Artificial Intelligence for Neuroimaging and Musculoskeletal Radiology: Overview of Current Commercial Algorithms.

Journal: Seminars in roentgenology
Published Date: Mar 31, 2023

Abstract

There is a rapidly increasing number of artificial intelligence (AI) products cleared by the Food and Drug Administration (FDA) for quantification, identification, and even diagnosis in clinical radiology. This review article aims to summarize the landscape of current commercial software products in neuroimaging and musculoskeletal radiology. We will discuss key applications, provide an overview of current FDA cleared products, and summarize relevant peer reviewed publications of these products when available.

Authors

  • Elisa R Berson
    Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT.
  • Mariam S Aboian
    From the Department of Radiology and Biomedical Imaging (Y.D., J.H.S., H.T., R.H., N.W.J., T.P.C., M.S.A., C.M.A., S.C.B., R.R.F., S.Y.H., Y.S., R.A.H., M.H.P., B.L.F.) and Institute for Computational Health Sciences (J.H.S., M.G.K., H.T., D.L., K.A.Z., D.H.), University of California, San Francisco, 550 Parnassus Ave, San Francisco, CA 94143; Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, Calif (Y.D.); and Department of Radiology, University of California, Davis, Sacramento, Calif (L.N.).
  • Ajay Malhotra
    Department of Radiology and Biomedical Imaging, Yale University School of Medicine, Box 208042, Tompkins East 2, 333 Cedar St, New Haven, CT, 06520-8042, USA. ajay.malhotra@yale.edu.
  • Seyedmehdi Payabvash
    Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.

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