Using Spatio-Temporal Hybrid Features for Detecting Bleeding Point in Laparoscopic Surgery

Research on video bleeding has become a hot topic in the computer-assisted surgery. We do further research to directly detect the bleeding point. Locating bleeding point can help surgeons stop bleeding quickly. We propose a mixed RCNN model based on faster RCNN for bleeding point detection in the laparoscopic surgery videos. And we make three contributions: (1) we propose an idea for hemostasis support system which can more directly assist the surgeons. (2) we show the blood's optical flow to improve bleeding point detection. (3) both arterial and venous bleeding can be detected. Experimental results on our laparoscopic surgery video datasets show that our approach performs very well in the bleeding point location and recognition.