Normalized Distance Along the Colon Centerline: A Method for Correlating Polyp Location On CT Colonography and Optical Colonoscopy

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. © 2012 Springer-Verlag.

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

A fully automated, anatomically-based procedure is developed for the coregistration of prone and supine scans in
computed tomographic colonography (CTC). Haustral folds, teniae coli and other anatomic landmarks are extracted
from the segmented colonic lumen and serve as the basis for iterative optimization-based matching of the colonic
surfaces. The three-dimensional coregistration is computed efficiently using a two-dimensional filet representation of the
colon. The circumferential positions of longitudinal structures such as teniae coli are used to estimate a rotational
prone-to-supine deformation, haustral folds give a longitudinal (stretching) deformation, while other landmarks and
anatomical considerations are used to constrain the allowable deformations. The proposed method is robust to changes in
the detected anatomical landmarks such as the obscuration or apparent bifurcation of teniae coli. Preliminary validation
in the Walter Reed CTC data set shows excellent coregistration accuracy-57 manually identified features (such as
polyps and diverticula) are automatically coregistered with a mean three-dimensional error of 16.4 mm. In phantom
studies, 210 fiducial pairs are coregistered to a mean three-dimensional error of 8.6 mm. The coregistration allows points
of interest in one scan to be automatically located in the other, leading to an expected improvement in per-patient read
time and a significant reduction in the cost of CTC.

Fully automated prone-supine coregistration in computed tomographic colonography

Computed tomographic (CT) colonography is a technique for detecting bowel cancer and potentially precancerous polyps. CT imaging is performed on the cleansed and insufflated bowel in order to produce a virtual endoluminal representation similar to optical colonoscopy. Because fluids and stool can mimic pathology, images are acquired with the patient in both prone and supine positions. Radiologists then match endoluminal locations visually between the two acquisitions in order to determine whether pathology is real or not. This process is hindered by the fact that the colon can undergo considerable deformation between acquisitions. Robust and accurate automated registration between prone and supine data acquisitions is therefore pivotal for medical interpretation, but a challenging problem. The method proposed in this thesis reduces the complexity of the registration task of aligning the prone and supine CT colonography acquisitions. This is done by utilising cylindrical representations of the colonic surface which reflect the colon's specific anatomy. Automated alignment in the cylindrical domain is achieved by non-rigid image registration using surface curvatures, applicable even when cases exhibit local luminal collapses. It is furthermore shown that landmark matches for initialisation improve the registration's accuracy and robustness. Additional performance improvements are achieved by symmetric and inverse-consistent registration and iteratively deforming the surface in order to compensate for differences in distension and bowel preparation. Manually identified reference points in human data and fiducial markers in a porcine phantom are used to validate the registration accuracy. The potential clinical impact of the method has been evaluated using data that reflects clinical practise. Furthermore, correspondence between follow-up CT colonography acquisitions is established in order to facilitate the clinical need to investigate polyp growth over time. Accurate registration has the potential to both improve the diagnostic process and decrease the radiologist's interpretation time. Furthermore, its result could be integrated into algorithms for improved computer-aided detection of colonic polyps.

Registration of prone and supine CT colonography images and its clinical application

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Registration of prone and supine CT colonography images and its clinical application