-5503	159	2	21	21	NUM
cana-5503	159	3	]	]	X
cana-5503	159	4	q.	q.	PROPN
cana-5503	159	5	jin	jin	PROPN
cana-5503	159	6	,	,	PUNCT
cana-5503	159	7	z.	z.	PROPN
cana-5503	159	8	meng	meng	PROPN
cana-5503	159	9	,	,	PUNCT
cana-5503	159	10	t.	t.	PROPN
cana-5503	159	11	d.	d.	PROPN
cana-5503	159	12	pham	pham	PROPN
cana-5503	159	13	,	,	PUNCT
cana-5503	159	14	q.	q.	PROPN
cana-5503	159	15	chen	chen	PROPN
cana-5503	159	16	,	,	PUNCT
cana-5503	159	17	l.	l.	PROPN
cana-5503	159	18	wei	wei	PROPN
cana-5503	159	19	,	,	PUNCT
cana-5503	159	20	and	and	CCONJ
cana-5503	159	21	r.	r.	PROPN
cana-5503	159	22	su	su	PROPN
cana-5503	159	23	,	,	PUNCT
cana-5503	159	24	“	"	PUNCT
cana-5503	159	25	dunet	dunet	PROPN
cana-5503	159	26	:	:	PUNCT
cana-5503	159	27	a	a	DET
cana-5503	159	28	deformable	deformable	ADJ
cana-5503	159	29	network	network	NOUN
cana-5503	159	30	for	for	ADP
cana-5503	159	31	communications	communication	NOUN
cana-5503	159	32	on	on	ADP
cana-5503	159	33	applied	apply	VERB
cana-5503	159	34	nonlinear	nonlinear	ADJ
cana-5503	159	35	analysis	analysis	NOUN
cana-5503	159	36	issn	issn	NOUN
cana-5503	159	37	:	:	PUNCT
cana-5503	159	38	1074	1074	NUM
cana-5503	159	39	-	-	PUNCT
cana-5503	159	40	133x	133x	NUM
cana-5503	159	41	vol	vol	VERB
cana-5503	159	42	32	32	NUM
cana-5503	159	43	no	no	NOUN
cana-5503	159	44	.	.	PUNCT
cana-5503	160	1	10s	10	NOUN
cana-5503	160	2	(	(	PUNCT
cana-5503	160	3	2025	2025	NUM
cana-5503	160	4	)	)	PUNCT
cana-5503	160	5	2538	2538	NUM
cana-5503	160	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5503	160	7	retinal	retinal	ADJ
cana-5503	160	8	vessel	vessel	NOUN
cana-5503	160	9	segmentation	segmentation	NOUN
cana-5503	160	10	,	,	PUNCT
cana-5503	160	11	”	"	PUNCT
cana-5503	160	12	knowledge	knowledge	NOUN
cana-5503	160	13	-	-	PUNCT
cana-5503	160	14	based	base	VERB
cana-5503	160	15	syst	syst	NOUN
cana-5503	160	16	.	.	PUNCT
cana-5503	160	17	,	,	PUNCT
cana-5503	160	18	vol	vol	NOUN
cana-5503	160	19	.	.	PROPN
cana-5503	160	20	178	178	NUM
cana-5503	160	21	,	,	PUNCT
cana-5503	160	22	no	no	INTJ
cana-5503	160	23	.	.	NOUN
cana-5503	160	24	8	8	NUM
cana-5503	160	25	,	,	PUNCT
cana-5503	160	26	pp	pp	ADJ
cana-5503	160	27	.	.	PUNCT
cana-5503	161	1	149–162	149–162	NUM
cana-5503	161	2	,	,	PUNCT
cana-5503	161	3	2019	2019	NUM
cana-5503	161	4	.	.	PUNCT
cana-5503	162	1	[	[	X
cana-5503	162	2	22	22	NUM
cana-5503	162	3	]	]	PUNCT
cana-5503	162	4	s.	s.	PROPN
cana-5503	162	5	sahu	sahu	PROPN
cana-5503	162	6	,	,	PUNCT
cana-5503	162	7	a.	a.	PROPN
cana-5503	162	8	k.	k.	PROPN
cana-5503	162	9	singh	singh	PROPN
cana-5503	162	10	,	,	PUNCT
cana-5503	162	11	and	and	CCONJ
cana-5503	162	12	m.	m.	NOUN
cana-5503	162	13	elhoseny	elhoseny	PROPN
cana-5503	162	14	,	,	PUNCT
cana-5503	162	15	“	"	PUNCT
cana-5503	162	16	an	an	DET
cana-5503	162	17	approach	approach	NOUN
cana-5503	162	18	for	for	ADP
cana-5503	162	19	de	de	NOUN
cana-5503	162	20	-	-	ADJ
cana-5503	162	21	noising	noising	ADJ
cana-5503	162	22	and	and	CCONJ
cana-5503	162	23	contrast	contrast	NOUN
cana-5503	162	24	enhancement	enhancement	NOUN
cana-5503	162	25	of	of	ADP
cana-5503	162	26	retinal	retinal	ADJ
cana-5503	162	27	fundus	fundus	NOUN
cana-5503	162	28	image	image	NOUN
cana-5503	162	29	using	use	VERB
cana-5503	162	30	clahe	clahe	NOUN
cana-5503	162	31	,	,	PUNCT
cana-5503	162	32	”	"	PUNCT
cana-5503	162	33	opt	opt	NOUN
cana-5503	162	34	.	.	PUNCT
cana-5503	163	1	laser	laser	NOUN
cana-5503	163	2	technol	technol	NOUN
cana-5503	163	3	.	.	PROPN
cana-5503	163	4	,	,	PUNCT
cana-5503	163	5	vol	vol	NOUN
cana-5503	163	6	.	.	PROPN
cana-5503	163	7	13	13	NUM
cana-5503	163	8	,	,	PUNCT
cana-5503	163	9	no	no	INTJ
cana-5503	163	10	.	.	PUNCT
cana-5503	164	1	july	july	PROPN
cana-5503	164	2	,	,	PUNCT
cana-5503	164	3	2018	2018	NUM
cana-5503	164	4	.	.	PUNCT
cana-5503	165	1	[	[	X
cana-5503	165	2	23	23	NUM
cana-5503	165	3	]	]	X
cana-5503	165	4	o.	o.	PROPN
cana-5503	165	5	noah	noah	PROPN
cana-5503	165	6	akande	akande	PROPN
cana-5503	165	7	,	,	PUNCT
cana-5503	165	8	o.	o.	PROPN
cana-5503	165	9	christiana	christiana	PROPN
cana-5503	165	10	abikoye	abikoye	PROPN
cana-5503	165	11	,	,	PUNCT
cana-5503	165	12	a.	a.	NOUN
cana-5503	165	13	anthonia	anthonia	PROPN
cana-5503	165	14	kayode	kayode	PROPN
cana-5503	165	15	,	,	PUNCT
cana-5503	165	16	and	and	CCONJ
cana-5503	165	17	y.	y.	PROPN
cana-5503	165	18	lamari	lamari	PROPN
cana-5503	165	19	,	,	PUNCT
cana-5503	165	20	“	"	PUNCT
cana-5503	165	21	implementation	implementation	NOUN
cana-5503	165	22	of	of	ADP
cana-5503	165	23	a	a	DET
cana-5503	165	24	framework	framework	NOUN
cana-5503	165	25	for	for	ADP
cana-5503	165	26	healthy	healthy	ADJ
cana-5503	165	27	and	and	CCONJ
cana-5503	165	28	diabetic	diabetic	ADJ
cana-5503	165	29	retinopathy	retinopathy	ADJ
cana-5503	165	30	retinal	retinal	ADJ
cana-5503	165	31	image	image	NOUN
cana-5503	165	32	recognition	recognition	NOUN
cana-5503	165	33	,	,	PUNCT
cana-5503	165	34	”	"	PUNCT
cana-5503	165	35	hindawi	hindawi	PROPN
cana-5503	165	36	sci	sci	PROPN
cana-5503	165	37	.	.	PROPN
cana-5503	165	38	,	,	PUNCT
cana-5503	165	39	vol	vol	NOUN
cana-5503	165	40	.	.	PUNCT
cana-5503	165	41	2020	2020	NUM
cana-5503	165	42	,	,	PUNCT
cana-5503	165	43	no	no	INTJ
cana-5503	165	44	.	.	PUNCT
cana-5503	166	1	may	may	AUX
cana-5503	166	2	,	,	PUNCT
cana-5503	166	3	pp	pp	ADV
cana-5503	166	4	.	.	PUNCT
cana-5503	167	1	1–14	1–14	PROPN
cana-5503	167	2	,	,	PUNCT
cana-5503	167	3	2022	2022	NUM
cana-5503	167	4	.	.	PUNCT
cana-5503	168	1	[	[	X
cana-5503	168	2	24	24	NUM
cana-5503	168	3	]	]	PUNCT
cana-5503	168	4	s.	s.	PROPN
cana-5503	168	5	s.	s.	PROPN
cana-5503	168	6	mondal	mondal	PROPN
cana-5503	168	7	,	,	PUNCT
cana-5503	168	8	n.	n.	PROPN
cana-5503	168	9	mandal	mandal	PROPN
cana-5503	168	10	,	,	PUNCT
cana-5503	168	11	a.	a.	NOUN
cana-5503	168	12	singh	singh	PROPN
cana-5503	168	13	,	,	PUNCT
cana-5503	168	14	and	and	CCONJ
cana-5503	168	15	k.	k.	PROPN
cana-5503	168	16	k.	k.	PROPN
cana-5503	168	17	singh	singh	PROPN
cana-5503	168	18	,	,	PUNCT
cana-5503	168	19	“	"	PUNCT
cana-5503	168	20	blood	blood	NOUN
cana-5503	168	21	vessel	vessel	NOUN
cana-5503	168	22	detection	detection	NOUN
cana-5503	168	23	from	from	ADP
cana-5503	168	24	retinal	retinal	ADJ
cana-5503	168	25	fundas	funda	NOUN
cana-5503	168	26	images	image	NOUN
cana-5503	168	27	using	use	VERB
cana-5503	168	28	gifkcn	gifkcn	ADJ
cana-5503	168	29	classifier	classifier	NOUN
cana-5503	168	30	,	,	PUNCT
cana-5503	168	31	”	"	PUNCT
cana-5503	168	32	procedia	procedia	NOUN
cana-5503	168	33	comput	comput	NOUN
cana-5503	168	34	.	.	PUNCT
cana-5503	169	1	sci	sci	PROPN
cana-5503	169	2	.	.	PROPN
cana-5503	169	3	,	,	PUNCT
cana-5503	169	4	vol	vol	NOUN
cana-5503	169	5	.	.	PROPN
cana-5503	169	6	167	167	NUM
cana-5503	169	7	,	,	PUNCT
cana-5503	169	8	no	no	INTJ
cana-5503	169	9	.	.	NOUN
cana-5503	169	10	2019	2019	NUM
cana-5503	169	11	,	,	PUNCT
cana-5503	169	12	pp	pp	ADJ
cana-5503	169	13	.	.	PUNCT
cana-5503	169	14	2060	2060	NUM
cana-5503	169	15	–	–	PUNCT
cana-5503	169	16	2069	2069	NUM
cana-5503	169	17	,	,	PUNCT
cana-5503	169	18	2022	2022	NUM
cana-5503	169	19	.	.	PUNCT
cana-5503	170	1	[	[	X
cana-5503	170	2	25	25	NUM
cana-5503	170	3	]	]	X
cana-5503	170	4	r.	r.	PROPN
cana-5503	170	5	r	r	PROPN
cana-5503	170	6	and	and	CCONJ
cana-5503	170	7	b.	b.	PROPN
cana-5503	170	8	lakshman	lakshman	PROPN
cana-5503	170	9	,	,	PUNCT
cana-5503	170	10	“	"	PUNCT
cana-5503	170	11	retinal	retinal	ADJ
cana-5503	170	12	image	image	NOUN
cana-5503	170	13	analysis	analysis	NOUN
cana-5503	170	14	using	use	VERB
cana-5503	170	15	morphological	morphological	ADJ
cana-5503	170	16	process	process	NOUN
cana-5503	170	17	and	and	CCONJ
cana-5503	170	18	clustering	clustering	NOUN
cana-5503	170	19	technique	technique	NOUN
cana-5503	170	20	,	,	PUNCT
cana-5503	170	21	”	"	PUNCT
cana-5503	170	22	signal	signal	ADJ
cana-5503	170	23	image	image	NOUN
cana-5503	170	24	process	process	NOUN
cana-5503	170	25	.	.	PUNCT
cana-5503	171	1	an	an	DET
cana-5503	171	2	int	int	NOUN
cana-5503	171	3	.	.	PUNCT
cana-5503	172	1	j.	j.	PROPN
cana-5503	172	2	,	,	PUNCT
cana-5503	172	3	vol	vol	NOUN
cana-5503	172	4	.	.	PROPN
cana-5503	172	5	4	4	NUM
cana-5503	172	6	,	,	PUNCT
cana-5503	172	7	no	no	INTJ
cana-5503	172	8	.	.	NOUN
cana-5503	172	9	6	6	NUM
cana-5503	172	10	,	,	PUNCT
cana-5503	172	11	pp	pp	ADJ
cana-5503	172	12	.	.	PUNCT
cana-5503	172	13	55–69	55–69	NUM
cana-5503	172	14	,	,	PUNCT
cana-5503	172	15	2013	2013	NUM
cana-5503	172	16	.	.	PUNCT
cana-5503	173	1	[	[	X
cana-5503	173	2	26	26	NUM
cana-5503	173	3	]	]	PUNCT
cana-5503	173	4	p.	p.	NOUN
cana-5503	173	5	v.	v.	PROPN
cana-5503	173	6	r.	r.	PROPN
cana-5503	173	7	raju	raju	PROPN
cana-5503	173	8	,	,	PUNCT
cana-5503	173	9	p.	p.	PROPN
cana-5503	173	10	k.	k.	PROPN
cana-5503	174	1	k.	k.	PROPN
cana-5503	174	2	varma	varma	PROPN
cana-5503	174	3	,	,	PUNCT
cana-5503	174	4	and	and	CCONJ
cana-5503	174	5	g.	g.	PROPN
cana-5503	174	6	nagaraju	nagaraju	PROPN
cana-5503	174	7	,	,	PUNCT
cana-5503	174	8	“	"	PUNCT
cana-5503	174	9	a	a	DET
cana-5503	174	10	dynamic	dynamic	ADJ
cana-5503	174	11	approach	approach	NOUN
cana-5503	174	12	for	for	ADP
cana-5503	174	13	exudates	exudate	NOUN
cana-5503	174	14	detection	detection	NOUN
cana-5503	174	15	in	in	ADP
cana-5503	174	16	diabetic	diabetic	ADJ
cana-5503	174	17	retinopathy	retinopathy	ADJ
cana-5503	174	18	images	image	NOUN
cana-5503	174	19	using	use	VERB
cana-5503	174	20	clustering	clustering	NOUN
cana-5503	174	21	,	,	PUNCT
cana-5503	174	22	”	"	PUNCT
cana-5503	174	23	int	int	NOUN
cana-5503	174	24	.	.	PUNCT
cana-5503	175	1	j.	j.	PROPN
cana-5503	175	2	pure	pure	PROPN
cana-5503	175	3	appl	appl	PROPN
cana-5503	175	4	.	.	PUNCT
cana-5503	175	5	math	math	PROPN
cana-5503	175	6	.	.	PUNCT
cana-5503	176	1	,	,	PUNCT
cana-5503	176	2	vol	vol	NOUN
cana-5503	176	3	.	.	PROPN
cana-5503	177	1	119	119	NUM
cana-5503	177	2	,	,	PUNCT
cana-5503	177	3	no	no	INTJ
cana-5503	177	4	.	.	NOUN
cana-5503	177	5	18	18	NUM
cana-5503	177	6	,	,	PUNCT
cana-5503	177	7	pp	pp	ADJ
cana-5503	177	8	.	.	PUNCT
cana-5503	178	1	751–765	751–765	NUM
cana-5503	178	2	,	,	PUNCT
cana-5503	178	3	2018	2018	NUM
cana-5503	178	4	.	.	PUNCT
cana-5503	179	1	[	[	X
cana-5503	179	2	27	27	NUM
cana-5503	179	3	]	]	PUNCT
cana-5503	179	4	z.	z.	PROPN
cana-5503	179	5	yavuz	yavuz	PROPN
cana-5503	179	6	and	and	CCONJ
cana-5503	179	7	c.	c.	PROPN
cana-5503	179	8	köse	köse	PROPN
cana-5503	179	9	,	,	PUNCT
cana-5503	179	10	“	"	PUNCT
cana-5503	179	11	blood	blood	NOUN
cana-5503	179	12	vessel	vessel	NOUN
cana-5503	179	13	extraction	extraction	NOUN
cana-5503	179	14	in	in	ADP
cana-5503	179	15	color	color	NOUN
cana-5503	179	16	retinal	retinal	ADJ
cana-5503	179	17	fundus	fundus	NOUN
cana-5503	179	18	images	image	NOUN
cana-5503	179	19	with	with	ADP
cana-5503	179	20	enhancement	enhancement	NOUN
cana-5503	179	21	filtering	filter	VERB
cana-5503	179	22	and	and	CCONJ
cana-5503	179	23	unsupervised	unsupervised	ADJ
cana-5503	179	24	classification	classification	NOUN
cana-5503	179	25	,	,	PUNCT
cana-5503	179	26	”	"	PUNCT
cana-5503	179	27	j.	j.	PROPN
cana-5503	179	28	healthc	healthc	PROPN
cana-5503	179	29	.	.	PUNCT
cana-5503	180	1	eng	eng	PROPN
cana-5503	180	2	.	.	PROPN
cana-5503	180	3	,	,	PUNCT
cana-5503	180	4	vol	vol	NOUN
cana-5503	180	5	.	.	PROPN
cana-5503	180	6	2017	2017	NUM
cana-5503	180	7	,	,	PUNCT
cana-5503	180	8	2017	2017	NUM
cana-5503	180	9	.	.	PUNCT
cana-5503	181	1	[	[	X
cana-5503	181	2	28	28	NUM
cana-5503	181	3	]	]	X
cana-5503	181	4	chavan	chavan	PROPN
cana-5503	181	5	,	,	PUNCT
cana-5503	181	6	r.	r.	PROPN
cana-5503	181	7	,	,	PUNCT
cana-5503	181	8	pete	pete	PROPN
cana-5503	181	9	,	,	PUNCT
cana-5503	181	10	d.	d.	PROPN
cana-5503	181	11	automatic	automatic	ADJ
cana-5503	181	12	multi	multi	ADJ
cana-5503	181	13	-	-	ADJ
cana-5503	181	14	disease	disease	ADJ
cana-5503	181	15	classification	classification	NOUN
cana-5503	181	16	on	on	ADP
cana-5503	181	17	retinal	retinal	ADJ
cana-5503	181	18	images	image	NOUN
cana-5503	181	19	using	use	VERB
cana-5503	181	20	multilevel	multilevel	PROPN
cana-5503	181	21	glowworm	glowworm	NOUN
cana-5503	181	22	swarm	swarm	NOUN
cana-5503	181	23	convolutional	convolutional	ADJ
cana-5503	181	24	neural	neural	ADJ
cana-5503	181	25	network	network	NOUN
cana-5503	181	26	.	.	PUNCT
cana-5503	182	1	j.	j.	PROPN
cana-5503	182	2	eng	eng	PROPN
cana-5503	182	3	.	.	PROPN
cana-5503	182	4	appl	appl	PROPN
cana-5503	182	5	.	.	PUNCT
cana-5503	183	1	sci	sci	PROPN
cana-5503	183	2	.	.	PROPN
cana-5503	184	1	71	71	NUM
cana-5503	184	2	,	,	PUNCT
cana-5503	184	3	26	26	NUM
cana-5503	184	4	(	(	PUNCT
cana-5503	184	5	2024	2024	NUM
cana-5503	184	6	)	)	PUNCT
cana-5503	184	7	.	.	PUNCT
cana-5503	185	1	https://doi.org/10.1186/s44147-023-00335-0	https://doi.org/10.1186/s44147-023-00335-0	NUM
cana-5503	185	2	.	.	PUNCT