Skin Lesion Segmentation

Skin lesion segmentation, the automated identification of skin lesion boundaries in images, is crucial for early skin cancer detection and improved diagnosis. Current research heavily utilizes deep learning, focusing on hybrid architectures that combine convolutional neural networks (CNNs) with transformers to leverage both local and global image features, and exploring lightweight models for efficient deployment on mobile devices. These advancements aim to improve segmentation accuracy, address challenges like blurry boundaries and varying lesion sizes, and ultimately enhance the speed and accessibility of skin cancer diagnosis.