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Challenges Related to Artificial Intelligence Research in Medical Imaging and the Importance of Image Analysis
Luciano M Prevedello1, Safwan S Halabi1, George Shih1
1Department of Radiology, The Ohio State University Wexner Medical Center, 395 West 12th Ave, 4th Floor, Room 422, Columbus, OH 43210 (L.M.P.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (S.S.H.); Department of Radiology, Weill Cornell Medical College, New York, NY (G.S.); Department of Diagnostic Radiology, University of Texas-MD Anderson Cancer Center, Houston, Tex (C.C.W.); Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, Calif (M.D.K.); Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Ga (F.H.C.); Department of Radiology, Mayo Clinic, Rochester, Minn (B.J.E.); Department of Radiology and Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Mass (J.K.C.); Department of Radiology, Brigham and Women's Hospital, Massachusetts General Hospital and BWH Center for Clinical Data Science, Boston, Mass (K.P.A.); and Department of Radiology, Thomas Jefferson University Hospital, Philadelphia, Pa (A.E.F.).
Abstract:
In recent years, there has been enormous interest in applying artificial intelligence (AI) to radiology. Although some of this interest may have been driven by exaggerated expectations that the technology can outperform radiologists in some tasks, there is a growing body of evidence that illustrates its limitations in medical imaging. The true potential of the technique probably lies somewhere in the middle, and AI will ultimately play a key role in medical imaging in the future. The limitless power of computers makes AI an ideal candidate to provide the standardization, consistency, and dependability needed to support radiologists in their mission to provide excellent patient care. However, important roadblocks currently limit the expansion of this field in medical imaging. This article reviews some of the challenges and potential solutions to advance the field forward, with focus on the experience gained by hosting image-based competitions.
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