AI RESEARCH
CapCLIP: A Vision-Language Representation Alignment Approach for Wireless Capsule Endoscopy Analysis
arXiv CS.CV
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ArXi:2605.08493v1 Announce Type: new Wireless capsule endoscopy (WCE) enables non-invasive visual assessment of the small bowel, but its clinical utility is constrained by the large volume of frames generated per examination and the difficulty of recognising subtle abnormalities under highly variable imaging conditions. Existing learning-based approaches for WCE are predominantly vision-only, often confined to narrow pathology sets, and show limited transfer across datasets and centres. To address these limitations, this study.