Literature DB >> 16524091

Hybrid segmentation of colon filled with air and opacified fluid for CT colonography.

Marek Franaszek1, Ronald M Summers, Perry J Pickhardt, J Richard Choi.   

Abstract

Reliable segmentation of the colon is a requirement for three-dimensional visualization programs and automatic detection of polyps on computed tomography (CT) colonography. There is an evolving clinical consensus that giving patients positive oral contrast to tag out remnants of stool and residual fluids is mandatory. The presence of positive oral contrast in the colon adds an additional challenge for colonic segmentation but ultimately is beneficial to the patient because the enhanced fluid helps reveal polyps in otherwise hidden areas. Therefore, we developed a new segmentation procedure which can handle both air- and fluid-filled parts of the colon. The procedure organizes individual air- and fluid-filled regions into a graph that enables identification and removal of undesired leakage outside the colon. In addition, the procedure provides a risk assessment of possible leakage to assist the user prior to the tedious task of visual verification. The proposed hybrid algorithm uses modified region growing, fuzzy connectedness and level set segmentation. We tested our algorithm on 160 CT colonography scans containing 183 known polyps. All 183 polyps were in segmented regions. In addition, visual inspection of 24 CT colonography scans demonstrated good performance of our procedure: the reconstructed colonic wall appeared smooth even at the interface between air and fluid and there were no leaked regions.

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Year:  2006        PMID: 16524091     DOI: 10.1109/TMI.2005.863836

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  16 in total

Review 1.  Improving the accuracy of CTC interpretation: computer-aided detection.

Authors:  Ronald M Summers
Journal:  Gastrointest Endosc Clin N Am       Date:  2010-04

2.  Optimizing area under the ROC curve using semi-supervised learning.

Authors:  Shijun Wang; Diana Li; Nicholas Petrick; Berkman Sahiner; Marius George Linguraru; Ronald M Summers
Journal:  Pattern Recognit       Date:  2015-01-01       Impact factor: 7.740

3.  Automated image-based colon cleansing for laxative-free CT colonography computer-aided polyp detection.

Authors:  Marius George Linguraru; Neil Panjwani; Joel G Fletcher; Ronald M Summers
Journal:  Med Phys       Date:  2011-12       Impact factor: 4.071

4.  The elephant in the room: bowel preparation for CT colonography.

Authors:  Ronald Summers
Journal:  Acad Radiol       Date:  2009-07       Impact factor: 3.173

Review 5.  Informatics in radiology: dual-energy electronic cleansing for fecal-tagging CT colonography.

Authors:  Wenli Cai; Se Hyung Kim; June-Goo Lee; Hiroyuki Yoshida
Journal:  Radiographics       Date:  2013-03-11       Impact factor: 5.333

6.  Informatics in radiology: Electronic cleansing for noncathartic CT colonography: a structure-analysis scheme.

Authors:  Wenli Cai; Hiroyuki Yoshida; Michael E Zalis; Janne Johannes Näppi; Gordon J Harris
Journal:  Radiographics       Date:  2010-03-10       Impact factor: 5.333

7.  Reversible projection technique for colon unfolding.

Authors:  Jianhua Yao; Ananda S Chowdhury; Javed Aman; Ronald M Summers
Journal:  IEEE Trans Biomed Eng       Date:  2010-06-10       Impact factor: 4.538

8.  Improving Polyp Detection Algorithms for CT Colonography: Pareto Front Approach.

Authors:  Adam Huang; Jiang Li; Ronald M Summers; Nicholas Petrick; Amy K Hara
Journal:  Pattern Recognit Lett       Date:  2010-03-21       Impact factor: 3.756

Review 9.  Machine learning and radiology.

Authors:  Shijun Wang; Ronald M Summers
Journal:  Med Image Anal       Date:  2012-02-23       Impact factor: 8.545

10.  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

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