{Reference Type}: Editorial
{Title}: Summary of the National Cancer Institute 2023 Virtual Workshop on Medical Image De-identification-Part 1: Report of the MIDI Task Group - Best Practices and Recommendations, Tools for Conventional Approaches to De-identification, International Approaches to De-identification, and Industry Panel on Image De-identification.
{Author}: Clunie D;Prior F;Rutherford M;Moore S;Parker W;Kondylakis H;Ludwigs C;Klenk J;Lou B;O'Sullivan LT;Marcus D;Dobes J;Gutman A;Farahani K;
{Journal}: J Imaging Inform Med
{Volume}: 0
{Issue}: 0
{Year}: 2024 Jul 12
暂无{DOI}: 10.1007/s10278-024-01182-y
{Abstract}: De-identification of medical images intended for research is a core requirement for data-sharing initiatives, particularly as the demand for data for artificial intelligence (AI) applications grows. The Center for Biomedical Informatics and Information Technology (CBIIT) of the US National Cancer Institute (NCI) convened a virtual workshop with the intent of summarizing the state of the art in de-identification technology and processes and exploring interesting aspects of the subject. This paper summarizes the highlights of the first day of the workshop, the recordings, and presentations of which are publicly available for review. The topics covered included the report of the Medical Image De-Identification Initiative (MIDI) Task Group on best practices and recommendations, tools for conventional approaches to de-identification, international approaches to de-identification, and an industry panel.