医学成像中人工智能研究的相关挑战及图像分析竞赛的重要性
Challenges Related to Artificial Intelligence Research in Medical Imaging and the Importance of Image Analysis Competitions.
作者信息
Prevedello Luciano M, Halabi Safwan S, Shih George, Wu Carol C, Kohli Marc D, Chokshi Falgun H, Erickson Bradley J, Kalpathy-Cramer Jayashree, Andriole Katherine P, Flanders Adam E
机构信息
Department 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.).
出版信息
Radiol Artif Intell. 2019 Jan 30;1(1):e180031. doi: 10.1148/ryai.2019180031. eCollection 2019 Jan.
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.
近年来，将人工智能（AI）应用于放射学引起了极大的兴趣。尽管这种兴趣部分可能是由于人们过度期望该技术在某些任务中能超越放射科医生，但越来越多的证据表明了其在医学成像中的局限性。该技术的真正潜力可能处于两者之间，并且人工智能最终将在未来的医学成像中发挥关键作用。计算机的无限能力使人工智能成为提供标准化、一致性和可靠性的理想选择，以支持放射科医生完成提供优质患者护理的使命。然而，目前一些重要的障碍限制了该领域在医学成像中的扩展。本文回顾了推进该领域发展的一些挑战和潜在解决方案，重点关注举办基于图像的竞赛所获得的经验。
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