An Automatic and Robust Visual SLAM Method for Intra-Abdominal Environment Reconstruction

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  • Wei Guodong
    School of Computer Science and Technology, Changchun University of Science and Technology
  • Shi Weili
    School of Computer Science and Technology, Changchun University of Science and Technology Zhongshan Institute, Changchun University of Science and Technology
  • Feng Guanyuan
    School of Computer Science and Technology, Changchun University of Science and Technology Zhongshan Institute, Changchun University of Science and Technology
  • Ao Yu
    School of Computer Science and Technology, Changchun University of Science and Technology Zhongshan Institute, Changchun University of Science and Technology
  • Miao Yu
    School of Computer Science and Technology, Changchun University of Science and Technology Zhongshan Institute, Changchun University of Science and Technology
  • He Wei
    School of Computer Science and Technology, Changchun University of Science and Technology Zhongshan Institute, Changchun University of Science and Technology
  • Chen Tao
    Department of General Surgery, Nanfang Hospital, Southern Medical University
  • Wang Yao
    Department of General Surgery, Zhongshan City People’s Hospital
  • Ji Bai
    Department of Hepatobiliary and Pancreatic Surgery, The First Hospital of Jilin University
  • Jiang Zhengang
    School of Computer Science and Technology, Changchun University of Science and Technology Zhongshan Institute, Changchun University of Science and Technology

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<p>Three-dimensional (3D) surface reconstruction is used to solve the problem of the narrow field of view in laparoscopy. It can provide surgeons or computer-assisted surgery systems with real-time complete internal abdominal anatomy. However, rapid changes in image depth, less texture, and specular reflection pose a challenge for the reconstruction. It is difficult to stably complete the reconstruction process using feature-based simultaneous localization and mapping (SLAM) method. This paper proposes a robust laparoscopic 3D surface reconstruction method using SLAM, which can automatically select appropriate parameters for stereo matching and robustly find matching point pairs for laparoscope motion estimation. The changing trend of disparity maps is used to predict stereo matching parameters to improve the quality of the disparity map. Feature patch extraction and tracking are selected to replace feature point extraction and matching in motion estimation, which reduces its failure and interruption in feature-based SLAM. The proposed feature patch matching method is suitable for parallel computing, which can improve its computing speed. Evaluation results on public in vivo and ex vivo porcine abdominal video data show the efficiency and robustness of our 3D surface reconstruction approach.</p>

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