De-identification in Medical Imaging: What You Need to Know | Nagels Consulting

With the rise of Machine Learning (ML) in Medical Imaging, training AI models requires real-world data—but how do we ensure Protected Health Information (PHI) stays private?
De-identification in Medical Imaging: What You Need to Know | Nagels Consulting

In this episode of Imaging Informatics Unplugged, we sit down with Luke Bideaux, BSRT, RT (R), CIIP, President & CEO of Vega Imaging Informatics, to break down:
✅ The challenges of de-identifying medical imaging data
✅ Why DICOM metadata & pixel data need special handling
✅ The best tools & techniques for PHI protection
✅ When re-identification is necessary

🎙 About Our Guest:
Luke Bideaux has worked in leadership roles at multiple imaging vendors & provider-based organizations in the U.S. He’s a published author, industry advocate, and expert in imaging informatics, interoperability, & data privacy. He trained in radiography at Mayo Clinic (Rochester, MN) and holds certifications from ARRT & ABII.

🔗 Connect with Luke & Vega Informatics:
🌐 Website: https://vegainformatics.com
📢 LinkedIn:   / lukebideaux  

Chapters
00:00 Introduction to Vega Informatics and Core Services
02:15 The Importance of De-identification in Data
06:34 Challenges in De-identifying Medical Imaging Data
13:08 Re-identification: When and Why It Matters
24:10 Tools and Techniques for Effective De-identification
29:01 Conferences and Future Engagements

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