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Medical Image Segmentation on MI-PMR

76.43Bladder Segmentation ScoreGeoProto
34.46645.360556.25567.1495May 11, 2026

Evaluation results

MethodLinks
GeoProtoBackbone=ResNet-101, Training Source=Abdominal CT, Evaluation Scenario=Cross-context, Few-shot Protocol=1-way 1-shot2026.0576.4359.4447.8361.24
RPTBackbone=ResNet-101, Training Source=Abdominal CT, Evaluation Scenario=Cross-context, Few-shot Protocol=1-way 1-shot2026.0566.1738.8426.9443.98
PMNetBackbone=ResNet-101, Training Source=Abdominal CT, Evaluation Scenario=Cross-context, Few-shot Protocol=1-way 1-shot2026.0557.0851.5444.8451.15
PATNetBackbone=ResNet-101, Training Source=Abdominal CT, Evaluation Scenario=Cross-context, Few-shot Protocol=1-way 1-shot2026.0556.546.9838.2247.23
IFABackbone=ResNet-101, Training Source=Abdominal CT, Evaluation Scenario=Cross-context, Few-shot Protocol=1-way 1-shot2026.0555.7738.0931.1641.67
SSL-ALPBackbone=ResNet-101, Training Source=Abdominal CT, Evaluation Scenario=Cross-context, Few-shot Protocol=1-way 1-shot2026.0554.2927.7619.9233.99
C-GraphBackbone=ResNet-101, Training Source=Abdominal CT, Evaluation Scenario=Cross-context, Few-shot Protocol=1-way 1-shot2026.0552.5548.4449.350.1
RobustEMDBackbone=ResNet-101, Training Source=Abdominal CT, Evaluation Scenario=Cross-context, Few-shot Protocol=1-way 1-shot2026.0544.9321.8120.0728.94
APM-MBackbone=ResNet-101, Training Source=Abdominal CT, Evaluation Scenario=Cross-context, Few-shot Protocol=1-way 1-shot2026.0543.0431.2641.1638.49
FAMNetBackbone=ResNet-101, Training Source=Abdominal CT, Evaluation Scenario=Cross-context, Few-shot Protocol=1-way 1-shot2026.0542.7827.0629.4433.09
ADNetBackbone=ResNet-101, Training Source=Abdominal CT, Evaluation Scenario=Cross-context, Few-shot Protocol=1-way 1-shot2026.0536.5125.3828.1430.01
GMRDBackbone=ResNet-101, Training Source=Abdominal CT, Evaluation Scenario=Cross-context, Few-shot Protocol=1-way 1-shot2026.0536.0822.3324.6127.67