Automated centerline for computed tomography colonography.

Rationale And Objectives: A novel method to compute the centerline of the human colon obtained from computed tomography colonography is proposed. Two applications of this method are demonstrated: to compute local colonic distension (caliber), and to match polyps on supine and prone images.

Materials And Methods: The centerline algorithm involves multiple steps including simplification of the colonic surface by decimation; thinning of the decimated colon to create a preliminary centerline; selection of equally spaced points on the preliminary centerline; grouping neighboring points; and mapping them back to rings in the original colon. This method was tested on 20 human computed tomography colonography datasets (supine and prone examinations of 10 patients) and on a computer-generated colon phantom.

Results: Visual inspection of the colons and their centerlines showed the centerline to be accurate. For the colon phantom, the average error was only 1 mm. For 11 polyps visualized in both the supine and prone positions and found by computer-aided detection, the normalized distance along the centerline to each polyp was not significantly different on the supine and prone views (r = 0.999; P < .001).

Conclusion: This method produces an accurate colon centerline that may be useful for flight path planning, matching detections on the supine and prone views, and computing local colonic distension.