Pixels to Patients: Bridging CV State-of-Art with Clinical Impact

Clinical medicine represents one of the most demanding testbeds for computer vision, where methods must function reliably under distribution shifts, strict regulatory constraints, and high social impact. Despite rapid progress in foundation models, multimodal learning, and self-supervision, a persistent gap remains between state-of-the-art CV research and its safe, effective deployment in clinical practice. This workshop, 'Pixels to Patients: Bridging CV State-of-the-Art with Clinical Impact', will bring together leading researchers, clinicians, and industry partners to address this gap head-on. Core themes include adapting recent CV breakthroughs -foundation and vision-language models, domain adaptation, and data-efficient learning - to healthcare, and exporting lessons from clinical deployment - bias auditing, monitoring, and regulatory compliance - back to the broader CV community. The program will feature keynotes from pioneers in medical AI, oral and poster sessions, a Problem-Pitch track to seed benchmark challenges, and a panel on real-world deployment and interoperability. By positioning medicine not as a silo but as a proving ground for trustworthy, generalizable vision systems, this workshop aims to catalyze advances that resonate across safety-critical domains, from healthcare to robotics and beyond.