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Updated: Nov 7, 2025

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
Published on: September 25, 2019
Construction of a Machine Learning Dataset through Collaboration: The RSNA 2019 Brain CT Hemorrhage Challenge
Adam E Flanders1, Luciano M Prevedello1, George Shih1
1Department of Radiology/Division of Neuroradiology, Thomas Jefferson University Hospital, 132 S Tenth St, Suite 1080B Main Building, Philadelphia, PA 19107 (A.E.F.); Department of Radiology, The Ohio State University, Columbus, Ohio (L.M.P.); Department of Radiology, Weill Cornell Medical College, New York, NY (G.S.); Department of Radiology, Stanford University, Stanford, Calif (S.S.H.); Department of Radiology and Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Mass (J.K.); Quantitative Sciences Unit, Stanford University, Stanford, Calif (R.B.); Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, Calif (J.T.M.); MD.ai, New York, NY (A.S.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Department of Radiology, Stanford University, Stanford, Calif (M.P.L.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (G.C.); Faculty of Health and Medical Sciences, University of Western Australia, Perth, Australia (L. Cala); Advanced Diagnostic Imaging, Clínica DAPI, Curitiba, Brazil (L. Coelho); Department of Radiology, University of Washington, Seattle, Wash (M.M.); Department of Radiology, Baylor College of Medicine, Houston, Tex (F.M., C.L.); Department of Radiology, University of Ottawa, Ottawa, Canada (E.M.); Department of Radiology & Biomedical Imaging, Yale University, New Haven, Conn (I.I., V.Z.); Department of Medical Imaging, Gold Coast University Hospital, Southport, Australia (O.M.); Department of Neuroradiology, University of Utah Health Sciences Center, Salt Lake City, Utah (L.S.); Department of Radiology and Medical Imaging, University of Virginia Health, Charlottesville, Va (D.J.); Division of Neuroradiology, University of Texas Southwestern Medical Center, Dallas, Tex (A.A.); Department of Radiology, Albert Einstein Healthcare Network, Philadelphia, Pa (R.K.L.); and Department of Radiology, SUNY Downstate Medical Center, Albany, NY (J.N.).
Abstract:
This dataset is composed of annotations of the five hemorrhage subtypes (subarachnoid, intraventricular, subdural, epidural, and intraparenchymal hemorrhage) typically encountered at brain CT.

