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

Medical image retrieval aims to identify clinically relevant lesion cases to support 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. We propose a transformer based framework that l

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ethics.ai (10 March 2026), “Composed Vision-Language Retrieval for Skin Cancer Case Search via Joint Alignment of Global and Local Representations,” evidence record 7454, https://ethics.ai/record/7454 (originally published by arXiv).

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