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Endoluminal surface registration for CT colonography using Haustral Fold Matching

Hampshire, T; Roth, HR; Helbren, E; Plumb, A; Boone, D; Slabaugh, G; Halligan, S; (2013) Endoluminal surface registration for CT colonography using Haustral Fold Matching. Medical Image Analysis , 17 (8) pp. 946-958. 10.1016/j.media.2013.04.006. Green open access

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Abstract

Computed Tomographic (CT) colonography is a technique used for the detection of bowel cancer or potentially precancerous polyps. The procedure is performed routinely with the patient both prone and supine to differentiate fixed colonic pathology from mobile faecal residue. Matching corresponding locations is difficult and time consuming for radiologists due to colonic deformations that occur during patient repositioning. We propose a novel method to establish correspondence between the two acquisitions automatically. The problem is first simplified by detecting haustral folds using a graph cut method applied to a curvature-based metric applied to a surface mesh generated from segmentation of the colonic lumen. A virtual camera is used to create a set of images that provide a metric for matching pairs of folds between the prone and supine acquisitions. Image patches are generated at the fold positions using depth map renderings of the endoluminal surface and optimised by performing a virtual camera registration over a restricted set of degrees of freedom. The intensity difference between image pairs, along with additional neighbourhood information to enforce geometric constraints over a 2D parameterisation of the 3D space, are used as unary and pair-wise costs respectively, and included in a Markov Random Field (MRF) model to estimate the maximum a-posteriori fold labelling assignment. The method achieved fold matching accuracy of 96.0% and 96.1% in patient cases with and without local colonic collapse. Moreover, it improved upon an existing surface-based registration algorithm by providing an initialisation. The set of landmark correspondences is used to non-rigidly transform a 2D source image derived from a conformal mapping process on the 3D endoluminal surface mesh. This achieves full surface correspondence between prone and supine views and can be further refined with an intensity based registration showing a statistically significant improvement (p<0.001p<0.001), and decreasing mean error from 11.9mm11.9mm to 6.0mm6.0mm measured at 1743 reference points from 17 CTC datasets.

Type: Article
Title: Endoluminal surface registration for CT colonography using Haustral Fold Matching
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.media.2013.04.006
Publisher version: http://dx.doi.org/10.1016/j.media.2013.04.006
Language: English
Additional information: © 2013 The Authors. Published by Elsevier B.V. All rights reserved. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 2.0 License. The license allows you to copy, distribute, and transmit the work. However, you must attribute the work to the author (but not in any way that suggests that they endorse you or your use of the work). Furthermore you cannot use the work for commercial purposes without prior permission of the author, and you may not alter, transform, or build upon this work.
Keywords: CT colonography, Markov random field, Haustral fold, Landmark, Registration
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Department of Imaging
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1395575
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