Fig. 5
From: Boundary-enhanced sparse transformer for generalizable and accurate medical image segmentation
Comparison of segmentation performance among the top four Dice-scoring models on the ISIC 2018 dataset. Columns (a)–(f) present the original image, ground-truth, and the predicted results from Swin-UNet, MedFormer, BRAU-Net++, and our model, respectively.
