One to Many: Adaptive Instrument Segmentation via Meta Learning and Dynamic Online Adaptation in Robotic Surgical Video
Zixu Zhao Yueming Jin Bo Lu Chi-Fai Ng Qi Dou Yun-Hui Liu Pheng-Ann Heng Zixu Zhao Yueming Jin Bo Lu Chi-Fai Ng Qi Dou Yun-Hui Liu Pheng-Ann Heng
Surgical instrument segmentation in robot-assisted surgery (RAS) - especially that using learning-based models - relies on the assumption that training and testing videos are sampled from the same domain. However, it is impractical and expensive to collect and annotate sufficient data from every new domain. To greatly increase the label efficiency, we explore a new problem, i.e., adaptive instrume...