CSDL Home C CVPRW 2008 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Anchorage, AK, USA
June 23, 2008 to June 28, 2008
Kalpathi Subramanian , The University of North Carolina at Charlotte, USA
Terry Yoo , National Library of Medicine, NIH Bethesda, Maryland, USA
Jianfei Liu , The University of North Carolina at Charlotte, USA
In this paper, we focus on the robustness and stability of our algorithm to plot the position of an endoscopic camera (during a colonoscopy procedure) on the corresponding pre-operative CT scan of the patient. The colon has few topological landmarks, in contrast to bronchoscopy images, where a number of registration algorithms have taken advantage of features such as anatomical marks or bifurcations. Our method estimates the camera motion from the optic-flow computed from the information contained in the video stream. Optic-flow computation is notoriously susceptible to errors in estimating the motion field. Our method relies on the following features to counter this, (1) we use a small but reliable set of feature points (sparse optic-flow field) to determine the spatio-temporal scale at which to perform optic-flow computation in each frame of the sequence, (2) the chosen scales are used to compute a more accurate dense optic flow field, which is used to compute qualitative parameters relating to the main motion direction, and (3) the sparse optic-flow field and the main motion parameters are then combined to estimate the camera parameters. A mathematical analysis of our algorithm is presented to illustrate the stability of our method, as well as comparison to existing motion estimation algorithms. We present preliminary results of using this algorithm on both a virtual colonoscopy image sequence, as well as a colon phantom image sequence.
Kalpathi Subramanian, Terry Yoo, Jianfei Liu, "A stable optic-flow based method for tracking colonoscopy images", CVPRW, 2008, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops 2008, pp. 1-8, doi:10.1109/CVPRW.2008.4562990