P2P-CV @ WACV 2026 — Pixels to Patients

About the Workshop

Pixels to Patients (P2P-CV) is a full-day workshop dedicated to bridging the gap between computer vision research and its safe, effective deployment in real-world clinical practice.

Medical imaging is among the most socially impactful domains of computer vision, yet a persistent gap remains between research breakthroughs and their safe, effective use in real-world clinics. WACV, with its strong tradition in applied computer vision, is the ideal venue to address this translation gap.

This workshop positions healthcare as a case study for broader CV challenges that arise whenever algorithms move from the lab to deployment. Topics such as domain generalization, fairness and bias mitigation, foundation models, trustworthy and explainable AI, and human–AI collaboration are central not only to medical imaging but also to autonomous driving, robotics, and other safety-critical applications.

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Research Excellence

Cutting-edge computer vision methods for medical imaging

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Clinical Impact

Real-world deployment and patient care outcomes

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Collaboration

Bridging researchers, clinicians, and industry

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Trustworthy AI

Fairness, explainability, and safety in healthcare

Call for Papers

We invite original research contributions that not only present technical innovations but also critically engage with the challenges of translating computer vision from research into clinical practice.

Foundation Models

Pre-training, fine-tuning, and adaptation for data-scarce medical imaging environments

Vision-Language Learning

Multimodal learning for clinical decision support and automated reporting

Domain Adaptation

Improving robustness across scanners, sites, and patient populations

Clinical Deployment

Validation, monitoring, and continual learning in practice

Explainable AI

Ensuring safety, transparency, and interpretability

Fairness & Equity

Auditing and mitigating bias for diverse populations

Data-Efficient Training

Active, weak, and self-supervised learning approaches

Quantitative Biomarkers

Using vision models for novel biomarker discovery

Human-AI Systems

Collaborative interfaces and human-in-the-loop learning

Submission Tracks

1

Regular Papers

Length: Up to 8 pages (excluding references)

Type: Archival - Published in WACV 2026 Workshop Proceedings

Purpose: Complete, original research with clinical relevance discussions

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2

Extended Abstracts

Length: 2-4 pages (excluding references)

Type: Non-archival

Purpose: Preliminary work, ongoing research, or negative results

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3

Problem-Pitch Proposals

Length: 2 slides maximum

Type: Non-archival

Purpose: Clinicians/industry present clinical challenges seeking technical solutions

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Review Process

Double-blind peer review for Regular Papers and Extended Abstracts
Manuscripts must be fully anonymized (no author names, affiliations, or self-identifying references)
Problem-Pitch Proposals reviewed by organizers for clarity, impact, and collaboration potential
At least one presenting author must register for the workshop

Important Dates

All deadlines are 23:59 Anywhere on Earth (AoE)

CFP Release

October 2025

Submission Deadline

November 28, 2025

Notification to Authors

January 2, 2026

Poster Upload

January 30, 2026

Workshop Day

March 6, 2026

Program Overview

Full-day schedule (tentative)

09:00 - 09:10

Opening Remarks

Welcome and workshop introduction

09:10 - 09:50

Keynote 1: Prof. Bradley J. Erickson

Building Multidisciplinary Bridges for Medical AI

Mayo Clinic

09:50 - 10:30

Oral Session I

Accepted paper presentations

10:30 - 11:00

Coffee Break & Networking

11:00 - 11:30

Keynote 2: Prof. Chieh-Ju Chao

Intelligent Imaging Pipelines for Cardiology: From Algorithms to Outcomes

Mayo Clinic

11:30 - 12:30

Collaboration-Building Session

Problem-Pitch & Solution-Match

12:30 - 14:00

Lunch + Poster Session

14:00 - 14:30

Keynote 3: Dr. Kenneth Philbrick

Foundation Models in Health: Opportunities, Challenges, and Lessons from MedGemma

Google Research (Health AI)

14:30 - 15:15

Keynote 4: Prof. Nassir Navab

Research–Clinical Translation

TUM / Helmholtz Munich

15:15 - 15:30

Oral Session II

Accepted paper presentations

15:30 - 16:00

Coffee Break

16:00 - 16:45

Panel Discussion: Deployment in the Real World

Clinical Monitoring and Interoperability Standards

16:45 - 17:00

Closing Remarks

Keynote Speakers

Prof. Bradley J. Erickson

M.D., Ph.D.

Mayo Clinic

Professor of Radiology and Director of the Mayo Clinic AI Lab. His work focuses on quantitative imaging and computer-aided diagnosis, developing AI algorithms for disease detection, prognosis, and prediction of molecular markers.

Prof. Chieh-Ju Chao

M.D.

Mayo Clinic - Department of Cardiology

Develops intelligent imaging pipelines linking algorithmic insights to real-world outcomes in cardiology, bridging the gap between advanced CV techniques and clinical practice.

Dr. Kenneth Philbrick

Ph.D.

Google Research (Health AI)

Research lead for foundation models and multimodal learning in healthcare. His work includes the development of MedGemma and advancing the application of large language models in medicine.

Prof. Nassir Navab

Ph.D.

Technical University of Munich & Helmholtz Munich

Pioneer in medical augmented reality and surgical AI. Leads research on human–AI collaboration and computer-assisted interventions, with decades of experience translating research to practice.

Organizers

Workshop Chairs

Dr. Sahika Betul Yayli

M.D.

Mayo Clinic AI Lab

Postdoctoral Research Fellow specializing in medical computer vision, segmentation, radiology vision-language models, and active learning. Previously Senior AI/ML Engineer at Turkcell.

p2pcv.wacv@gmail.com

Prof. Bradley J. Erickson

M.D., Ph.D.

Mayo Clinic AI Lab

Professor of Radiology and Director of the Mayo Clinic AI Lab. Pioneer in quantitative imaging and computer-aided diagnosis.

bje@mayo.edu

Program Chairs

Dr. Bardia Khosravi

M.D., M.P.H., M.H.P.E.

Yale University

Radiology resident with extensive experience in full-stack development and machine learning, focusing on the intersection of radiology, AI, and medical education.

bardia.khosravi@yale.edu

Dr. Pouria Rouzrokh

M.D., M.P.H., M.H.P.E.

Yale University

Diagnostic Radiology resident applying machine learning to radiology imaging and clinical workflow optimization, exploring generative AI in education.

pouria.rouzrokh@yale.edu

Dr. Elham Mahmoudi

M.D., M.P.H.

Mayo Clinic AI Lab

Postdoctoral Research Fellow focusing on deep learning analysis of cardiac imaging and textual medical documents.

mahmoudi.elham@mayo.edu

Program Committee

Prof. Bradley J. Erickson (Mayo Clinic)
Prof. Chieh-Ju Chao (Mayo Clinic)
Prof. Nassir Navab (TUM)
Dr. Kenneth Philbrick (Google Research)
Kevin O'Donnell (Canon Medical)
Dr. Gian Marco Conte (Mayo Clinic)
Huzeyfe Ayaz (TUM)
Dr. Salih Beyaz (Baskent University)
Dr. Sahika Betul Yayli (Mayo Clinic)

Dr. Nicolo Pecco (San Raffaele Hospital)
Dr. Jaidip Jagtap (Mayo Clinic)
Dr. Amirali Khosravi (Mayo Clinic)
Dr. Elham Mahmoudi (Mayo Clinic)
Dr. Allison Scarbrough (Mayo Clinic)
Fatih Ibrahim Ozlugedik (TUM/Helmholtz)
Dr. Pouria Rouzrokh (Yale University)
Dr. Bardia Khosravi (Yale University)
Dr. Ersin Kilic (Nevsehir University)
Dr. Paulo Kuriki (UTSW)

Expected Outcomes & Impact

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Knowledge Exchange

Direct dialogue between CV researchers, clinicians, and industry leaders on practical deployment challenges

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Barrier Identification

Clear understanding of methodological, infrastructural, and regulatory obstacles to safe AI deployment

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New Collaborations

Problem-Pitch sessions catalyzing partnerships between those with clinical problems and technical solutions

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Archival Proceedings

Accepted papers published in official WACV 2026 workshop proceedings

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Robust & Equitable Systems

Focus on fairness, diversity, and accessibility across all deployment contexts

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Broader CV Impact

Insights applicable to autonomous driving, robotics, and other safety-critical AI applications

Contact & Information

Primary Contact

Dr. Sahika Betul Yayli, M.D.

Mayo Clinic AI Lab

pixels2patients@gmail.com

Workshop Details

Format: Full-Day Workshop

Expected Audience: 50-90 participants

Proceedings

Publication: Official WACV 2026 Workshop Proceedings

Review: Double-blind peer review