Hybrid 3D/2D Convolutional Neural Network for Hemorrhage Evaluation on Head CT.

Journal: AJNR. American journal of neuroradiology
Published Date: Jul 26, 2018

Abstract

BACKGROUND AND PURPOSE: Convolutional neural networks are a powerful technology for image recognition. This study evaluates a convolutional neural network optimized for the detection and quantification of intraparenchymal, epidural/subdural, and subarachnoid hemorrhages on noncontrast CT.

Authors

  • P D Chang
    From the Departments of Radiology (P.D.C., E.K., M.T., R.H., M.-Y.S., D.C.).
  • E Kuoy
    From the Departments of Radiology (P.D.C., E.K., M.T., R.H., M.-Y.S., D.C.).
  • J Grinband
    Department of Radiology (J.G.), Columbia University, New York, New York.
  • B D Weinberg
    Department of Radiology (B.D.W.), Emory University School of Medicine, Atlanta, Georgia.
  • M Thompson
    From the Departments of Radiology (P.D.C., E.K., M.T., R.H., M.-Y.S., D.C.).
  • R Homo
    From the Departments of Radiology (P.D.C., E.K., M.T., R.H., M.-Y.S., D.C.).
  • J Chen
    Neurosurgery (J.C.).
  • H Abcede
    Neurology (H.A., M.S., W.Y.), University of California Irvine.
  • M Shafie
    Neurology (H.A., M.S., W.Y.), University of California Irvine.
  • L Sugrue
    Departments of Radiology (P.D.C., L.S., C.H.), University of California, San Francisco, California.
  • C G Filippi
    Department of Radiology (C.G.F.), North Shore University Hospital, Long Island, New York.
  • M-Y Su
    Departments of Radiology (M.B., M.K., M.-Y.S., D.C.).
  • W Yu
    Neurology (H.A., M.S., W.Y.), University of California Irvine.
  • C Hess
    Departments of Radiology (P.D.C., L.S., C.H.), University of California, San Francisco, California.
  • D Chow
    Departments of Radiology (M.B., M.K., M.-Y.S., D.C.) chowd3@uci.edu.

Keywords

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