CT colonography (virtual colonoscopy)

Thin-section multi–detector row computed tomographic (CT) colonography is a powerful tool for the detection and classification of colonic lesions. Isotropic imaging (ie equal voxel size in all three planes) of the colon with thin collimation has become standard and provides high-quality multi-planar reformatted (MPR) images and three dimensional (3D) assessment of the entire colon, while allowing excellent visualisation of all other intra-abdominal organs.peer-reviewe

Detection of Polyps via Shape and Appearance Modeling

Presented at the MICCAI 2008 Workshop on Computational and Visualization Challenges in the New Era of Virtual Colonoscopy, September 6, 2008, New York, USA.This paper describes a CAD system for the detection of colorectal polyps in CT. It is based on stochastic shape and appearance modeling of structures of the colon and rectum, in contrast to the data-driven approaches more commonly found in the literature it derives predictive stochastic models for the features used for classification. The method makes extensive use of medical domain knowledge in the design of the models and in the setting of their parameters. The proposed approach was successfully tested on challenging datasets acquired under a protocol with little colonic preparation; such protocol reduces patient discomfort and potentially improves compliance

Preoperative staging of colorectal cancer using virtual colonoscopy: correlation with surgical results

The aim of this study was to evaluate the clinical usefulness of computed tomography colonography (CTC) in the preoperative staging in patients with abdominal pain for occlusive colorectal cancer (CRC) and to compare the results of CTC with the surgical ones

Focal Spot, Spring 1999

https://digitalcommons.wustl.edu/focal_spot_archives/1081/thumbnail.jp

Colon centreline calculation for CT colonography using optimised 3D opological thinning

CT colonography is an emerging technique for colorectal cancer screening. This technique facilitates noninvasive imaging of the colon interior by generating virtual reality models of the colon lumen. Manual navigation through these models is a slow and tedious process. It is possible to automate navigation by calculating the centreline of the colon lumen. There are numerous well documented approaches for centreline calculation. Many of these techniques have been developed as alternatives to 3D topological thinning which has been discounted by others due to its computationally intensive nature. This paper describes a fully automated, optimised version of 3D topological thinning that has been specifically developed for calculating the centreline of the human colon