A parallel network utilizing local features and global representations for segmentation of surgical instruments.

Journal: International journal of computer assisted radiology and surgery
Published Date: Oct 1, 2022

Abstract

PURPOSE: Automatic image segmentation of surgical instruments is a fundamental task in robot-assisted minimally invasive surgery, which greatly improves the context awareness of surgeons during the operation. A novel method based on Mask R-CNN is proposed in this paper to realize accurate instance segmentation of surgical instruments.

Authors

  • Xinan Sun
    Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, 135 Yaguan Road, Tianjin, 300350, China.
  • Yuelin Zou
    Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, 135 Yaguan Road, Tianjin, 300350, China.
  • Shuxin Wang
    a Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education , Tianjin University , Tianjin , China.
  • He Su
    Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, 135 Yaguan Road, Tianjin, 300350, China. suhe@tju.edu.cn.
  • Bo Guan
    Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, 135 Yaguan Road, Tianjin, 300350, China.

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