Image-Based Flexible Endoscope Steering

Manually steering the tip of a flexible endoscope to navigate through an endoluminal path relies on the physician’s dexterity and experience. In this paper we present the realization of a robotic flexible endoscope steering system that uses the endoscopic images to control the tip orientation towards the direction of the lumen. Two image-based control algorithms are investigated, one is based on the optical flow and the other is based on the image intensity. Both are evaluated using simulations in which the endoscope was steered through the lumen. The RMS distance to the lumen center was less than 25% of the lumen width. An experimental setup was built using a standard flexible endoscope, and the image-based control algorithms were used to actuate the wheels of the endoscope for tip steering. Experiments were conducted in an anatomical model to simulate gastroscopy. The image intensity- based algorithm was capable of steering the endoscope tip through an endoluminal path from the mouth to the duodenum accurately. Compared to manual control, the robotically steered endoscope performed 68% better in terms of keeping the lumen centered in the image

04251 -- Imaging Beyond the Pinhole Camera

From 13.06.04 to 18.06.04, the Dagstuhl Seminar 04251 ``Imaging Beyond the Pin-hole Camera. 12th Seminar on Theoretical Foundations of Computer Vision\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Optical Flow on Moving Manifolds

Optical flow is a powerful tool for the study and analysis of motion in a sequence of images. In this article we study a Horn-Schunck type spatio-temporal regularization functional for image sequences that have a non-Euclidean, time varying image domain. To that end we construct a Riemannian metric that describes the deformation and structure of this evolving surface. The resulting functional can be seen as natural geometric generalization of previous work by Weickert and Schn\"orr (2001) and Lef\`evre and Baillet (2008) for static image domains. In this work we show the existence and wellposedness of the corresponding optical flow problem and derive necessary and sufficient optimality conditions. We demonstrate the functionality of our approach in a series of experiments using both synthetic and real data.Comment: 26 pages, 6 figure