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Medical Image Segmentation research benchmarks – Page 26 · SOTA2 Research

Medical Image Segmentation

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

77.67DICE Score

6

Feb 26, 2026

Adaptformer + SAM-COBOT

0.873DSC

6

Feb 26, 2026

Adaptformer + SAM-COBOT

89.2DSC

6

Feb 26, 2026

Adaptformer + SAM-COBOT

96.4DSC

6

Feb 26, 2026

78.99Dice (WMH)

6

Feb 26, 2026

0.876Dice (CSF)

6

Feb 26, 2026

Liver Segmentation dataset (test)

3D-UNet w/ MC dropout

95Dice Coefficient

6

Feb 26, 2026

79.37F1 Score

6

Feb 26, 2026

89.7F1 Score

6

Feb 26, 2026

0.605mIoU

6

Feb 26, 2026

BE (Barrett's Esophagus) target

73.3IoU

6

Feb 26, 2026

input image 256x256

34.9Params (M)

6

Feb 26, 2026

NAMIC T2-w to T1-w (test)

83.64Dice

6

Feb 26, 2026

NAMIC T1-w to T2-w (test)

0.852Dice Coefficient

6

Feb 26, 2026

IXI PD-w to T2-w (test)

87.9Dice (DSC)

6

Feb 26, 2026

IXI T2-w to PD-w (test)

0.808Dice Coefficient

6

Feb 26, 2026

MSD Lung (test)

73.8Dice (Label 1)

6

May 22, 2026

89.5Dice

6

Feb 26, 2026

ColonTumor (external val)

70.05DSC

6

Feb 26, 2026

Spleen (external val)

89.37DSC

6

Feb 26, 2026

LiverTumor (external val)

0.491DSC

6

Feb 26, 2026

Liver (external val)

0.774DSC

6

Feb 26, 2026

Brain Tumor (external val)

67.26DSC

6

Feb 26, 2026

Prostate (external val)

86.01DSC

6

Feb 26, 2026

Hippocampus (external val)

0.81DSC

6

Feb 26, 2026

Page 26 of 34

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