ROBOTICS ENGINEERING COLLOQUIUM SERIES

Dr. Shan Lin

University of California, San Diego

Exploring Robust Real-time Instrument Segmentation for Endoscopic Sinus Surgery

Friday September 10, 2021

2:00 PM - 3:00 PM

Virtual | Zoom: https://wpi.zoom.us/j/96621539032

Abstract: Vision-based surgical instrument segmentation, which aims to detect instrument regions in surgery images, is often a critical component for computer or robot-assisted surgical systems. While advanced algorithms including deep CNN models have achieved promising instrument segmentation results, several limitations remain unsolved: (1) The robustness and generalization ability of existing algorithms is still insufficient for challenging surgery images, and (2) deep networks usually come with high computation cost, which needed to be addressed for time-sensitive applications during surgery. In this talk, I will first introduce a lightweight CNN that can achieve better segmentation performance with less inference time on low-quality endoscopic sinus surgery videos. I will then introduce my recent work on domain adaptation for instrument segmentation, which aims to transfer the knowledge learned from relevant and labeled datasets for instrument segmentation on an unlabeled dataset. Finally, I will conclude with a discussion of future research directions in surgical video analysis that I find most exciting.

Biography: Shan Lin is a postdoctoral scholar at the Electrical and Computer Engineering department of the University of California San Diego, working with Prof. Michael Yip. She obtained her PhD in Electrical and Computer Engineering from the University of Washington in 2021. Her current research focuses on analyzing endoscopic videos for surgical robotics, as well as surgical scene reconstruction.