Skin Lesion Segmentation Using Unet With A Topology Term in Loss Function

This paper proposes a novel method to improve skin lesion segmentation by incorporating topology difference into the loss function. We conducted experiments on the widely used HAM10000 dataset. Our results show that integrating the topology difference term enhances performance compared to the U-Net model trained without this additional loss component. (Abstract)