国家癌症研究所成像数据共享:向成像人工智能的透明度,可复制性和可扩展性

Andrey Fedorov¹, William J R Longabaugh¹, David Pot¹+18

• ¹From the Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 399 Revolution Dr, Somerville, MA 02145 (A.F., D.K., V.K.T., C.C., R.K.); Institute for Systems Biology, Seattle, Wash (W.J.R.L., D.L.G.); General Dynamics Information Technology, Rockville, Md (D.P.); PixelMed Publishing, Bangor, Pa (D.A.C.); Isomics, Cambridge, Mass (S.D.P.); Departments of Radiology (C.B.) and Pathology (M.D.H.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass; Fraunhofer MEVIS, Bremen, Germany (A.H., D.P.S.); Radical Imaging, Boston, Mass (R.L.); Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Mass (H.J.W.L.A., D.B.); Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, the Netherlands (H.J.W.L.A., D.B.); Frederick National Laboratory for Cancer Research, Rockville, Md (T.P., U.W.); and National Cancer Institute, Bethesda, Md (K.F., E.K.).