Prone to Supine CT Colonography Registration Using a Landmark and Intensity Composite Method

Hampshire, T.E., Roth, H.R., Boone, D.J., Slabaugh, G.G., Halligan, S. & Hawkes, D.J. (2012). Prone to Supine CT Colonography Registration Using a Landmark and Intensity Composite Method. In: H Yoshida, DJ Hawkes & MW Vannier (Eds.), Abdominal Imaging. Computational and Clinical Applications. (pp. 1-9). Springer. ISBN 978-3-642-33611-9

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Matching corresponding location between prone and supine acquisitions for CT colonography (CTC) is essential to verify the existence of a polyp, which can be a difficult task due to the considerable deformations that will often occur to the colon during repositioning of the patient. This can induce error and increase interpretation time. We propose a novel method to automatically establish correspondence between the two acquisitions. A first step segments a set of haustral folds in each view and determines correspondence via a labelling process using a Markov Random Field (MRF) model. We show how the landmark correspondences can be used to non-rigidly transform a 2D source image derived from a conformal mapping process on the 3D endoluminal surface mesh to achieve full surface correspondence between prone and supine views. This can be used to initialise an intensity-based non-rigid B-spline registration method which further increases the accuracy. We demonstrate a statistically significant improvement over the intensity based non-rigid B-spline registration by using the composite method.

Item Type: Book Section
Additional Information: © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords: CT colonography, image registration
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RC Internal medicine
Divisions: School of Informatics > Department of Computing

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