Registration of prone and supine CT colonography scans using correlation optimized warping and canonical correlation analysis.
OBJECTIVE
In computed tomographic colonography (CTC), a patient will be scanned twice-Once supine and once prone-to improve the sensitivity for polyp detection. To assist radiologists in CTC reading, in this paper we propose an automated method for colon registration from supine and prone CTC scans.


METHODS
We propose a new colon centerline registration method for prone and supine CTC scans using correlation optimized warping (COW) and canonical correlation analysis (CCA) based on the anatomical structure of the colon. Four anatomical salient points on the colon are first automatically distinguished. Then correlation optimized warping is applied to the segments defined by the anatomical landmarks to improve the global registration based on local correlation of segments. The COW method was modified by embedding canonical correlation analysis to allow multiple features along the colon centerline to be used in our implementation.


RESULTS
We tested the COW algorithm on a CTC data set of 39 patients with 39 polyps (19 training and 20 test cases) to verify the effectiveness of the proposed COW registration method. Experimental results on the test set show that the COW method significantly reduces the average estimation error in a polyp location between supine and prone scans by 67.6%, from 46.27 +/- 52.97 to 14.98 mm +/- 11.41 mm, compared to the normalized distance along the colon centerline algorithm (p < 0.01).


CONCLUSIONS
The proposed COW algorithm is more accurate for the colon centerline registration compared to the normalized distance along the colon centerline method and the dynamic time warping method. Comparison results showed that the feature combination of z-coordinate and curvature achieved lowest registration error compared to the other feature combinations used by COW. The proposed method is tolerant to centerline errors because anatomical landmarks help prevent the propagation of errors across the entire colon centerline.
Wang
Shijun
S
Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Maryland 20892-1182, USA. wangshi@cc.nih.gov
Yao
Jianhua
J
Liu
Jiamin
J
Petrick
Nicholas
N
Van Uitert
Robert L
RL
Periaswamy
Senthil
S
Summers
Ronald M
RM
D023881:Colonography, Computed Tomographic / Q000379:methods*; D006801:Humans; D008297:Male; D008875:Middle Aged; D016684:Prone Position; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D016683:Supine Position