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Page History
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The primary emphasis of the workshop wass on was on medical images with accompanying data elements, especially those in formats in which the data elements are embedded, particularly DICOM.
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- Share best practices and recommendations for medical imaging de-identification, as identified by the MIDI Task Group convened by the NCI.
- Learn about approaches to conventional image de-identification in the United States, the European Union, and Canada.
- Discuss approaches to image de-identification by industry.
- Explore the roles of statistical risk analysis, de-facing, and AI in de-identification.
Recordings
Slide Presentations
The workshop agenda and speaker bios are on the workshop website.
Some documents on this page are not Section 508 compliant. To receive a compliant document, please email NCI CBIIT MIDI Group.
| Speaker | Presentation Title | Slides |
|---|---|---|
| Day 1 | ||
| Keyvan Farahani, PhD, National Heart, Lung, and Blood Institute, National Institutes of Health | Welcome & Introduction |
https://docs.google.com/presentation/d/1vZQDBSNhBAZFPtJwOUE_i6NgOu6IL1ZMmIWZPaCctLA/edit?usp=sharing
| Session 1: |
|---|
| Report of the MIDI Task Group - Best Practices and Recommendations | ||
|---|---|---|
| David Clunie, MBBS, PixelMed | Report of the MIDI Task Group |
Session 2: Tools for |
|---|
Conventional Approaches to De-Identification Chairperson, Fred Prior, PhD | ||
|---|---|---|
| Fred Prior, PhD | Setting the Stage |
| Michael Rutherford, MS, University of Arkansas for Medical Sciences | The Tools of TCIA: Standardizing Zero-Tolerance De-identification |
| Stephen Moore, MS, Washington University School of Medicine in St. Louis | XNAT Platform: Image De-identification |
Session 3: International Approaches to De-Identification Chairperson: |
|---|
William Parker, University of British Columbia |
|---|
| William Parker, MD | Medical Data De-ID - A Canadian Perspective |
| Parker Slides | ||
| Haridimos Kondylakis, PhD, Institute of Computer Science, Foundation of Research & Technology (FORTH) | Data Infrastructures for AI in Medical Imaging: A report on the experiences of five EU projects | |
| Christian Ludwigs, MSc, Aigora GmbH | Legal framework and best practices for medical image de-identification in the EU |
Session 4: Industry Panel on Image De-Identification Chairperson: Juergen Klenk, PhD, Deloitte Consulting | ||
|---|---|---|
| Juergen Klenk, PhD | Introductory Remarks to the Industry Panel |
| Bob Lou, MD, Google | Medical imaging de-identification on both images and text using AI models |
Also emailed file
| Lawrence (Tony) O’Sullivan, MS, IBIS | Optimizing and Automating Radiology Data De-identification Workflows |
| Dan Marcus, PhD, Flywheel | The Flywheel Platform for Intelligent Image Anonymization |
| Jiri Dobes, PhD, John Snow Labs | Automated Medical Data De-Identification and Obfuscation |
| Abraham Gutman, MS, AG Mednet, Inc. | Advances in Medical Imaging De-Identification and the Impact of Regulatory Constraints |
| Day 2 | ||
|---|---|---|
| Session 5: Pathology Whole Slide Image De-Identification | ||
| Adam Taylor, PhD, Sage Bionetworks | Pathology Whole Slide Image De-Identification | |
| Tom Bisson, PhD, Charité Universitätsmedizin Berlin | Anonymization of Whole Slide Images in in Histopathology for Research and Education | |
| David Gutman, MD, PhD, Emory University | Image DePHI and the DSA: Open Source tools for Histology Image DeIdentification | |
| Session 6: De-Facing | De-Facing | |
| Ying Xiao,PhD, Hospital of the University of Pennsylvania | Medical Image De-Facing and Clinical Research Data Sharing | |
| Christopher Schwarz, PhD, Mayo Clinic | Face Recognition and De-Identification of Research Brain Images with mri_reface | |
| Douglas Greve, PhD, MGH/Harvard | MIDEFACE: Minimally Invasive Defacing | |
| Session 7: The Role of AI in Image De-Identification | ||
| Judy Gichoya, MD, Emory University | ||
| George Shih, MD, Weill Cornell Medical College | Pixel De-Identification Using AI | |
| Adrienne Kline, MD, PhD, Northwestern University | PyLogik: An open-source resource for medical image de-identification | |
| Session 8: NCI MIDI Datasets and Pipeline | ||
| Keyvan Farahani, PhD | The Medical Image De-Identification Initiative (MIDI) | |
| Fred Prior, PhD | Synthetic Data for De-Identification Testing - The MIDI Datasets | |
| Ben Kopchick, PhD, Deloitte Consulting | Building a cloud-based MIDI pipeline |
