(she/her/hers)
University of California, San Diego
Robot Vision, Medical Robotics, Computer Vision for Automation, Surgical Scene Understanding
Shan Lin is a Postdoctoral Researcher at the University of California, San Diego. Here she is leading an effort to develop semantically assisted endoscopic video reasoning, tissue deformation tracking, and 3D reconstruction, as well as medical imaging analysis, and virtual reality for surgical training. She received her M.S. degree in Electrical Engineering from Vanderbilt University, Nashville, in 2017, and the Ph.D. degree in Electrical and Computer Engineering from the University of Washington, Seattle, in 2021.
Toward Surgical Scene Understanding: A Semantic-aware Surgical Perception Framework for Endoscopic Tissue Segmentation, Tracking, and Reconstruction
Minimally invasive robotic surgery has gained increasing popularity as it provides many benefits to patients, but it also introduces perception challenges to surgeons due to a limited field of view and reduced depth cues. Therefore, achieving accurate and robust tracking and reconstruction of the surgical scene is a critical for safer surgery, and ultimately toward autonomous robotic surgery. In this presentation, a novel, comprehensive surgical perception framework, that integrates geometric and semantic information to facilitate data association, 3D reconstruction, and tracking of endoscopic scenes, will be introduced. This framework builds 3D map that contains semantic information of different anatomies in deformable surgical scenes, which could benefit endoscopic surgical navigation and other related tasks in the future.