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DAY 1, May 22, 2023 (10:00 am to 2:00 pm EDT) 

Welcome and Opening Comments

Keyvan Farahani, PhD

Dr. Farahani is the senior program director of data science, imaging, and AI at the National Heart, Lung, and Blood Institute. He's on detail at NCI CBIIT as a program director for imaging informatics and serves as the federal lead for several imaging projects, including the MIDI Initiative.

Session 1: Report of the MIDI Task Group - Best Practices and Recommendations

Session Chair: David Clunie, MBBS, PixelMed, LLC

In this session, David Clunie, chair of the MIDI Task Group, will summarize the best practices and recommendations included in the task group's report, recently available in pre-print, followed by a question and answer period.

Session 2: Tools for Conventional Approaches to De-Identification

Session Chair: Fred Prior, PhD, University of Arkansas for Medical Sciences

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Estimated at 11:55-12:05 p.m.

Session 3: International Approaches to De-Identification

Session chair: Bill Parker, MD, DABR, FRCPC, University of British Columbia

This session will focus on requirements for de-identification outside of the United States.

Session 3: Industry Approaches to De-Identification

Session chair: Keyvan Farahani, PhD, Center for Biomedical Informatics and Information Technology, National Cancer Institute, National Institutes of Health

Industry has a role to play in de-identification, developing tools that protect human identity in medical images. This session will feature presentations by industry groups that examine their approaches and offerings.

Closing Remarks

David Clunie, MBBS, PixelMed, Inc.

DAY 2, May 23, 2023 (10:00 am to 2:00 pm EDT) 

Welcome and Recap

David Clunie, MBBS, PixelMed, LLC

Session 4: Statistical Risk Analysis of Indirect Identifiers in an Image Context

Session chair: Mark Elliot, PhD, University of Manchester

In this session, researchers will discuss how to analyze the re-identification risk of indirect identifiers in medical images.

Session 5: De-facing

Session chair: Ying Xiao, Ph.D. Hospital of the University of Pennsylvania

This session will focus on balancing the risks of removing potentially reconstructable facial information in head and neck cross-sectional images, also called de-facing, with the diminished utility of these images caused by restricted access to them. 

Break

Estimated at 11:50 a.m. - 12:00 p.m.

Session 6: The Role of Artificial Intelligence in De-Identification

Session chair: Judy Wawira Gichoya, MD, MS, Emory University

In this session, researchers discuss the utility and risk of using algorithms from machine learning (ML) and artificial intelligence (AI) to de-identify medical images.

Session 7: Panel Discussion

Session chair: Jürgen Klenk, PhD, Deloitte Consulting LLP

Discussion of the approaches and challenges identified during the workshop and opportunities for the future.

Closing Remarks

David Clunie, MBBS, PixelMed, LLC

Keyvan Farahani, NCI