2024 Medical Imaging De-Identification (MIDI-B) Challenge Workshop - Oct 24th, 2024
David Clunie
https://wiki.nci.nih.gov/display/MIDI/2024+MIDI-B+Challenge+Workshop
https://cbiit.webex.com/cbiit/j.php?MTID=m33e2783bc9a2256fd136cec55a5ba751
The National Cancer Institute (NCI) has completed the Medical Image De-Identification Benchmark (MIDI-B) Challenge in collaboration with Sage Bionetworks and the Medical Imaging Computing and Computer Assisted Interventions Society (MICCAI 2024). The goal of the MIDI-B Challenge was to benchmark image de-identification tools against a reference data set, a large and diverse set of standardized clinical Digital Imaging and Communications in Medicine (DICOM) images with synthetic identifiers. The challenge addressed the fundamental requirements of protecting patient privacy and preserving the research value of the data for sharing medical images through public data commons. Given the recent NIH mandate for data sharing and the pivotal role of data in training AI models, accurate, automated, and scalable methods for image de-identification are desirable.
The goals of the workshop are to:
- Share the MIDI-B Challenge design.
- Describe the MIDI synthetic dataset and the evaluation method.
- Learn about the de-identification algorithms and results by the challenge finalist.
Co-chairs:
Keyvan Farahani, Ph.D., National Heart, Lung, and Blood Institute, NIH
Granger Sutton, Ph.D., National Cancer Institute, NIH
Michael Ventresca
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