Endoscopic bladder image registration using sparse graph cuts

Abstract

Video endoscopy is one of the standard clinical procedures for visually detecting lesions on the internal wall of human bladders. In order to facilitate the diagnosis, it is helpful to build panoramic maps by registering consecutive images from the video sequence. We show how to efficiently reduce the computation time of graph cut based image registration by an order of magnitude. The number of nodes in a graph is greatly reduced using spatial image properties in order to minimize the loss of information. The set of edges in this sparse graph is obtained by applying a watershed transform on the set of nodes. This graph reduction has negligible negative effects on image registration quality compared to a dense graph cut, so that visually coherent panoramic maps of bladder walls can be built. Results demonstrate that the method improves the registration accuracy and reduces the computation time of other endoscopic bladder image registration methods. This work is an important step towards real time map construction.