CENTERLINE REGISTRATION OF PRONE AND SUPINE CT COLONOGRAPHY SCANS BASED ON CORRELATION OPTIMIZED WARPING AND ANATOMICAL LANDMARKS

In this paper, we propose an automated method for colon registration from supine and prone scans. We formulate the colon registration problem as time series matching along the centerline of the colon. Four anatomical salient points on the colon are distinguished first. They can be viewed as landmarks along the central path of the colon. Then correlation optimized warping is applied to the segments defined by the anatomical landmarks to find better global registration based on local correlation of segments. To verify the effectiveness of the proposed method, we use polyp location as a measure for the registration error. We tested the algorithm on a CTC dataset of 12 patients with 14 polyps. Experimental results show that by using our method, the estimation error of polyp location could be reduced 60.4% (from 47.2mm to 18.7mm on average) compared to a dynamic warping algorithm.