FedDermaSeg: Federated Learning for Dermatological Image Segmentation
Skin cancer is a major global health concern, and early detection and accurate lesion delineation are important for effective diagnosis and treatment planning. Automated skin lesion analysis can assist dermatologists, with lesion segmentation serving as a fundamental step in computer-aided diagnostic systems. Conventional deep learning-based segmentation models typically rely on centralized training, where images and their corresponding segmentation masks are collected on a central server. Such data aggregation raises privacy concerns in medical applications and requires substantial centralized computational resources. To address these limitations, we investigate the feasibility of federa...
| Authors | Anabik Pal, Ganesh Patidar, Bikash Santra |
|---|---|
| Primary category | cs.CV |
| Published | 6 October 2026 |
| Last updated at source | 6 October 2026 |
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