G-CASCADE: Efficient Cascaded Graph Convolutional Decoding for 2D Medical Image Segmentation

Benchmark Model Rank Results
medical-image-segmentation-on-chase-db1MERIT-GCASCADE#1DSC: 0.8267
medical-image-segmentation-on-chase-db1PVT-GCASCADE#2DSC: 0.8251
medical-image-segmentation-on-driveMERIT-GCASCADE#1mIoU: 0.7081F1 score: 0.8290Recall: 0.8281Specificity: 0.9844
medical-image-segmentation-on-drivePVT-GCASCADE#2mIoU: 0.697F1 score: 0.8210Recall: 0.83Specificity: 0.9822
medical-image-segmentation-on-isic-2018PVT-GCASCADE#2DSC: 91.51mIoU: 86.53
medical-image-segmentation-on-miccai-2015-multi-atlas-abdomen-labeling-challengeMERIT-GCASCADE#2Avg DSC: 84.54Avg HD: 10.38
medical-image-segmentation-on-miccai-2015-multi-atlas-abdomen-labeling-challengePVT-GCASCADE#5Avg DSC: 83.28Avg HD: 15.83
medical-image-segmentation-on-acdc-2MERIT-GCASCADE#7Avg DSC: 92.23
medical-image-segmentation-on-acdc-2PVT-GCASCADE#11Avg DSC: 91.95
medical-image-segmentation-on-cvc-colondbPVT-GCASCADE#8mean Dice: 0.8261mIoU: 0.7460
medical-image-segmentation-on-cvc-clinicdbPVT-GCASCADE#14mean Dice: 0.9468mIoU: 0.9018
retinal-vessel-segmentation-on-chase-db1MERIT-GCASCADE#14F1 score: 0.8267mIOU: 0.7050Sensitivity: 0.8493
retinal-vessel-segmentation-on-chase-db1PVT-GCASCADE#15F1 score: 0.8251mIOU: 0.7024Sensitivity: 0.8584
medical-image-segmentation-on-kvasir-segPVT-GCASCADE#15mean Dice: 0.9274mIoU: 0.8790
retinal-vessel-segmentation-on-driveMERIT-GCASCADE#15F1 score: 0.8290Accuracy: 0.9707mIoU: 0.7081sensitivity: 0.8281…
retinal-vessel-segmentation-on-drivePVT-GCASCADE#18F1 score: 0.8210Accuracy: 0.9689mIoU: 0.6970sensitivity: 0.83…