Deep learning method for segmentation of rotator cuff muscles on MR images.

Journal: Skeletal radiology
Published Date: Apr 1, 2021

Abstract

OBJECTIVE: To develop and validate a deep convolutional neural network (CNN) method capable of (1) selecting a specific shoulder sagittal MR image (Y-view) and (2) automatically segmenting rotator cuff (RC) muscles on a Y-view. We hypothesized a CNN approach can accurately perform both tasks compared with manual reference standards.

Authors

  • Giovanna Medina
    Department of Orthopedics, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA.
  • Colleen G Buckless
    Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, YAW 6048, Boston, MA, 02114, USA.
  • Eamon Thomasson
    Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street - YAW 6048, Boston, MA, 02114, USA.
  • Luke S Oh
    Department of Orthopedics, Massachusetts General Hospital, Harvard Medical School, 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.

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