Region flow: a multi-stage method for colonoscopy tracking

  • Authors:

  • Jianfei Liu;Kalpathi R. Subramanian;Terry S. Yoo

  • Affiliations:

  • Department of Computer Science, The University of North Carolina at Charlotte, Charlotte, NC;Department of Computer Science, The University of North Carolina at Charlotte, Charlotte, NC;Office of High Performance Computing and Communications, National Library of Medicine, NIH, Bethesda, MD

  • Venue:
  • MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
  • Year:
  • 2010

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Abstract

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.