National Experts Chart Roadmap For AI In Medical Imaging

A foundational research roadmap for artificial intelligence (AI) in medical imaging was published this week in the journal Radiology. The report was based on outcomes from a workshop to explore the future of AI in medical imaging, featuring experts in medical imaging, and hosted at the National Institutes of Health in Bethesda, Maryland. The workshop was co-sponsored by the National Institute of Biomedical Imaging and Bioengineering, the Radiological Society of North America, the American College of Radiology, and the Academy for Radiology and Biomedical Imaging Research.

The collaborative report underscores the commitment by standards bodies, professional societies, governmental agencies, and private industry to work together to accomplish a set of shared goals in service of patients, who stand to benefit from the potential of AI to bring about innovative imaging technologies.

The report describes innovations that would help to produce more publicly available, validated and reusable data sets against which to evaluate new algorithms and techniques, noting that to be useful for machine learning these data sets require methods to rapidly create labeled or annotated imaging data. The roadmap of priorities for AI in medical imaging research includes:

Article

Langlotz, CP, et al. A Roadmap for Foundational Research on Artificial Intelligence in Medical Imaging: From the 2018 NIH/RSNA/ACR/The Academy Workshop. Radiology. April 16, 2019.

Co-authors of the report with Curtis P. Langlotz were Bibb Allen, M.D.; Bradley J. Erickson, M.D., Ph.D.; Jayashree Kalpathy-Cramer, Ph.D.; Keith Bigelow, B.A.; Tessa S. Cook, M.D., Ph.D.; Adam E. Flanders, M.D.; Matthew P. Lungren, M.D., M.P.H.; David S. Mendelson, M.D.; Jeffrey D. Rudie, M.D., Ph.D.; Ge Wang, Ph.D.; and Krishna Kandarpa, M.D., Ph.D.

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