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Proceedings Paper

CT colonography: inverse-consistent symmetric registration of prone and supine inner colon surfaces
Author(s): Holger R. Roth; Jamie R. McClelland; Marc Modat; Thomas E. Hampshire; Darren J. Boone; Emma Helbren; Andrew Plumb; Mingxing Hu; Sebastien Ourselin; Steve Halligan; David J. Hawkes
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Paper Abstract

CT colonography interpretation is difficult and time-consuming because fecal residue or fluid can mimic or obscure polyps, leading to diagnostic errors. To compensate for this, it is normal practice to obtain CT data with the patient in prone and supine positions. Repositioning redistributes fecal residue and colonic gas; fecal residue tends to move, while fixed mural pathology does not. The cornerstone of competent interpretation is the matching of corresponding endoluminal locations between prone and supine acquisitions. Robust and accurate automated registration between acquisitions should lead to faster and more accurate detection of colorectal cancer and polyps. Any directional bias when registering the colonic surfaces could lead to incorrect anatomical correspondence resulting in reader error. We aim to reduce directional bias and so increase robustness by adapting a cylindrical registration algorithm to penalize inverse-consistency error, using a symmetric optimization. Using 17 validation cases, the mean inverse-consistency error was reduced significantly by 86%, from 3.3 mm to 0.45 mm. Furthermore, we show improved alignment of the prone and supine colonic surfaces, evidenced by a reduction in the mean-of-squared-differences by 43% overall. Mean registration error, measured at a sparse set of manually selected reference points, remained at the same level as the non-symmetric method (no significant differences). Our results suggest that the inverse-consistent symmetric algorithm performs more robustly than non-symmetric implementation of B-spline registration.

Paper Details

Date Published: 13 March 2013
PDF: 8 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 866912 (13 March 2013); doi: 10.1117/12.2007004
Show Author Affiliations
Holger R. Roth, Univ. College London (United Kingdom)
Jamie R. McClelland, Univ. College London (United Kingdom)
Marc Modat, Univ. College London (United Kingdom)
Thomas E. Hampshire, Univ. College London (United Kingdom)
Darren J. Boone, Univ. College London (United Kingdom)
Emma Helbren, Univ. College London (United Kingdom)
Andrew Plumb, Univ. College London (United Kingdom)
Mingxing Hu, Univ. College London (United Kingdom)
Sebastien Ourselin, Univ. College London (United Kingdom)
Steve Halligan, Univ. College London (United Kingdom)
David J. Hawkes, Univ. College London (United Kingdom)

Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)

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