A SLAM framework based spinal endoscopic localization method

Abstract

Percutaneous endoscopy has become an important part of spinal surgery. During endoscopic operation, image navigation is an important technique to ensure accuracy and reliability. Optical navigation is the most widely used technique for endoscopic surgery, but it has some limitations such as inability to locate the non-rigid end of the instrument and limiting the operating space of the doctor. In order to solve these problems, a navigation strategy based on the idea of Simultaneous Localization And Mapping (SLAM) algorithm is proposed in this paper. In this novel navigation strategy, the 3D reconstruction CT image was used to be the global point cloud map of the surgical environment, while the local point cloud was reconstructed using the endoscopic image, and a Structure From Motion(SFM) algorithm was adopted to locate the endoscope in the local space. Then, the position and pose of the endoscope in the global space was calculated via the registration of the local and global point clouds. The feasibility and effectiveness of the proposed method are verified by comparative experiments on the experimental platform of robot-assisted endoscopic spine surgery.