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Table 1 Medical image dataset

From: Advantages of transformer and its application for medical image segmentation: a survey

Datasets

Year

Tasks

Resolving power(pixel)

Sample

STARE [79]

2000

Retinal vascular segmentation

700 \(\times\) 605

20

DRIVE [80]

2004

Retinal vascular segmentation

768 \(\times\) 584

40

Alizarine [81]

2010

Corneal endothelial cell segmentation

768 \(\times\) 576

30

CHASE-DBI [82]

2012

Retinal vascular segmentation

999 \(\times\) 960

28

HRF [83]

2013

Retinal vascular segmentation

3304 \(\times\) 2336

45

GLAS [72]

2016

Glandular segmentation

567 \(\times\) 430 \(\sim\)775 \(\times\) 522

165

MoNuSeg [73]

2017

Nuclear segmentation of multiple organs

1000 \(\times\) 1000

30

DSB18 [84]

2018

Nuclear segmentation

\(\sim\)

670

TNBC [85]

2018

Nuclear segmentation

512 \(\times\) 512

50

IDRiD [86]

2018

Segmentation of fundus lesions

4288 \(\times\) 2848

516

DDR [87]

2019

Segmentation of fundus lesions

512 \(\times\) 512

757

PanNuke [88]

2019

Multiple organ pan cancer cell segmentation

256 \(\times\) 256

7904

Brain US [89]

2019

Ventricular septum segmentation

512\(\times\) 512

1629

Kvasir-SEG [90]

2020

Gastrointestinal polyp segmentation

332 \(\times\) 487\(\sim\)1920 \(\times\) 1072

1000

TM-EM3000 [91]

2021

Corneal endothelial cell segmentation

266 \(\times\) 480

184

PROMISE12 [92]

2012

Prostate segmentation

\(\sim\)

100

BTCV [37]

2015

Abdominal organ segmentation

512 \(\times\) 512\(\times *\)

50

BCV [41]

2015

Abdominal organ segmentation

\(\sim\)

30

ACDC [93]

2018

Cardiac segmentation

\(\sim\)

150

BraTS [94]

2018

Brain tumor segmentation

240 \(\times\) 240 \(\times\) 155

285

MSD [38]

2018

Decathlon Division

\(\sim\)

2633

LiTS [60]

2019

Liver tumor segmentation

512 \(\times\) 512\(\times *\)

131

KiTS19 [95]

2019

Renal tumor segmentation

\(\sim\)

210

SegTHOR [43]

2019

Chest organ segmentation

\(\sim\)

40

Thorax-85 [42]

2021

Chest organ segmentation

\(\sim\)

85