3D supine and prone colon registration for computed tomographic colonography scans based on graph matching

In this paper, we propose a new registration method for supine and prone computed tomographic colonography scans based on graph matching. We first formulated 3D colon registration as a graph matching problem and utilized a graph matching algorithm based on mean field theory. During the iterative optimization process, one-to-one matching constraints were added to the system step-by-step. Prominent matching pairs found in previous iterations are used to guide subsequent mean field calculations. The advantage of the proposed method is that it does not require a colon centerline for registration. We tested the algorithm on a CTC dataset of 19 patients with 19 polyps. The average registration error of the proposed method was 4.0cm (std. 2.1cm). The 95% confidence intervals were [3.0cm, 5.0mm]. There was no significant difference between the proposed method and our previous method based on the normalized distance along the colon centerline (p=0.1).