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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 🎧 Subscribe & Stay Updated! ✅ Get expert insights on Imaging Informatics, AI/ML, Interoperability, and more →    / @nagelsconsulting   🔔 Hit the bell to stay notified of new episodes! 📚 Expand Your Knowledge on Imaging Informatics 🌐 Website: https://www.nagelsconsulting.com 🎓 Courses: https://learn.nagelsconsulting.com 🔗 Connect with Us on LinkedIn →   / nagels-consulting