id	sid	tid	token	lemma	pos
5x21td99n58	1	1	in	in	ADP
5x21td99n58	1	2	vivo	vivo	PROPN
5x21td99n58	1	3	fluorescence	fluorescence	ADJ
5x21td99n58	1	4	imaging	image	VERB
5x21td99n58	1	5	is	be	AUX
5x21td99n58	1	6	a	a	DET
5x21td99n58	1	7	powerful	powerful	ADJ
5x21td99n58	1	8	tool	tool	NOUN
5x21td99n58	1	9	for	for	ADP
5x21td99n58	1	10	understanding	understanding	NOUN
5x21td99n58	1	11	and	and	CCONJ
5x21td99n58	1	12	characterizing	characterize	VERB
5x21td99n58	1	13	biological	biological	ADJ
5x21td99n58	1	14	systems	system	NOUN
5x21td99n58	1	15	.	.	PUNCT
5x21td99n58	2	1	for	for	ADP
5x21td99n58	2	2	example	example	NOUN
5x21td99n58	2	3	,	,	PUNCT
5x21td99n58	2	4	with	with	ADP
5x21td99n58	2	5	the	the	DET
5x21td99n58	2	6	help	help	NOUN
5x21td99n58	2	7	of	of	ADP
5x21td99n58	2	8	in	in	ADP
5x21td99n58	2	9	vivo	vivo	PROPN
5x21td99n58	2	10	fluorescence	fluorescence	ADJ
5x21td99n58	2	11	imaging	imaging	NOUN
5x21td99n58	2	12	,	,	PUNCT
5x21td99n58	2	13	one	one	PRON
5x21td99n58	2	14	can	can	AUX
5x21td99n58	2	15	record	record	VERB
5x21td99n58	2	16	the	the	DET
5x21td99n58	2	17	neural	neural	ADJ
5x21td99n58	2	18	activity	activity	NOUN
5x21td99n58	2	19	(	(	PUNCT
5x21td99n58	2	20	neuronal	neuronal	ADJ
5x21td99n58	2	21	firing	firing	NOUN
5x21td99n58	2	22	)	)	PUNCT
5x21td99n58	2	23	of	of	ADP
5x21td99n58	2	24	freely	freely	ADV
5x21td99n58	2	25	moving	move	VERB
5x21td99n58	2	26	mice	mouse	NOUN
5x21td99n58	2	27	.	.	PUNCT
5x21td99n58	3	1	while	while	SCONJ
5x21td99n58	3	2	in	in	ADP
5x21td99n58	3	3	vivo	vivo	PROPN
5x21td99n58	3	4	fluorescence	fluorescence	ADJ
5x21td99n58	3	5	imaging	imaging	NOUN
5x21td99n58	3	6	technique	technique	NOUN
5x21td99n58	3	7	has	have	AUX
5x21td99n58	3	8	been	be	AUX
5x21td99n58	3	9	widely	widely	ADV
5x21td99n58	3	10	used	use	VERB
5x21td99n58	3	11	and	and	CCONJ
5x21td99n58	3	12	has	have	AUX
5x21td99n58	3	13	brought	bring	VERB
5x21td99n58	3	14	many	many	ADJ
5x21td99n58	3	15	benefits	benefit	NOUN
5x21td99n58	3	16	to	to	ADP
5x21td99n58	3	17	the	the	DET
5x21td99n58	3	18	biomedical	biomedical	ADJ
5x21td99n58	3	19	image	image	NOUN
5x21td99n58	3	20	processing	processing	NOUN
5x21td99n58	3	21	field	field	NOUN
5x21td99n58	3	22	,	,	PUNCT
5x21td99n58	3	23	a	a	DET
5x21td99n58	3	24	few	few	ADJ
5x21td99n58	3	25	major	major	ADJ
5x21td99n58	3	26	physical	physical	ADJ
5x21td99n58	3	27	limitations	limitation	NOUN
5x21td99n58	3	28	affect	affect	VERB
5x21td99n58	3	29	the	the	DET
5x21td99n58	3	30	image	image	NOUN
5x21td99n58	3	31	quality	quality	NOUN
5x21td99n58	3	32	and	and	CCONJ
5x21td99n58	3	33	data	datum	NOUN
5x21td99n58	3	34	analysis	analysis	NOUN
5x21td99n58	3	35	.	.	PUNCT
5x21td99n58	4	1	the	the	DET
5x21td99n58	4	2	three	three	NUM
5x21td99n58	4	3	fundamental	fundamental	ADJ
5x21td99n58	4	4	limits	limit	NOUN
5x21td99n58	4	5	in	in	ADP
5x21td99n58	4	6	fluorescence	fluorescence	ADJ
5x21td99n58	4	7	microscopy	microscopy	NOUN
5x21td99n58	4	8	include	include	VERB
5x21td99n58	4	9	poor	poor	ADJ
5x21td99n58	4	10	signal	signal	NOUN
5x21td99n58	4	11	-	-	PUNCT
5x21td99n58	4	12	to	to	ADP
5x21td99n58	4	13	-	-	PUNCT
5x21td99n58	4	14	noise	noise	NOUN
5x21td99n58	4	15	ratio	ratio	NOUN
5x21td99n58	4	16	(	(	PUNCT
5x21td99n58	4	17	snr	snr	PROPN
5x21td99n58	4	18	)	)	PUNCT
5x21td99n58	4	19	,	,	PUNCT
5x21td99n58	4	20	poor	poor	ADJ
5x21td99n58	4	21	spatial	spatial	ADJ
5x21td99n58	4	22	resolution	resolution	NOUN
5x21td99n58	4	23	,	,	PUNCT
5x21td99n58	4	24	and	and	CCONJ
5x21td99n58	4	25	dense	dense	ADJ
5x21td99n58	4	26	axial	axial	ADJ
5x21td99n58	4	27	images	image	NOUN
5x21td99n58	4	28	.	.	PUNCT
5x21td99n58	5	1	in	in	ADP
5x21td99n58	5	2	this	this	DET
5x21td99n58	5	3	work	work	NOUN
5x21td99n58	5	4	,	,	PUNCT
5x21td99n58	5	5	we	we	PRON
5x21td99n58	5	6	employ	employ	VERB
5x21td99n58	5	7	machine	machine	NOUN
5x21td99n58	5	8	learning	learning	NOUN
5x21td99n58	5	9	(	(	PUNCT
5x21td99n58	5	10	ml	ml	PROPN
5x21td99n58	5	11	)	)	PUNCT
5x21td99n58	5	12	models	model	NOUN
5x21td99n58	5	13	based	base	VERB
5x21td99n58	5	14	on	on	ADP
5x21td99n58	5	15	deep	deep	ADJ
5x21td99n58	5	16	convolutional	convolutional	ADJ
5x21td99n58	5	17	neural	neural	ADJ
5x21td99n58	5	18	networks	network	NOUN
5x21td99n58	5	19	(	(	PUNCT
5x21td99n58	5	20	cnn	cnn	PROPN
5x21td99n58	5	21	)	)	PUNCT
5x21td99n58	5	22	to	to	PART
5x21td99n58	5	23	overcome	overcome	VERB
5x21td99n58	5	24	the	the	DET
5x21td99n58	5	25	above	above	ADV
5x21td99n58	5	26	-	-	PUNCT
5x21td99n58	5	27	mentioned	mention	VERB
5x21td99n58	5	28	fundamental	fundamental	ADJ
5x21td99n58	5	29	limits	limit	NOUN
5x21td99n58	5	30	for	for	ADP
5x21td99n58	5	31	3d	3d	NOUN
5x21td99n58	5	32	in	in	ADP
5x21td99n58	5	33	vivo	vivo	PROPN
5x21td99n58	5	34	fluorescence	fluorescence	PROPN
5x21td99n58	5	35	imaging.firstly	imaging.firstly	ADV
5x21td99n58	5	36	,	,	PUNCT
5x21td99n58	5	37	the	the	DET
5x21td99n58	5	38	poor	poor	ADJ
5x21td99n58	5	39	snr	snr	PROPN
5x21td99n58	5	40	arises	arise	VERB
5x21td99n58	5	41	due	due	ADP
5x21td99n58	5	42	to	to	ADP
5x21td99n58	5	43	the	the	DET
5x21td99n58	5	44	faster	fast	ADJ
5x21td99n58	5	45	imaging	imaging	NOUN
5x21td99n58	5	46	speed	speed	NOUN
5x21td99n58	5	47	in	in	ADP
5x21td99n58	5	48	scenarios	scenario	NOUN
5x21td99n58	5	49	where	where	SCONJ
5x21td99n58	5	50	one	one	PRON
5x21td99n58	5	51	needs	need	VERB
5x21td99n58	5	52	to	to	PART
5x21td99n58	5	53	understand	understand	VERB
5x21td99n58	5	54	the	the	DET
5x21td99n58	5	55	dynamic	dynamic	ADJ
5x21td99n58	5	56	processes	process	NOUN
5x21td99n58	5	57	in	in	ADP
5x21td99n58	5	58	3d	3d	NOUN
5x21td99n58	5	59	in	in	ADP
5x21td99n58	5	60	vivo	vivo	PROPN
5x21td99n58	5	61	.	.	PUNCT
5x21td99n58	6	1	conventionally	conventionally	ADV
5x21td99n58	6	2	,	,	PUNCT
5x21td99n58	6	3	to	to	PART
5x21td99n58	6	4	improve	improve	VERB
5x21td99n58	6	5	image	image	NOUN
5x21td99n58	6	6	snr	snr	PROPN
5x21td99n58	6	7	for	for	ADP
5x21td99n58	6	8	a	a	DET
5x21td99n58	6	9	given	give	VERB
5x21td99n58	6	10	image	image	NOUN
5x21td99n58	6	11	acquisition	acquisition	NOUN
5x21td99n58	6	12	rate	rate	NOUN
5x21td99n58	6	13	,	,	PUNCT
5x21td99n58	6	14	one	one	PRON
5x21td99n58	6	15	can	can	AUX
5x21td99n58	6	16	use	use	VERB
5x21td99n58	6	17	statistical	statistical	ADJ
5x21td99n58	6	18	methods	method	NOUN
5x21td99n58	6	19	-	-	PUNCT
5x21td99n58	6	20	based	base	VERB
5x21td99n58	6	21	computational	computational	ADJ
5x21td99n58	6	22	denoising	denoise	VERB
5x21td99n58	6	23	techniques	technique	NOUN
5x21td99n58	6	24	to	to	PART
5x21td99n58	6	25	suppress	suppress	VERB
5x21td99n58	6	26	the	the	DET
5x21td99n58	6	27	noise	noise	NOUN
5x21td99n58	6	28	.	.	PUNCT
5x21td99n58	7	1	however	however	ADV
5x21td99n58	7	2	,	,	PUNCT
5x21td99n58	7	3	these	these	DET
5x21td99n58	7	4	methods	method	NOUN
5x21td99n58	7	5	are	be	AUX
5x21td99n58	7	6	either	either	CCONJ
5x21td99n58	7	7	computationally	computationally	ADV
5x21td99n58	7	8	expensive	expensive	ADJ
5x21td99n58	7	9	or	or	CCONJ
5x21td99n58	7	10	rely	rely	VERB
5x21td99n58	7	11	on	on	ADP
5x21td99n58	7	12	only	only	ADJ
5x21td99n58	7	13	simple	simple	ADJ
5x21td99n58	7	14	poisson	poisson	NOUN
5x21td99n58	7	15	or	or	CCONJ
5x21td99n58	7	16	gaussian	gaussian	ADJ
5x21td99n58	7	17	noise	noise	NOUN
5x21td99n58	7	18	statistics	statistic	NOUN
5x21td99n58	7	19	,	,	PUNCT
5x21td99n58	7	20	which	which	PRON
5x21td99n58	7	21	are	be	AUX
5x21td99n58	7	22	not	not	PART
5x21td99n58	7	23	appropriate	appropriate	ADJ
5x21td99n58	7	24	for	for	ADP
5x21td99n58	7	25	fluorescence	fluorescence	ADJ
5x21td99n58	7	26	microscopes	microscope	NOUN
5x21td99n58	7	27	that	that	PRON
5x21td99n58	7	28	usually	usually	ADV
5x21td99n58	7	29	contain	contain	VERB
5x21td99n58	7	30	a	a	DET
5x21td99n58	7	31	mixture	mixture	NOUN
5x21td99n58	7	32	of	of	ADP
5x21td99n58	7	33	poisson	poisson	NOUN
5x21td99n58	7	34	and	and	CCONJ
5x21td99n58	7	35	gaussian	gaussian	ADJ
5x21td99n58	7	36	(	(	PUNCT
5x21td99n58	7	37	mpg	mpg	ADJ
5x21td99n58	7	38	)	)	PUNCT
5x21td99n58	7	39	noise	noise	NOUN
5x21td99n58	7	40	.	.	PUNCT
5x21td99n58	8	1	therefore	therefore	ADV
5x21td99n58	8	2	,	,	PUNCT
5x21td99n58	8	3	to	to	PART
5x21td99n58	8	4	overcome	overcome	VERB
5x21td99n58	8	5	this	this	DET
5x21td99n58	8	6	fundamental	fundamental	ADJ
5x21td99n58	8	7	limitation	limitation	NOUN
5x21td99n58	8	8	,	,	PUNCT
5x21td99n58	8	9	we	we	PRON
5x21td99n58	8	10	have	have	AUX
5x21td99n58	8	11	developed	develop	VERB
5x21td99n58	8	12	two	two	NUM
5x21td99n58	8	13	cnn	cnn	NOUN
5x21td99n58	8	14	models	model	NOUN
5x21td99n58	8	15	based	base	VERB
5x21td99n58	8	16	on	on	ADP
5x21td99n58	8	17	the	the	DET
5x21td99n58	8	18	noise2noise	noise2noise	ADJ
5x21td99n58	8	19	and	and	CCONJ
5x21td99n58	8	20	dncnn	dncnn	ADJ
5x21td99n58	8	21	architectures	architecture	NOUN
5x21td99n58	8	22	trained	train	VERB
5x21td99n58	8	23	on	on	ADP
5x21td99n58	8	24	the	the	DET
5x21td99n58	8	25	massive	massive	ADJ
5x21td99n58	8	26	fluorescence	fluorescence	ADJ
5x21td99n58	8	27	microscopy	microscopy	NOUN
5x21td99n58	8	28	denoising	denoise	VERB
5x21td99n58	8	29	dataset	dataset	NOUN
5x21td99n58	8	30	containing	contain	VERB
5x21td99n58	8	31	mpg	mpg	NOUN
5x21td99n58	8	32	noise	noise	NOUN
5x21td99n58	8	33	.	.	PUNCT
5x21td99n58	9	1	noisy	noisy	ADJ
5x21td99n58	9	2	images	image	NOUN
5x21td99n58	9	3	in	in	ADP
5x21td99n58	9	4	the	the	DET
5x21td99n58	9	5	trained	train	VERB
5x21td99n58	9	6	dataset	dataset	NOUN
5x21td99n58	9	7	were	be	AUX
5x21td99n58	9	8	collected	collect	VERB
5x21td99n58	9	9	by	by	ADP
5x21td99n58	9	10	wide	wide	ADJ
5x21td99n58	9	11	-	-	PUNCT
5x21td99n58	9	12	field	field	NOUN
5x21td99n58	9	13	,	,	PUNCT
5x21td99n58	9	14	confocal	confocal	ADJ
5x21td99n58	9	15	and	and	CCONJ
5x21td99n58	9	16	two	two	NUM
5x21td99n58	9	17	-	-	PUNCT
5x21td99n58	9	18	photon	photon	NOUN
5x21td99n58	9	19	microscopes	microscope	NOUN
5x21td99n58	9	20	with	with	ADP
5x21td99n58	9	21	samples	sample	NOUN
5x21td99n58	9	22	including	include	VERB
5x21td99n58	9	23	fixed	fix	VERB
5x21td99n58	9	24	cells	cell	NOUN
5x21td99n58	9	25	,	,	PUNCT
5x21td99n58	9	26	zebrafish	zebrafish	NOUN
5x21td99n58	9	27	,	,	PUNCT
5x21td99n58	9	28	and	and	CCONJ
5x21td99n58	9	29	mouse	mouse	NOUN
5x21td99n58	9	30	brains	brain	NOUN
5x21td99n58	9	31	.	.	PUNCT
5x21td99n58	10	1	an	an	DET
5x21td99n58	10	2	open	open	ADJ
5x21td99n58	10	3	-	-	PUNCT
5x21td99n58	10	4	source	source	NOUN
5x21td99n58	10	5	imagej	imagej	ADJ
5x21td99n58	10	6	plugin	plugin	NOUN
5x21td99n58	10	7	was	be	AUX
5x21td99n58	10	8	developed	develop	VERB
5x21td99n58	10	9	using	use	VERB
5x21td99n58	10	10	the	the	DET
5x21td99n58	10	11	trained	train	VERB
5x21td99n58	10	12	cnn	cnn	PROPN
5x21td99n58	10	13	model	model	NOUN
5x21td99n58	10	14	that	that	PRON
5x21td99n58	10	15	performs	perform	VERB
5x21td99n58	10	16	instant	instant	ADJ
5x21td99n58	10	17	image	image	NOUN
5x21td99n58	10	18	denoising	denoise	VERB
5x21td99n58	10	19	within	within	ADP
5x21td99n58	10	20	tens	ten	NOUN
5x21td99n58	10	21	of	of	ADP
5x21td99n58	10	22	milliseconds	millisecond	NOUN
5x21td99n58	10	23	with	with	ADP
5x21td99n58	10	24	superior	superior	ADJ
5x21td99n58	10	25	performance	performance	NOUN
5x21td99n58	10	26	(	(	PUNCT
5x21td99n58	10	27	~8.1	~8.1	PROPN
5x21td99n58	10	28	db	db	PROPN
5x21td99n58	10	29	psnr	psnr	PROPN
5x21td99n58	10	30	improvement	improvement	PROPN
5x21td99n58	10	31	or	or	CCONJ
5x21td99n58	10	32	8x	8x	VERB
5x21td99n58	10	33	faster	fast	ADV
5x21td99n58	10	34	in	in	ADP
5x21td99n58	10	35	acquisition	acquisition	NOUN
5x21td99n58	10	36	)	)	PUNCT
5x21td99n58	10	37	compared	compare	VERB
5x21td99n58	10	38	to	to	ADP
5x21td99n58	10	39	the	the	DET
5x21td99n58	10	40	conventional	conventional	ADJ
5x21td99n58	10	41	denoising	denoise	VERB
5x21td99n58	10	42	methods	method	NOUN
5x21td99n58	10	43	.	.	PUNCT
5x21td99n58	11	1	hence	hence	ADV
5x21td99n58	11	2	,	,	PUNCT
5x21td99n58	11	3	imaging	image	VERB
5x21td99n58	11	4	speed	speed	NOUN
5x21td99n58	11	5	is	be	AUX
5x21td99n58	11	6	improved	improve	VERB
5x21td99n58	11	7	by	by	ADP
5x21td99n58	11	8	eight	eight	NUM
5x21td99n58	11	9	times	time	NOUN
5x21td99n58	11	10	using	use	VERB
5x21td99n58	11	11	this	this	DET
5x21td99n58	11	12	cnn	cnn	PROPN
5x21td99n58	11	13	-	-	PUNCT
5x21td99n58	11	14	based	base	VERB
5x21td99n58	11	15	image	image	NOUN
5x21td99n58	11	16	denoising	denoise	VERB
5x21td99n58	11	17	method	method	NOUN
5x21td99n58	11	18	.	.	PUNCT
5x21td99n58	12	1	next	next	ADJ
5x21td99n58	12	2	,	,	PUNCT
5x21td99n58	12	3	extensive	extensive	ADJ
5x21td99n58	12	4	validation	validation	NOUN
5x21td99n58	12	5	of	of	ADP
5x21td99n58	12	6	the	the	DET
5x21td99n58	12	7	pre	pre	ADJ
5x21td99n58	12	8	-	-	ADJ
5x21td99n58	12	9	trained	train	VERB
5x21td99n58	12	10	models	model	NOUN
5x21td99n58	12	11	was	be	AUX
5x21td99n58	12	12	performed	perform	VERB
5x21td99n58	12	13	on	on	ADP
5x21td99n58	12	14	the	the	DET
5x21td99n58	12	15	out	out	ADV
5x21td99n58	12	16	-	-	PUNCT
5x21td99n58	12	17	of	of	ADP
5x21td99n58	12	18	-	-	PUNCT
5x21td99n58	12	19	distribution	distribution	NOUN
5x21td99n58	12	20	noise	noise	NOUN
5x21td99n58	12	21	,	,	PUNCT
5x21td99n58	12	22	contrast	contrast	NOUN
5x21td99n58	12	23	,	,	PUNCT
5x21td99n58	12	24	microscope	microscope	NOUN
5x21td99n58	12	25	modality	modality	NOUN
5x21td99n58	12	26	,	,	PUNCT
5x21td99n58	12	27	biological	biological	ADJ
5x21td99n58	12	28	samples	sample	NOUN
5x21td99n58	12	29	(	(	PUNCT
5x21td99n58	12	30	2d	2d	NOUN
5x21td99n58	12	31	and	and	CCONJ
5x21td99n58	12	32	3d	3d	NOUN
5x21td99n58	12	33	images	image	NOUN
5x21td99n58	12	34	)	)	PUNCT
5x21td99n58	12	35	,	,	PUNCT
5x21td99n58	12	36	and	and	CCONJ
5x21td99n58	12	37	other	other	ADJ
5x21td99n58	12	38	open	open	ADJ
5x21td99n58	12	39	-	-	PUNCT
5x21td99n58	12	40	source	source	NOUN
5x21td99n58	12	41	fluorescence	fluorescence	ADJ
5x21td99n58	12	42	microscopy	microscopy	NOUN
5x21td99n58	12	43	datasets	dataset	NOUN
5x21td99n58	12	44	.	.	PUNCT
5x21td99n58	13	1	ml	ml	PROPN
5x21td99n58	13	2	-	-	PUNCT
5x21td99n58	13	3	based	base	VERB
5x21td99n58	13	4	fluorescence	fluorescence	ADJ
5x21td99n58	13	5	lifetime	lifetime	NOUN
5x21td99n58	13	6	and	and	CCONJ
5x21td99n58	13	7	phasor	phasor	VERB
5x21td99n58	13	8	denoising	denoise	VERB
5x21td99n58	13	9	techniques	technique	NOUN
5x21td99n58	13	10	and	and	CCONJ
5x21td99n58	13	11	their	their	PRON
5x21td99n58	13	12	applications	application	NOUN
5x21td99n58	13	13	are	be	AUX
5x21td99n58	13	14	also	also	ADV
5x21td99n58	13	15	demonstrated	demonstrate	VERB
5x21td99n58	13	16	.	.	PUNCT
5x21td99n58	14	1	the	the	DET
5x21td99n58	14	2	ml	ml	PROPN
5x21td99n58	14	3	-	-	PUNCT
5x21td99n58	14	4	based	base	VERB
5x21td99n58	14	5	approaches	approach	NOUN
5x21td99n58	14	6	provide	provide	VERB
5x21td99n58	14	7	high	high	ADJ
5x21td99n58	14	8	snr	snr	PROPN
5x21td99n58	14	9	in	in	ADP
5x21td99n58	14	10	lifetime	lifetime	NOUN
5x21td99n58	14	11	information	information	NOUN
5x21td99n58	14	12	and	and	CCONJ
5x21td99n58	14	13	improve	improve	VERB
5x21td99n58	14	14	the	the	DET
5x21td99n58	14	15	lifetime	lifetime	NOUN
5x21td99n58	14	16	segmentation	segmentation	NOUN
5x21td99n58	14	17	with	with	ADP
5x21td99n58	14	18	denoised	denoise	VERB
5x21td99n58	14	19	phasor.secondly	phasor.secondly	ADV
5x21td99n58	14	20	,	,	PUNCT
5x21td99n58	14	21	after	after	ADP
5x21td99n58	14	22	achieving	achieve	VERB
5x21td99n58	14	23	a	a	DET
5x21td99n58	14	24	faster	fast	ADJ
5x21td99n58	14	25	image	image	NOUN
5x21td99n58	14	26	acquisition	acquisition	NOUN
5x21td99n58	14	27	speed	speed	NOUN
5x21td99n58	14	28	of	of	ADP
5x21td99n58	14	29	the	the	DET
5x21td99n58	14	30	in	in	ADP
5x21td99n58	14	31	vivo	vivo	ADJ
5x21td99n58	14	32	images	image	NOUN
5x21td99n58	14	33	,	,	PUNCT
5x21td99n58	14	34	our	our	PRON
5x21td99n58	14	35	next	next	ADJ
5x21td99n58	14	36	goal	goal	NOUN
5x21td99n58	14	37	is	be	AUX
5x21td99n58	14	38	to	to	PART
5x21td99n58	14	39	improve	improve	VERB
5x21td99n58	14	40	the	the	DET
5x21td99n58	14	41	spatial	spatial	ADJ
5x21td99n58	14	42	resolution	resolution	NOUN
5x21td99n58	14	43	of	of	ADP
5x21td99n58	14	44	the	the	DET
5x21td99n58	14	45	fluorescence	fluorescence	ADJ
5x21td99n58	14	46	images	image	NOUN
5x21td99n58	14	47	by	by	ADP
5x21td99n58	14	48	overcoming	overcome	VERB
5x21td99n58	14	49	the	the	DET
5x21td99n58	14	50	fundamental	fundamental	ADJ
5x21td99n58	14	51	diffraction	diffraction	NOUN
5x21td99n58	14	52	limit	limit	NOUN
5x21td99n58	14	53	.	.	PUNCT
5x21td99n58	15	1	to	to	PART
5x21td99n58	15	2	develop	develop	VERB
5x21td99n58	15	3	the	the	DET
5x21td99n58	15	4	ml	ml	PROPN
5x21td99n58	15	5	model	model	NOUN
5x21td99n58	15	6	,	,	PUNCT
5x21td99n58	15	7	we	we	PRON
5x21td99n58	15	8	need	need	VERB
5x21td99n58	15	9	another	another	DET
5x21td99n58	15	10	massive	massive	ADJ
5x21td99n58	15	11	training	training	NOUN
5x21td99n58	15	12	dataset	dataset	NOUN
5x21td99n58	15	13	that	that	PRON
5x21td99n58	15	14	maps	map	VERB
5x21td99n58	15	15	from	from	ADP
5x21td99n58	15	16	the	the	DET
5x21td99n58	15	17	diffraction	diffraction	NOUN
5x21td99n58	15	18	-	-	PUNCT
5x21td99n58	15	19	limited	limit	VERB
5x21td99n58	15	20	images	image	NOUN
5x21td99n58	15	21	to	to	ADP
5x21td99n58	15	22	super	super	ADJ
5x21td99n58	15	23	-	-	ADJ
5x21td99n58	15	24	resolution	resolution	ADJ
5x21td99n58	15	25	images	image	NOUN
5x21td99n58	15	26	,	,	PUNCT
5x21td99n58	15	27	which	which	PRON
5x21td99n58	15	28	is	be	AUX
5x21td99n58	15	29	a	a	DET
5x21td99n58	15	30	cumbersome	cumbersome	ADJ
5x21td99n58	15	31	process	process	NOUN
5x21td99n58	15	32	.	.	PUNCT
5x21td99n58	16	1	currently	currently	ADV
5x21td99n58	16	2	,	,	PUNCT
5x21td99n58	16	3	we	we	PRON
5x21td99n58	16	4	have	have	AUX
5x21td99n58	16	5	developed	develop	VERB
5x21td99n58	16	6	a	a	DET
5x21td99n58	16	7	prototype	prototype	NOUN
5x21td99n58	16	8	of	of	ADP
5x21td99n58	16	9	the	the	DET
5x21td99n58	16	10	ml	ml	PROPN
5x21td99n58	16	11	model	model	NOUN
5x21td99n58	16	12	that	that	PRON
5x21td99n58	16	13	requires	require	VERB
5x21td99n58	16	14	only	only	ADV
5x21td99n58	16	15	an	an	DET
5x21td99n58	16	16	ultra	ultra	ADJ
5x21td99n58	16	17	-	-	ADJ
5x21td99n58	16	18	small	small	ADJ
5x21td99n58	16	19	training	training	NOUN
5x21td99n58	16	20	dataset	dataset	NOUN
5x21td99n58	16	21	(	(	PUNCT
5x21td99n58	16	22	15	15	NUM
5x21td99n58	16	23	target	target	NOUN
5x21td99n58	16	24	sr	sr	NOUN
5x21td99n58	16	25	images	image	NOUN
5x21td99n58	16	26	with	with	ADP
5x21td99n58	16	27	50	50	NUM
5x21td99n58	16	28	diffraction	diffraction	NOUN
5x21td99n58	16	29	-	-	PUNCT
5x21td99n58	16	30	limited	limit	VERB
5x21td99n58	16	31	images	image	NOUN
5x21td99n58	16	32	per	per	ADP
5x21td99n58	16	33	target	target	NOUN
5x21td99n58	16	34	)	)	PUNCT
5x21td99n58	16	35	to	to	PART
5x21td99n58	16	36	generate	generate	VERB
5x21td99n58	16	37	super	super	ADJ
5x21td99n58	16	38	-	-	ADJ
5x21td99n58	16	39	resolution	resolution	ADJ
5x21td99n58	16	40	images	image	NOUN
5x21td99n58	16	41	.	.	PUNCT
5x21td99n58	17	1	briefly	briefly	ADV
5x21td99n58	17	2	,	,	PUNCT
5x21td99n58	17	3	this	this	DET
5x21td99n58	17	4	model	model	NOUN
5x21td99n58	17	5	is	be	AUX
5x21td99n58	17	6	based	base	VERB
5x21td99n58	17	7	on	on	ADP
5x21td99n58	17	8	the	the	DET
5x21td99n58	17	9	novel	novel	NOUN
5x21td99n58	17	10	`	`	PUNCT
5x21td99n58	17	11	`	`	PUNCT
5x21td99n58	17	12	dense	dense	ADJ
5x21td99n58	17	13	encoder	encoder	NOUN
5x21td99n58	17	14	-	-	PUNCT
5x21td99n58	17	15	decoder	decoder	NOUN
5x21td99n58	17	16	"	"	PUNCT
5x21td99n58	17	17	(	(	PUNCT
5x21td99n58	17	18	denseed	denseed	PROPN
5x21td99n58	17	19	)	)	PUNCT
5x21td99n58	17	20	block	block	NOUN
5x21td99n58	17	21	,	,	PUNCT
5x21td99n58	17	22	developed	develop	VERB
5x21td99n58	17	23	based	base	VERB
5x21td99n58	17	24	on	on	ADP
5x21td99n58	17	25	the	the	DET
5x21td99n58	17	26	dense	dense	ADJ
5x21td99n58	17	27	layer	layer	NOUN
5x21td99n58	17	28	in	in	ADP
5x21td99n58	17	29	the	the	DET
5x21td99n58	17	30	existing	exist	VERB
5x21td99n58	17	31	popular	popular	ADJ
5x21td99n58	17	32	super	super	ADJ
5x21td99n58	17	33	-	-	ADJ
5x21td99n58	17	34	resolution	resolution	ADJ
5x21td99n58	17	35	models	model	NOUN
5x21td99n58	17	36	.	.	PUNCT
5x21td99n58	18	1	we	we	PRON
5x21td99n58	18	2	experimentally	experimentally	ADV
5x21td99n58	18	3	verified	verify	VERB
5x21td99n58	18	4	our	our	PRON
5x21td99n58	18	5	demonstrated	demonstrated	ADJ
5x21td99n58	18	6	ml	ml	PROPN
5x21td99n58	18	7	model	model	NOUN
5x21td99n58	18	8	using	use	VERB
5x21td99n58	18	9	fluorescent	fluorescent	NOUN
5x21td99n58	18	10	-	-	PUNCT
5x21td99n58	18	11	labeled	label	VERB
5x21td99n58	18	12	fixed	fixed	ADJ
5x21td99n58	18	13	bovine	bovine	NOUN
5x21td99n58	18	14	pulmonary	pulmonary	ADJ
5x21td99n58	18	15	artery	artery	NOUN
5x21td99n58	18	16	endothelial	endothelial	NOUN
5x21td99n58	18	17	(	(	PUNCT
5x21td99n58	18	18	bpae	bpae	PROPN
5x21td99n58	18	19	)	)	PUNCT
5x21td99n58	18	20	cells	cell	NOUN
5x21td99n58	18	21	.	.	PUNCT
5x21td99n58	19	1	the	the	DET
5x21td99n58	19	2	improvement	improvement	NOUN
5x21td99n58	19	3	in	in	ADP
5x21td99n58	19	4	snr	snr	PROPN
5x21td99n58	19	5	and	and	CCONJ
5x21td99n58	19	6	spatial	spatial	ADJ
5x21td99n58	19	7	resolution	resolution	NOUN
5x21td99n58	19	8	in	in	ADP
5x21td99n58	19	9	the	the	DET
5x21td99n58	19	10	ml	ml	PROPN
5x21td99n58	19	11	-	-	PUNCT
5x21td99n58	19	12	generated	generate	VERB
5x21td99n58	19	13	super	super	ADJ
5x21td99n58	19	14	-	-	ADJ
5x21td99n58	19	15	resolution	resolution	ADJ
5x21td99n58	19	16	images	image	NOUN
5x21td99n58	19	17	is	be	AUX
5x21td99n58	19	18	~3.49	~3.49	PUNCT
5x21td99n58	19	19	db	db	PROPN
5x21td99n58	19	20	and	and	CCONJ
5x21td99n58	19	21	2x	2x	PROPN
5x21td99n58	19	22	,	,	PUNCT
5x21td99n58	19	23	respectively	respectively	ADV
5x21td99n58	19	24	,	,	PUNCT
5x21td99n58	19	25	compared	compare	VERB
5x21td99n58	19	26	to	to	ADP
5x21td99n58	19	27	the	the	DET
5x21td99n58	19	28	diffraction	diffraction	NOUN
5x21td99n58	19	29	-	-	PUNCT
5x21td99n58	19	30	limited	limit	VERB
5x21td99n58	19	31	image	image	NOUN
5x21td99n58	19	32	.	.	PUNCT
5x21td99n58	20	1	this	this	DET
5x21td99n58	20	2	approach	approach	NOUN
5x21td99n58	20	3	is	be	AUX
5x21td99n58	20	4	beneficial	beneficial	ADJ
5x21td99n58	20	5	for	for	ADP
5x21td99n58	20	6	in	in	ADP
5x21td99n58	20	7	vivo	vivo	ADJ
5x21td99n58	20	8	imaging	imaging	NOUN
5x21td99n58	20	9	,	,	PUNCT
5x21td99n58	20	10	x	x	NOUN
5x21td99n58	20	11	-	-	NOUN
5x21td99n58	20	12	ray	ray	NOUN
5x21td99n58	20	13	,	,	PUNCT
5x21td99n58	20	14	and	and	CCONJ
5x21td99n58	20	15	mri	mri	NOUN
5x21td99n58	20	16	imaging	imaging	NOUN
5x21td99n58	20	17	,	,	PUNCT
5x21td99n58	20	18	where	where	SCONJ
5x21td99n58	20	19	extracting	extract	VERB
5x21td99n58	20	20	large	large	ADJ
5x21td99n58	20	21	datasets	dataset	NOUN
5x21td99n58	20	22	is	be	AUX
5x21td99n58	20	23	challenging	challenging	ADJ
5x21td99n58	20	24	.	.	PUNCT
5x21td99n58	21	1	next	next	ADV
5x21td99n58	21	2	,	,	PUNCT
5x21td99n58	21	3	validation	validation	NOUN
5x21td99n58	21	4	of	of	ADP
5x21td99n58	21	5	the	the	DET
5x21td99n58	21	6	proposed	propose	VERB
5x21td99n58	21	7	methodology	methodology	NOUN
5x21td99n58	21	8	is	be	AUX
5x21td99n58	21	9	shown	show	VERB
5x21td99n58	21	10	on	on	ADP
5x21td99n58	21	11	the	the	DET
5x21td99n58	21	12	experimentally	experimentally	ADV
5x21td99n58	21	13	captured	capture	VERB
5x21td99n58	21	14	diffraction	diffraction	NOUN
5x21td99n58	21	15	-	-	PUNCT
5x21td99n58	21	16	limited	limit	VERB
5x21td99n58	21	17	and	and	CCONJ
5x21td99n58	21	18	super	super	ADJ
5x21td99n58	21	19	-	-	ADJ
5x21td99n58	21	20	resolution	resolution	ADJ
5x21td99n58	21	21	image	image	NOUN
5x21td99n58	21	22	datasets	dataset	NOUN
5x21td99n58	21	23	.	.	PUNCT
5x21td99n58	22	1	clearly	clearly	ADV
5x21td99n58	22	2	,	,	PUNCT
5x21td99n58	22	3	the	the	DET
5x21td99n58	22	4	demonstrated	demonstrate	VERB
5x21td99n58	22	5	`	`	PUNCT
5x21td99n58	22	6	`	`	PUNCT
5x21td99n58	22	7	denseed	denseed	X
5x21td99n58	22	8	"	"	PUNCT
5x21td99n58	22	9	ml	ml	PROPN
5x21td99n58	22	10	block	block	NOUN
5x21td99n58	22	11	provides	provide	VERB
5x21td99n58	22	12	enhanced	enhanced	ADJ
5x21td99n58	22	13	super	super	ADJ
5x21td99n58	22	14	-	-	ADJ
5x21td99n58	22	15	resolution	resolution	ADJ
5x21td99n58	22	16	images	image	NOUN
5x21td99n58	22	17	compared	compare	VERB
5x21td99n58	22	18	to	to	ADP
5x21td99n58	22	19	simple	simple	ADJ
5x21td99n58	22	20	cnn	cnn	PROPN
5x21td99n58	22	21	-	-	PUNCT
5x21td99n58	22	22	based	base	VERB
5x21td99n58	22	23	ml	ml	PROPN
5x21td99n58	22	24	models	model	NOUN
5x21td99n58	22	25	when	when	SCONJ
5x21td99n58	22	26	trained	train	VERB
5x21td99n58	22	27	with	with	ADP
5x21td99n58	22	28	an	an	DET
5x21td99n58	22	29	ultra	ultra	ADJ
5x21td99n58	22	30	-	-	ADJ
5x21td99n58	22	31	small	small	ADJ
5x21td99n58	22	32	training	training	NOUN
5x21td99n58	22	33	dataset	dataset	NOUN
5x21td99n58	22	34	(	(	PUNCT
5x21td99n58	22	35	minimal	minimal	ADJ
5x21td99n58	22	36	number	number	NOUN
5x21td99n58	22	37	of	of	ADP
5x21td99n58	22	38	fovs	fovs	NOUN
5x21td99n58	22	39	)	)	PUNCT
5x21td99n58	22	40	.	.	PUNCT
5x21td99n58	23	1	in	in	ADP
5x21td99n58	23	2	the	the	DET
5x21td99n58	23	3	case	case	NOUN
5x21td99n58	23	4	of	of	ADP
5x21td99n58	23	5	flim	flim	PROPN
5x21td99n58	23	6	super	super	NOUN
5x21td99n58	23	7	-	-	NOUN
5x21td99n58	23	8	resolution	resolution	NOUN
5x21td99n58	23	9	,	,	PUNCT
5x21td99n58	23	10	we	we	PRON
5x21td99n58	23	11	proposed	propose	VERB
5x21td99n58	23	12	a	a	DET
5x21td99n58	23	13	traditional	traditional	ADJ
5x21td99n58	23	14	deconvolution	deconvolution	NOUN
5x21td99n58	23	15	approach	approach	NOUN
5x21td99n58	23	16	to	to	PART
5x21td99n58	23	17	identify	identify	VERB
5x21td99n58	23	18	the	the	DET
5x21td99n58	23	19	true	true	ADJ
5x21td99n58	23	20	object	object	NOUN
5x21td99n58	23	21	/	/	SYM
5x21td99n58	23	22	sample	sample	NOUN
5x21td99n58	23	23	from	from	ADP
5x21td99n58	23	24	the	the	DET
5x21td99n58	23	25	diffraction	diffraction	NOUN
5x21td99n58	23	26	-	-	PUNCT
5x21td99n58	23	27	limited	limit	VERB
5x21td99n58	23	28	images	image	NOUN
5x21td99n58	23	29	(	(	PUNCT
5x21td99n58	23	30	experimentally	experimentally	ADV
5x21td99n58	23	31	captured	capture	VERB
5x21td99n58	23	32	)	)	PUNCT
5x21td99n58	23	33	.	.	PUNCT
5x21td99n58	24	1	in	in	ADP
5x21td99n58	24	2	this	this	DET
5x21td99n58	24	3	project	project	NOUN
5x21td99n58	24	4	,	,	PUNCT
5x21td99n58	24	5	we	we	PRON
5x21td99n58	24	6	provide	provide	VERB
5x21td99n58	24	7	a	a	DET
5x21td99n58	24	8	theoretical	theoretical	ADJ
5x21td99n58	24	9	model	model	NOUN
5x21td99n58	24	10	for	for	ADP
5x21td99n58	24	11	convolution	convolution	NOUN
5x21td99n58	24	12	in	in	ADP
5x21td99n58	24	13	flim	flim	PROPN
5x21td99n58	24	14	and	and	CCONJ
5x21td99n58	24	15	richardson	richardson	PROPN
5x21td99n58	24	16	-	-	PUNCT
5x21td99n58	24	17	lucy	lucy	PROPN
5x21td99n58	24	18	(	(	PUNCT
5x21td99n58	24	19	rl	rl	PROPN
5x21td99n58	24	20	)	)	PUNCT
5x21td99n58	24	21	based	base	VERB
5x21td99n58	24	22	deconvolution	deconvolution	NOUN
5x21td99n58	24	23	,	,	PUNCT
5x21td99n58	24	24	including	include	VERB
5x21td99n58	24	25	the	the	DET
5x21td99n58	24	26	total	total	ADJ
5x21td99n58	24	27	variation	variation	NOUN
5x21td99n58	24	28	(	(	PUNCT
5x21td99n58	24	29	tv	tv	NOUN
5x21td99n58	24	30	)	)	PUNCT
5x21td99n58	24	31	regularization	regularization	NOUN
5x21td99n58	24	32	method	method	NOUN
5x21td99n58	24	33	to	to	PART
5x21td99n58	24	34	correct	correct	VERB
5x21td99n58	24	35	the	the	DET
5x21td99n58	24	36	convolution	convolution	NOUN
5x21td99n58	24	37	-	-	PUNCT
5x21td99n58	24	38	induced	induce	VERB
5x21td99n58	24	39	distortions	distortion	NOUN
5x21td99n58	24	40	in	in	ADP
5x21td99n58	24	41	flim	flim	ADJ
5x21td99n58	24	42	measurements	measurement	NOUN
5x21td99n58	24	43	.	.	PUNCT
5x21td99n58	25	1	in	in	ADP
5x21td99n58	25	2	addition	addition	NOUN
5x21td99n58	25	3	,	,	PUNCT
5x21td99n58	25	4	the	the	DET
5x21td99n58	25	5	proposed	propose	VERB
5x21td99n58	25	6	method	method	NOUN
5x21td99n58	25	7	is	be	AUX
5x21td99n58	25	8	validated	validate	VERB
5x21td99n58	25	9	on	on	ADP
5x21td99n58	25	10	experimental	experimental	ADJ
5x21td99n58	25	11	images	image	NOUN
5x21td99n58	25	12	captured	capture	VERB
5x21td99n58	25	13	using	use	VERB
5x21td99n58	25	14	multi	multi	ADJ
5x21td99n58	25	15	-	-	ADJ
5x21td99n58	25	16	photon	photon	ADJ
5x21td99n58	25	17	microscopy	microscopy	NOUN
5x21td99n58	25	18	(	(	PUNCT
5x21td99n58	25	19	mpm)-flim	mpm)-flim	NUM
5x21td99n58	25	20	images	image	NOUN
5x21td99n58	25	21	of	of	ADP
5x21td99n58	25	22	fluorescent	fluorescent	NOUN
5x21td99n58	25	23	-	-	PUNCT
5x21td99n58	25	24	labeled	label	VERB
5x21td99n58	25	25	fixed	fix	VERB
5x21td99n58	25	26	bovine	bovine	NOUN
5x21td99n58	25	27	pulmonary	pulmonary	ADJ
5x21td99n58	25	28	arterial	arterial	ADJ
5x21td99n58	25	29	endothelial	endothelial	NOUN
5x21td99n58	25	30	(	(	PUNCT
5x21td99n58	25	31	bpae	bpae	PROPN
5x21td99n58	25	32	)	)	PUNCT
5x21td99n58	25	33	cells	cell	NOUN
5x21td99n58	25	34	.	.	PUNCT
5x21td99n58	26	1	finally	finally	ADV
5x21td99n58	26	2	,	,	PUNCT
5x21td99n58	26	3	we	we	PRON
5x21td99n58	26	4	further	far	ADV
5x21td99n58	26	5	enhance	enhance	VERB
5x21td99n58	26	6	the	the	DET
5x21td99n58	26	7	capabilities	capability	NOUN
5x21td99n58	26	8	of	of	ADP
5x21td99n58	26	9	low	low	ADJ
5x21td99n58	26	10	dosage	dosage	NOUN
5x21td99n58	26	11	,	,	PUNCT
5x21td99n58	26	12	long	long	ADJ
5x21td99n58	26	13	-	-	PUNCT
5x21td99n58	26	14	term	term	NOUN
5x21td99n58	26	15	,	,	PUNCT
5x21td99n58	26	16	in	in	ADP
5x21td99n58	26	17	vivo	vivo	NOUN
5x21td99n58	26	18	imaging	image	VERB
5x21td99n58	26	19	with	with	ADP
5x21td99n58	26	20	the	the	DET
5x21td99n58	26	21	assistance	assistance	NOUN
5x21td99n58	26	22	of	of	ADP
5x21td99n58	26	23	ml	ml	PROPN
5x21td99n58	26	24	models	model	NOUN
5x21td99n58	26	25	.	.	PUNCT
5x21td99n58	27	1	compressive	compressive	ADJ
5x21td99n58	27	2	sensing	sense	VERB
5x21td99n58	27	3	-	-	PUNCT
5x21td99n58	27	4	based	base	VERB
5x21td99n58	27	5	(	(	PUNCT
5x21td99n58	27	6	unsupervised	unsupervised	ADJ
5x21td99n58	27	7	machine	machine	NOUN
5x21td99n58	27	8	learning	learning	NOUN
5x21td99n58	27	9	model	model	NOUN
5x21td99n58	27	10	)	)	PUNCT
5x21td99n58	27	11	3d	3d	NOUN
5x21td99n58	27	12	volume	volume	NOUN
5x21td99n58	27	13	reconstruction	reconstruction	NOUN
5x21td99n58	27	14	and	and	CCONJ
5x21td99n58	27	15	image	image	NOUN
5x21td99n58	27	16	denoising	denoise	VERB
5x21td99n58	27	17	for	for	ADP
5x21td99n58	27	18	low	low	ADJ
5x21td99n58	27	19	-	-	PUNCT
5x21td99n58	27	20	power	power	NOUN
5x21td99n58	27	21	image	image	NOUN
5x21td99n58	27	22	acquisition	acquisition	NOUN
5x21td99n58	27	23	will	will	AUX
5x21td99n58	27	24	be	be	AUX
5x21td99n58	27	25	developed	develop	VERB
5x21td99n58	27	26	to	to	PART
5x21td99n58	27	27	accurately	accurately	ADV
5x21td99n58	27	28	reconstruct	reconstruct	VERB
5x21td99n58	27	29	and	and	CCONJ
5x21td99n58	27	30	improve	improve	VERB
5x21td99n58	27	31	the	the	DET
5x21td99n58	27	32	snr	snr	PROPN
5x21td99n58	27	33	for	for	ADP
5x21td99n58	27	34	long	long	ADJ
5x21td99n58	27	35	-	-	PUNCT
5x21td99n58	27	36	term	term	NOUN
5x21td99n58	27	37	imaging	imaging	NOUN
5x21td99n58	27	38	.	.	PUNCT
5x21td99n58	28	1	experimental	experimental	ADJ
5x21td99n58	28	2	results	result	NOUN
5x21td99n58	28	3	are	be	AUX
5x21td99n58	28	4	presented	present	VERB
5x21td99n58	28	5	in	in	ADP
5x21td99n58	28	6	the	the	DET
5x21td99n58	28	7	respective	respective	ADJ
5x21td99n58	28	8	sections.overall	sections.overall	PROPN
5x21td99n58	28	9	,	,	PUNCT
5x21td99n58	28	10	in	in	ADP
5x21td99n58	28	11	this	this	DET
5x21td99n58	28	12	dissertation	dissertation	NOUN
5x21td99n58	28	13	,	,	PUNCT
5x21td99n58	28	14	we	we	PRON
5x21td99n58	28	15	show	show	VERB
5x21td99n58	28	16	that	that	SCONJ
5x21td99n58	28	17	the	the	DET
5x21td99n58	28	18	above	above	ADV
5x21td99n58	28	19	-	-	PUNCT
5x21td99n58	28	20	mentioned	mention	VERB
5x21td99n58	28	21	methods	method	NOUN
5x21td99n58	28	22	namely	namely	ADV
5x21td99n58	28	23	image	image	NOUN
5x21td99n58	28	24	denoising	denoising	NOUN
5x21td99n58	28	25	,	,	PUNCT
5x21td99n58	28	26	image	image	NOUN
5x21td99n58	28	27	super	super	NOUN
5x21td99n58	28	28	-	-	NOUN
5x21td99n58	28	29	resolution	resolution	NOUN
5x21td99n58	28	30	,	,	PUNCT
5x21td99n58	28	31	and	and	CCONJ
5x21td99n58	28	32	low	low	ADJ
5x21td99n58	28	33	-	-	PUNCT
5x21td99n58	28	34	dosage	dosage	NOUN
5x21td99n58	28	35	3d	3d	NOUN
5x21td99n58	28	36	volume	volume	NOUN
5x21td99n58	28	37	imaging	imaging	NOUN
5x21td99n58	28	38	can	can	AUX
5x21td99n58	28	39	be	be	AUX
5x21td99n58	28	40	used	use	VERB
5x21td99n58	28	41	to	to	PART
5x21td99n58	28	42	solve	solve	VERB
5x21td99n58	28	43	the	the	DET
5x21td99n58	28	44	fundamental	fundamental	ADJ
5x21td99n58	28	45	limitations	limitation	NOUN
5x21td99n58	28	46	of	of	ADP
5x21td99n58	28	47	fluorescence	fluorescence	ADJ
5x21td99n58	28	48	microscopy	microscopy	NOUN
5x21td99n58	28	49	/	/	SYM
5x21td99n58	28	50	flim	flim	NOUN
5x21td99n58	28	51	using	use	VERB
5x21td99n58	28	52	machine	machine	NOUN
5x21td99n58	28	53	learning	learning	NOUN
5x21td99n58	28	54	models	model	NOUN
5x21td99n58	28	55	and	and	CCONJ
5x21td99n58	28	56	obtain	obtain	VERB
5x21td99n58	28	57	significant	significant	ADJ
5x21td99n58	28	58	acceleration	acceleration	NOUN
5x21td99n58	28	59	in	in	ADP
5x21td99n58	28	60	terms	term	NOUN
5x21td99n58	28	61	of	of	ADP
5x21td99n58	28	62	accuracy	accuracy	NOUN
5x21td99n58	28	63	and	and	CCONJ
5x21td99n58	28	64	computational	computational	ADJ
5x21td99n58	28	65	cost	cost	NOUN
5x21td99n58	28	66	(	(	PUNCT
5x21td99n58	28	67	in	in	ADP
5x21td99n58	28	68	-	-	PUNCT
5x21td99n58	28	69	terms	term	NOUN
5x21td99n58	28	70	of	of	ADP
5x21td99n58	28	71	instant	instant	ADJ
5x21td99n58	28	72	imaging	imaging	NOUN
5x21td99n58	28	73	,	,	PUNCT
5x21td99n58	28	74	faster	fast	ADV
5x21td99n58	28	75	training	training	NOUN
5x21td99n58	28	76	ml	ml	NOUN
5x21td99n58	28	77	models	model	NOUN
5x21td99n58	28	78	and	and	CCONJ
5x21td99n58	28	79	avoiding	avoid	VERB
5x21td99n58	28	80	photo	photo	NOUN
5x21td99n58	28	81	-	-	PUNCT
5x21td99n58	28	82	bleaching	bleaching	NOUN
5x21td99n58	28	83	of	of	ADP
5x21td99n58	28	84	the	the	DET
5x21td99n58	28	85	sample	sample	NOUN
5x21td99n58	28	86	)	)	PUNCT
5x21td99n58	28	87	than	than	ADP
5x21td99n58	28	88	conventional	conventional	ADJ
5x21td99n58	28	89	methods	method	NOUN
5x21td99n58	28	90	.	.	PUNCT