Page History
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Speaker | Presentation Title | Slides | |
---|---|---|---|
Day 1 | |||
Keyvan Farahani, National Heart, Lung, and Blood Institute, National Institutes of Health | Welcome & Introduction | ||
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: Willam Parker, University of British Columbia | International Approaches to Image De-Identification | ||
William Parker, MD | Medical Data De-ID A Canadian Perspective | Parker Slides | |
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 | |
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 | ||
Lawrence (Tony) O’Sullivan, MS, IBIS | Optimizing and Automating Radiology Data De-identification Workflows | O'Sullivan Slides | |
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 |