Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging.

Journal: Magnetic resonance in medicine
Published Date: Jul 21, 2017

Abstract

PURPOSE: To describe and evaluate a new fully automated musculoskeletal tissue segmentation method using deep convolutional neural network (CNN) and three-dimensional (3D) simplex deformable modeling to improve the accuracy and efficiency of cartilage and bone segmentation within the knee joint.

Authors

  • Fang Liu
    The First Clinical Medical College of Gannan Medical University, Ganzhou 341000, Jiangxi Province, China.
  • Zhaoye Zhou
    Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, USA.
  • Hyungseok Jang
    Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
  • Alexey Samsonov
    Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
  • Gengyan Zhao
    Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
  • Richard Kijowski
    Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.

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