NDLI: Registration of prone and supine CT colonography scans based on correlation optimized warping and canonical correlation analysis

Content Provider	IEEE Xplore Digital Library
Author	Shijun Wang Jianhua Yao Jiamin Liu Petrick, N. Summers, R.M.
Copyright Year	2009
Description	Author affiliation: NIBIB/CDRH Laboratory for the Assessment of Medical Imaging Systems, Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993-0002 (Petrick, N.) \|\| Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health, Building 10 Room B2S-231 MSC 1182, Bethesda, MD 20892-1182 (Shijun Wang; Jianhua Yao; Jiamin Liu; Summers, R.M.)
Abstract	In this paper, we propose an automated method for colon registration from supine and prone scans. Four anatomical salient points on the colon are distinguished first. Then correlation optimized warping (COW) method is applied to the segments defined by the anatomical landmarks to find better global registration based on local correlation of segments. To utilize more features along the colon centerline, we extended the COW method by embedding canonical correlation analysis into it for correlation calculation of colon segments. To verify the effectiveness of the proposed method, we tested the algorithm on a CTC dataset of 19 patients with 23 polyps. Experimental results show that by using our method, the estimation error of polyp location could be reduced 68.5% (from 41.6mm to 13.1mm on average) compared to a traditional dynamic warping algorithm.
Starting Page	81
Ending Page	84
File Size	1063063
Page Count	4
File Format	PDF
ISBN	9781424432967
ISSN	1557170X
DOI	10.1109/IEMBS.2009.5334691
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Virtual colonoscopy Colon Colonic polyps Optimization methods Colonography Heuristic algorithms Cancer Surface reconstruction Image reconstruction Laboratories
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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