Precise laminae segmentation based on neural network for robot-assisted decompressive laminectomy.

Journal: Computer methods and programs in biomedicine
PMID: 34391999

Abstract

BACKGROUND AND OBJECTIVE: The decompressive laminectomy is one of the most common operations to treat lumbar spinal stenosis by removing the laminae above the spinal nerve. Recently, an increasing number of robots are deployed during the surgical process to reduce the burden on surgeons and to reduce complications. However, for the robot-assisted decompressive laminectomy, an accurate 3D model of laminae from a CT image is highly desired. The purpose of this paper is to precisely segment the laminae with fewer calculations.

Authors

  • Qian Li
    Emergency and Critical Care Center, Department of Emergency Medicine, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, China.
  • Zhijiang Du
    State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China. duzj01@hit.edu.cn.
  • Hongjian Yu
    State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China. Electronic address: yuhongjian99@126.com.

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