Original research: utilization of a convolutional neural network for automated detection of lytic spinal lesions on body CTs.

Journal: Skeletal radiology
PMID:

Abstract

OBJECTIVE: To develop, train, and test a convolutional neural network (CNN) for detection of spinal lytic lesions in chest, abdomen, and pelvis CT scans.

Authors

  • Connie Y Chang
    Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, YAW 6, Boston, MA, 02114, USA. cychang@mgh.harvard.edu.
  • Florian A Huber
    Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland. Electronic address: florian.huber@usz.ch.
  • Kaitlyn J Yeh
    Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, YAW 6, Boston, MA, 02114, USA.
  • Colleen Buckless
    Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, YAW 6, Boston, MA, 02114, USA.
  • Martin Torriani
    Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, YAW 6048, Boston, MA, 02114, USA. mtorriani@mgh.harvard.edu.