Visionbased Virtual Fixtures Generation for RoboticAssisted Polyp Dissection Procedures Polyp dissection requires very accurate detection of the region of interest and highprecision cutting with adequate safety margins. Robotassisted polyp dissection is a solution to accomplish highquality intervention. This paper proposes a method to constrain the robot to follow an accurate dissection path based on Virtual Fixtures (VF). The VFs are created via specific control points obtained directly from images of the surgical scene and are updated by the vision algorithm. The VF constraints can autonomously adapt themselves to environment changing during the surgical intervention. The entire pipeline is validated through experiments on the da Vinci Research Kit (dVRK) robot.

An Efficient SpatialTemporal Polyp Detection Framework for Colonoscopy Video Recent computeraided polyp detection systems showed its effectiveness to decrease the polyp miss rate in colonoscopy operations, which is helpful to reduce colorectal cancer mortality. However, traditional polyp detection approaches suffer from the following drawbacks: low precision and sensitivity caused by the variance of polypu0027s appearance, and the system may not be able to detect polyps in real time due to the high computation complexity of the detection algorithms. To alleviate those problems, we introduce a realtime detection framework that incorporates spatial and temporal information extracted from colonoscopy videos. Our framework consists of the following three components: 1) we adopt Single Shot MultiBox Detector (SSD) to generate the proposal bounding boxes in each video frame. 2) Simultaneously, we compute optical flow from neighboring frames to extract temporal information and generate another group of polyp proposals with the temporal detection network. 3) At last, the final result is generated by a fusion module that connects the end of both streams. Experimental results on ETISLARIB dataset demonstrate that our proposed approach reaches the stateoftheart performance on polyp localization with realtime performance.