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Proceedings Paper

Computer-aided teniae coli detection using height maps from computed tomographic colonography images
Author(s): Zhuoshi Wei; Jianhua Yao; Shijun Wang; Ronald M. Summers
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Paper Abstract

Computed tomographic colonography (CTC) is a minimally invasive technique for colonic polyps and cancer screening. Teniae coli are three bands of longitudinal smooth muscle on the colon surface. They are parallel, equally distributed on the colon wall, and form a triple helix structure from the appendix to the sigmoid colon. Because of their characteristics, teniae coli are important anatomical meaningful landmarks on human colon. This paper proposes a novel method for teniae coli detection on CT colonography. We first unfold the three-dimensional (3D) colon using a reversible projection technique and compute the two-dimensional (2D) height map of the unfolded colon. The height map records the elevation of colon surface relative to the unfolding plane, where haustral folds corresponding to high elevation points and teniae to low elevation points. The teniae coli are detected on the height map and then projected back to the 3D colon. Since teniae are located where the haustral folds meet, we break down the problem by first detecting haustral folds. We apply 2D Gabor filter banks to extract fold features. The maximum response of the filter banks is then selected as the feature image. The fold centers are then identified based on piecewise thresholding on the feature image. Connecting the fold centers yields a path of the folds. Teniae coli are finally extracted as lines running between the fold paths. Experiments were carried out on 7 cases. The proposed method yielded a promising result with an average normalized RMSE of 5.66% and standard deviation of 4.79% of the circumference of the colon.

Paper Details

Date Published: 8 March 2011
PDF: 8 pages
Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 79631G (8 March 2011); doi: 10.1117/12.878257
Show Author Affiliations
Zhuoshi Wei, National Institutes of Health (United States)
Jianhua Yao, National Institutes of Health (United States)
Shijun Wang, National Institutes of Health (United States)
Ronald M. Summers, National Institutes of Health (United States)

Published in SPIE Proceedings Vol. 7963:
Medical Imaging 2011: Computer-Aided Diagnosis
Ronald M. Summers; Bram van Ginneken, Editor(s)

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