Foot Ulcer Segmentation

Foot ulcer segmentation, the automated identification of wound boundaries in images, aims to improve the diagnosis and treatment of diabetic foot ulcers (DFUs) and other chronic wounds. Current research focuses on developing and refining deep learning models, particularly encoder-decoder architectures like U-Net and variations incorporating EfficientNet backbones or HarDNet modifications, to achieve accurate segmentation even with limited annotated data. These advancements leverage techniques such as cross-domain augmentation and synthetic image generation to overcome data scarcity challenges, ultimately improving the efficiency and objectivity of wound assessment and potentially impacting patient care and clinical research.