Literature DB >> 18092735

Polyp enhancing level set evolution of colon wall: method and pilot study.

Ender Konukoglu1, Burak Acar, David S Paik, Christopher F Beaulieu, Jarrett Rosenberg, Sandy Napel.   

Abstract

Computer aided detection (CAD) in computed tomography colonography (CTC) aims at detecting colonic polyps that are the precursors of colon cancer. In this work, we propose a colon wall evolution algorithm polyp enhancing level sets (PELS) based on the level-set formulation that regularizes and enhances polyps as a preprocessing step to CTC CAD algorithms. The underlying idea is to evolve the polyps towards spherical protrusions on the colon wall while keeping other structures, such as haustral folds, relatively unchanged and, thereby, potentially improve the performance of CTC CAD algorithms, especially for smaller polyps. To evaluate our methods, we conducted a pilot study using an arbitrarily chosen CTC CAD method, the surface normal overlap (SNO) CAD algorithm, on a nine patient CTC data set with 47 polyps of sizes ranging from 2.0 to 17.0 mm in diameter. PELS increased the maximum sensitivity by 8.1% (from 21/37 to 24/37) for small polyps of sizes ranging from 5.0 to 9.0 mm in diameter. This is accompanied by a statistically significant separation between small polyps and false positives. PELS did not change the CTC CAD performance significantly for larger polyps.

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Year:  2007        PMID: 18092735     DOI: 10.1109/tmi.2007.901429

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


  6 in total

1.  Improved computer-aided detection of small polyps in CT colonography using interpolation for curvature estimation.

Authors:  Jiamin Liu; Suraj Kabadi; Robert Van Uitert; Nicholas Petrick; Rachid Deriche; Ronald M Summers
Journal:  Med Phys       Date:  2011-07       Impact factor: 4.071

2.  Improved curvature estimation for computer-aided detection of colonic polyps in CT colonography.

Authors:  Hongbin Zhu; Yi Fan; Hongbing Lu; Zhengrong Liang
Journal:  Acad Radiol       Date:  2011-06-11       Impact factor: 3.173

3.  Seeing is believing: video classification for computed tomographic colonography using multiple-instance learning.

Authors:  Shijun Wang; Matthew T McKenna; Tan B Nguyen; Joseph E Burns; Nicholas Petrick; Berkman Sahiner; Ronald M Summers
Journal:  IEEE Trans Med Imaging       Date:  2012-05       Impact factor: 10.048

Review 4.  Machine learning and radiology.

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

5.  EMPLOYING TOPOGRAPHICAL HEIGHT MAP IN COLONIC POLYP MEASUREMENT AND FALSE POSITIVE REDUCTION.

Authors:  Jianhua Yao; Jiang Li; Ronald M Summers
Journal:  Pattern Recognit       Date:  2009       Impact factor: 7.740

6.  Attraction Propagation: A User-Friendly Interactive Approach for Polyp Segmentation in Colonoscopy Images.

Authors:  Ning Du; Xiaofei Wang; Jianhua Guo; Meidong Xu
Journal:  PLoS One       Date:  2016-05-18       Impact factor: 3.240

  6 in total

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