Virtual Workshop on Medical Image De-Identification (MIDI)
Do you work with medical images that contain potentially sensitive data elements? Do these image formats include DICOM? If so, register to attend this workshop! You’ll learn about:
- the best practices/recommendations for conducting sensitive data removal, known as “de-identification,” as identified by the MIDI Task Group (convened by NCI).
- approaches to conventional image de-identification in the United States, the European Union, and Canada.
- approaches to image de-identification by industry.
- the roles that statistical risk analysis, de-facing (or de-identification of facial features), and artificial intelligence (AI) play in de-identification.
Medical imaging data is valuable for disease diagnose, treatment, and research. However, medical images often contain sensitive information such as personally identifiable information or protected health information. Thus, de-identifying this information is essential to allow data sharing.
This workshop will be hosted by the NCI Center for Biomedical Informatics and Information Technology (CBIIT). For information about the workshop, please contact the NCI CBIIT MIDI Group.
Dr. Farahani is the senior program director of data science, imaging, and AI at the National Heart, Lung, and Blood Institute. He's on detail at NCI CBIIT as a program director for imaging informatics and serves as the federal lead for several imaging projects, including the MIDI Initiative.
- UCSC Genome Browser and BRCA Exchange: Data Resources for Clinical Variant InterpretationJune 06, 2023PhenoDB, a Phenotypic and Genotypic Data Sharing ToolJune 09, 2023Human Tumor Atlas Network (HTAN) Summer MeetingJune 12, 2023 - June 13, 2023