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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

The priorities of and approaches by industry when it comes to protecting human identity in medical images can differ from those of governments. This session will examine those priorities and approaches with presentations by various industry groups.

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

Welcome and Recap

David Clunie, MBBS, PixelMed, Inc.

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. 

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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, Inc.