Literature DB >> 15543800

Registration of central paths and colonic polyps between supine and prone scans in computed tomography colonography: pilot study.

Ping Li1, Sandy Napel, Burak Acar, David S Paik, R Brooke Jeffrey, Christopher F Beaulieu.   

Abstract

Computed tomography colonography (CTC) is a minimally invasive method that allows the evaluation of the colon wall from CT sections of the abdomen/pelvis. The primary goal of CTC is to detect colonic polyps, precursors to colorectal cancer. Because imperfect cleansing and distension can cause portions of the colon wall to be collapsed, covered with water, and/or covered with retained stool, patients are scanned in both prone and supine positions. We believe that both reading efficiency and computer aided detection (CAD) of CTC images can be improved by accurate registration of data from the supine and prone positions. We developed a two-stage approach that first registers the colonic central paths using a heuristic and automated algorithm and then matches polyps or polyp candidates (CAD hits) by a statistical approach. We evaluated the registration algorithm on 24 patient cases. After path registration, the mean misalignment distance between prone and supine identical anatomic landmarks was reduced from 47.08 to 12.66 mm, a 73% improvement. The polyp registration algorithm was specifically evaluated using eight patient cases for which radiologists identified polyps separately for both supine and prone data sets, and then manually registered corresponding pairs. The algorithm correctly matched 78% of these pairs without user input. The algorithm was also applied to the 30 highest-scoring CAD hits in the prone and supine scans and showed a success rate of 50% in automatically registering corresponding polyp pairs. Finally, we computed the average number of CAD hits that need to be manually compared in order to find the correct matches among the top 30 CAD hits. With polyp registration, the average number of comparisons was 1.78 per polyp, as opposed to 4.28 comparisons without polyp registration.

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Year:  2004        PMID: 15543800     DOI: 10.1118/1.1796171

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  10 in total

1.  Supine and prone colon registration using quasi-conformal mapping.

Authors:  Wei Zeng; Joseph Marino; Krishna Chaitanya Gurijala; Xianfeng Gu; Arie Kaufman
Journal:  IEEE Trans Vis Comput Graph       Date:  2010 Nov-Dec       Impact factor: 4.579

2.  Corresponding Supine and Prone Colon Visualization Using Eigenfunction Analysis and Fold Modeling.

Authors:  Saad Nadeem; Joseph Marino; Xianfeng Gu; Arie Kaufman
Journal:  IEEE Trans Vis Comput Graph       Date:  2017-01       Impact factor: 4.579

3.  Matching 3-D prone and supine CT colonography scans using graphs.

Authors:  Shijun Wang; Nicholas Petrick; Robert L Van Uitert; Senthil Periaswamy; Zhuoshi Wei; Ronald M Summers
Journal:  IEEE Trans Inf Technol Biomed       Date:  2012-04-27

4.  Automated teniae coli detection and identification on computed tomographic colonography.

Authors:  Zhuoshi Wei; Jianhua Yao; Shijun Wang; Jiamin Liu; Ronald M Summers
Journal:  Med Phys       Date:  2012-02       Impact factor: 4.071

5.  Predicting polyp location on optical colonoscopy from CT colonography by minimal-energy curve modeling of the colonoscope path.

Authors:  Jiamin Liu; Kevin W Chang; Jianhua Yao; Ronald M Summers
Journal:  IEEE Trans Biomed Eng       Date:  2012-09-28       Impact factor: 4.538

6.  Registration of prone and supine CT colonography scans based on correlation optimized warping and canonical correlation analysis.

Authors:  Shijun Wang; Jianhua Yao; Jiamin Liu; Nicholas Petrick; Ronald M Summers
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009

7.  Registration of prone and supine CT colonography scans using correlation optimized warping and canonical correlation analysis.

Authors:  Shijun Wang; Jianhua Yao; Jiamin Liu; Nicholas Petrick; Robert L Van Uitert; Senthil Periaswamy; Ronald M Summers
Journal:  Med Phys       Date:  2009-12       Impact factor: 4.071

Review 8.  Computer-aided detection for virtual colonoscopy.

Authors:  James J Perumpillichira; Hiroyuki Yoshida; Dushyant V Sahani
Journal:  Cancer Imaging       Date:  2005-08-23       Impact factor: 3.909

9.  Haustral loop extraction for CT colonography using geodesics.

Authors:  Yongkai Liu; Chaijie Duan; Jerome Liang; Jing Hu; Hongbing Lu; Mingyue Luo
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-11-16       Impact factor: 2.924

10.  Endoluminal surface registration for CT colonography using haustral fold matching.

Authors:  Thomas Hampshire; Holger R Roth; Emma Helbren; Andrew Plumb; Darren Boone; Greg Slabaugh; Steve Halligan; David J Hawkes
Journal:  Med Image Anal       Date:  2013-04-27       Impact factor: 8.545

  10 in total

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