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Updated: Oct 11, 2025

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Published on: July 11, 2025
RSNA-MICCAI Panel Discussion: 2. Leveraging the Full Potential of AI-Radiologists and Data Scientists Working
Marius George Linguraru1, Lena Maier-Hein1, Ronald M Summers1
1Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC (M.G.L.); Department of Computer Assisted Medical Interventions, German Cancer Research Centre, Heidelberg, Germany (L.M.H.); Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.); and Department of Radiology, University of Pennsylvania, 3400 Spruce St, 1 Silverstein, Philadelphia, PA 19104 (C.E.K.).
Abstract:
In March 2021, the Radiological Society of North America hosted a virtual panel discussion with members of the Medical Image Computing and Computer Assisted Intervention Society. Both organizations share a vision to develop radiologic and medical imaging techniques through advanced quantitative imaging biomarkers and artificial intelligence. The panel addressed how radiologists and data scientists can collaborate to advance the science of AI in radiology. Keywords: Adults and Pediatrics, Segmentation, Feature Detection, Quantification, Diagnosis/Classification, Prognosis/Classification © RSNA, 2021.
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