Prone to supine CT colonography registration using a landmark and intensity composite method

Authors:
Thomas E. Hampshire;Holger R. Roth;Darren J. Boone;Greg Slabaugh;Steve Halligan;David J. Hawkes
Affiliations:
Centre for Medical Image Computing, University College London, London, UK;Centre for Medical Image Computing, University College London, London, UK;Centre for Medical Imaging, University College Hospital, London, UK;Department of Computing, City University, London, UK;Centre for Medical Imaging, University College Hospital, London, UK;Centre for Medical Image Computing, University College London, London, UK
Venue:
MICCAI'12 Proceedings of the 4th international conference on Abdominal Imaging: computational and clinical applications
Year:
2012

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Abstract

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.