Composed Vision-Language Retrieval for Skin Cancer Case Search via Joint Alignment of Global and Local Representations

ArXi:2603.09108v1 Announce Type: cross Medical image retrieval aims to identify clinically relevant lesion cases to diagnostic decision making, education, and quality control. In practice, retrieval queries often combine a reference lesion image with textual descriptors such as dermoscopic features. We study composed vision-language retrieval for skin cancer, where each query consists of an image to text pair and the database contains biopsy-confirmed, multi-class disease cases.