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Session 2: Tools for Conventional Approaches to De-Identification
11:00 am -
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11:
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50 pm EDT
In this session, speakers will share methods currently in use for medical de-identification.
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11:00 am - 11:10 am Fred Prior, PhD, University of Arkansas for Medical Sciences
Setting the Stage
11:10 am - 11:20 am Michael Rutherford, MS, University of Arkansas for Medical Sciences
The Tools of TCIA: Standardizing Zero-Tolerance De-identification
11:20 am - 11:30 am Stephen Moore, MS, Washington University School of Medicine in St. Louis XNAT
XNAT Platform: Image De-identification
11:30 am - 11:50 am Panel Discussion
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Session chair: William Parker, MD, University of British Columbia
12:00 pm - 12:10 pm William Parker, MD, University of British Columbia
12:10 pm - 12:20 pm Haridimos Kondylakis, PhD, Institute Institute of Computer Science, Foundation of Research & Technology (FORTH) Data
Data Infrastructures for AI in Medical Imaging: A report on the experiences of five EU projects
12:20 pm - 12:30 pm Christian Ludwigs, MSc, Aigora GmbH
Legal Framework and Best Practices for Medical Image De-Identification in the EU
12:30 pm - 12:40 pm DiscussionDiscussion
Session 4: Industry Panel on Image De-Identification
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- Abraham Gutman, MS, AG Mednet
Advances in Medical Imaging De-Identification and the Impact of Regulatory Constraints - Dan Marcus, PhD, Flywheel
The Flywheel Platform for Intelligent Image Anonymization - 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 - Jiri Dobes, PhD, John Snow Labs
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10:20 am - 10:30 am Tom Bisson, PhD, Charité Universitätsmedizin Berlin
Anonymization of Whole Slide Images in in Histopathology for Research and Education
10:30 am - 10:40 am David Gutman, MD, PhD, Emory University
Image DePHI and the DSA: Open Source tools for Histology Image De-Identification
10:40 am - 11:00 am Panel Discussion
Session 6: De-facing
11:00 am - 12:00 pm EDT
This session will focus on balancing the risks of removing potentially reconstructable facial information in head and neck cross-sectional images, also called de-facing, with the diminished utility of these images caused by restricted access to them.
Session chair: Ying Xiao, PhD, Hospital of the University of Pennsylvania
11:00 am - 11:10 am Ying Xiao, PhD, University of Pennsylvania
11:10 am - 11:20 am Christopher Schwarz, PhD, Mayo Clinic
Face Recognition and De-Identification of Research Brain Images with mri_reface
11:20 am - 11:30 am Douglas Greve, PhD, MGH/Harvard
MIDEFACE: Minimally Invasive Defacing
11:30 am - 11:50 am Panel Discussion
Break 11:50 am - 12:00 pm
Session 7: The Role of AI in Image
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De-Identification
12:00 pm - 12:50 pm
In this session, researchers discuss the utility of AI algorithms in image de-identification.
Session chair: Judy Wawira Gichoya, MD, Emory University
12:00 pm - 12:10 pm Judy Wawira Gichoya, MD, Emory University
12:10 pm - 12:20 pm George Shih, MD, Weill Cornell Medical College
Pixel De-Identification Using AI
12:20 pm - 12:30 pm Adrienne Kline, MD, PhD, Northwestern University PyLogik
PyLogik: An open-source resource for medical image de-identification
12:30 pm - 12:50 pm pm Panel Discussion
Session 8: NCI MIDI Datasets and Pipeline
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Session chair: Keyvan Farahani, PhD, National Heart, Lung, and Blood Institute & National Cancer Institute, National Institutes of Health
12:50 pm - 1:00 pm Keyvan Farahani, PhD
1:00 pm - 1:10 pm Fred Prior, PhD, University of Arkansas for Medical Sciences
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Synthetic Data for De-Identification Testing
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The MIDI Datasets
1:10 pm - 1:20 pm Ben Kopchick, PhD, Deloitte Consulting
Building a cloud-based MIDI pipeline
1:20 pm - 1:50 pm Panel Discussion
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