Region Flow: A Multi-stage Method for Colonoscopy Tracking
Co-located optical and virtual colonoscopy images provide important clinical information during routine colonoscopy procedures. Tracking algorithms that rely on image features to align virtual and optical images can fail when they encounter blurry image sequences. This is a common occurrence in colonoscopy images, when the endoscope touches a wall or is immersed in fluid. We propose a region-flow based matching algorithm to determine the large changes between images that bridge such interruptions in the visual field. The region flow field is used as the means to limit the search space for computing corresponding feature points; a sequence of refining steps is performed to identify the most reliable and accurate feature point pairs. The feature point pairs are then used in a deformation based scheme to compute the final camera parameters. We have successfully tested this algorithm on four clinical colonoscopy image sequences containing anywhere from 9-57 consecutive blurry images. Two additional tabletop experiments were performed to quantitatively validate the algorithm: the endoscope was moved along a slightly curved path by 24 mm and along a straight path by 40 mm. Our method reported errors within 1-5％ in these experiments.
colonoscopy tracking failure recovery image matching
Jianfei Liu Kalpathi R.Subramanian Terry S.Yoo
Department of Computer Science,The University of North Carolina at Charlotte, Charlotte, NC, 28223, Office of High Performance Computing and Communications, National Library of Medicine, NIH, Bethesda
国际会议
北京
英文
505-513
2010-09-01（万方平台首次上网日期，不代表论文的发表时间）