The Center for Biomedical Informatics and Information Technology of the National Cancer Institute (NCI) presented a virtual Medical Imaging De-Identification (MIDI) workshop focused on public sharing of imaging data.
The primary emphasis of the workshop wass on medical images with accompanying data elements, especially those in formats in which the data elements are embedded, particularly DICOM.
The goals of the two-day workshop were to:
- 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
| Date | Slides | Recording |
|---|---|---|
| 5/22/2023 | Day 1 Recording | |
| 5/23/2023 | Day 2 Slide Deck | Day 2 |
Slide Presentations
Information about the workshop program chairs, agenda, and speaker bios are at https://events.cancer.gov/nci/midi-workshop.
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 |
|---|---|---|
| Keyvan Farahani, National Heart, Lung, and Blood Institute, National Institutes of Health | Welcome & Introduction | https://docs.google.com/presentation/d/1vZQDBSNhBAZFPtJwOUE_i6NgOu6IL1ZMmIWZPaCctLA/edit?usp=sharing |
| David Clunie, PixelMed | Report of the MIDI Task Group | https://docs.google.com/presentation/d/1pccphYb-y-uHDgicrlXZxseKMxpKNTxE51pC3ChtewA/edit |
| Fred Prior | Setting the Stage | Emailed file |
| Michael Rutherford, University of Arkansas for Medical Sciences | The Tools of TCIA: Standardizing Zero-Tolerance De-identification | Emailed file |
| Stephen Moore, Washington University School of Medicine in St. Louis | XNAT Platform: Image De-identification | https://docs.google.com/presentation/d/1roHkw48PbtV8n1agwPqtp0bBIingypxF-VNyYjI45Ss/edit?usp=sharing |
| Chairperson: Willam Parker, University of British Columbia | International Approaches to Image De-Identification | |
| William Parker | Medical Data De-ID A Canadian Perspective | https://www.icloud.com/keynote/001sv_DNMidQcXVnlQaAvsnmw#NIH_MIDI_Session |
| Haridimos Kondylakis, 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 | Legal framework and best practices for medical image de-identification in the EU | |
| Chairperson: Juergen Klenk, Deloitte Consulting | Industry Panel on Image De-Identification | |
| Juergen Klenk | Introductory Remarks to the Industry Panel | Emailed file |
| Bob Lou, Google | Medical imaging de-identification on both images and text using AI models | https://docs.google.com/presentation/d/12TnPrlyAxNYvWbFv7y3KXZynQBHG2N5QPehQ5ah7RmY/edit#slide=id.g839f2df6fc_2_102 Also emailed file |
| Lawrence (Tony) O’Sullivan, IBIS | Optimizing and Automating Radiology Data De-identification Workflows | https://docsend.com/view/234ee2vubhyg7eyy |
| Dan Marcus, Flywheel | The Flywheel Platform for Intelligent Image Anonymization | https://docs.google.com/presentation/d/1kMd6w4w8Au3o4XjEF49y-aceg-ssTS0HKH-bsu5rZzI/edit?usp=sharing |
| Jiri Dobes, John Snow Labs | Automated Medical Data De-Identification and Obfuscation | https://johnsnowlabs-my.sharepoint.com/:p:/p/jiri/EdbJq7F3wB9Lhgf6B8QH_V8BFqmuqqGVNN3NJq5XgvX9Dg?e=20s6j2 |
| Abraham Gutman, AG Mednet, Inc. | Advances in Medical Imaging De-Identification and the Impact of Regulatory Constraints | https://www.dropbox.com/s/3wa8jbrzhj6pu2s/AG%20De-ID%20Panel.pptx?dl=0 |
