CVF/CVPR Medical Computer Vision Workshop


Mathias Unberath (Johns Hopkins University), Yuyin Zhou (University of California, Santa Cruz), Nicolas Padoy (University of Strasbourg, France), Tal Arbel (McGill University, Canada), Qi Dou (The Chinese University of Hong Kong), Vasileios Belagiannis (Otto von Guericke University Magdeburg)


06/19/2022 (full day)

Our workshop is featured in Computer Vision News!

The event was featured in CVPR Daily!

Our event was featured in Best of CVPR again!

The talks can still be watched below.


The CVPR MCV workshop provides a unique forum for researchers and developers in academia, industry and healthcare to present, discuss and learn about cutting-edge advances in machine learning and computer vision for medical image analysis and computer assisted interventions. The workshop offers a venue for potential new collaborative efforts, encouraging more dataset and information exchanges for important clinical applications.

The ultimate goal of the MCV workshop is to bring together stakeholders interested in leveraging medical imaging data, machine learning and computer vision algorithms to build the next generation of tools and products to advance image-based healthcare. It is time to deliver!

The program features invited talks from leading researchers from academia and industry and clinicians. There will be no paper submissions at this year's workshop.

Schedule (US Central Time)

8:00 AM , Welcome and Opening Remarks

Morning Session:

  • 8:00 AM - 10:00 AM , Session 1

  • Moderators: Mathias Unberath (in-person), Nicolas Padoy (virtual), Qi Dou (virtual)

    1. Kensaku Mori, Nagoya University, Japan (virtual)

AI-based endoscopic procedure – Current and Future

    1. Ender Konukoglu, ETH Zurich, Switzerland (virtual)
      Towards robust and trustworthy AI for medical imaging

    2. Ben Glocker, Imperial College London, UK (virtual)
      Safety nets in medical imaging AI

  • Coffee Break (10:00 AM - 10:30 AM)

  • 10:30 AM - 12:30 PM , Session 2

  • Moderators: Vasileios Belagiannis (virtual), Yuyin Zhou (virtual)

    1. Xiaoxiao Li, University of British Columbia, Canada (virtual)
      Advancing AI in Healthcare with More and Diverse Data via Federated Learning

    2. Ismail Ben Ayed, École de Technologie Supérieur, Canada (virtual)
      Leveraging Unlabeled Data

    3. Pablo Arbelaez, Universidad de los Andes, Colombia (in person)
      AI for Global Health

    4. Mert Sabuncu, Cornell Tech, USA (in person)
      Neural Encoding Models

Lunch Break (12:30 PM - 1:30 PM)

Afternoon Session:

  • 1:30 PM - 3:30 PM , Session 3

  • Moderators: Mathias Unberath (in person), Yuyin Zhou (virtual)

    1. Oliver Taubmann, Siemens Healthineers, Germany (in person)
      Vision in the CT Workflow

    2. Ulas Bagci , Northwestern, USA (virtual)
      Trustworthy AI for Imaging-based Diagnoses

    3. Jie Ying Wu, Vanderbilt University, USA (in person)
      Modeling robotic surgery

    4. Daniel Rückert, TU Munich, Germany (in person)
      Learning clinically useful information from medical images

3:30 PM , Closing Remarks


Xiaoxiao Li

University of British Columbia (UBC)

Ender Konukoglu


Jie Ying Wu

Vanderbilt University

Ben Glocker

Imperial College London

Kensaku Mori

Nagoya University

Oliver Taubmann

Siemens Healthineers

Mert Sabuncu

Cornell University

Pablo Arbelaez

University of Los Andes (Colombia)

Ismail Ben Ayed

Ecole de Technologie Superieure (ETS)

Ulas Bagci

Northwestern University

Daniel Rueckert

TU Munich and Imperial College London


Kensaku Mori (Nagoya University) - "AI-based endoscopic procedure – Current and Future"

Ender Konukoglu (ETH Zurich ) - "Towards robust and trustworthy AI for medical imaging"

Ben Glocker (Imperial College London) - "Safety nets in medical imaging AI"

Xiaoxiao Li (University of British Columbia) - "Advancing AI in Healthcare with More and Diverse Data via Federated Learning"

Ismail Ben Ayed (École de Technologie Supérieur) - "Leveraging Unlabeled Data"

Pablo Arbelaez (Universidad de los Andes) - "AI for Global Health"

Mert Sabuncu (Cornell Tech) - "Neural Encoding Models"

Oliver Taubmann (Siemens Healthineers) - "Vision in the CT Workflow"

Ulas Bagci (Northwestern University) - "Trustworthy AI for Imaging-based Diagnoses"

Jie Ying Wu (Vanderbilt University, USA) - "Modeling robotic surgery"

Daniel Rückert (TU Munich) - "Learning clinically useful information from medical images"