A novel colonic polyp volume segmentation method for computer tomographic colonography

Huafeng Wang; Lihong C. Li; Hao Han; Bowen Song; Hao Peng; Yunhong Wang; Lihua Wang; Zhengrong Liang

doi:10.1117/12.2043556

18 March 2014 A novel colonic polyp volume segmentation method for computer tomographic colonography

Huafeng Wang, Lihong C. Li, Hao Han, Bowen Song, Hao Peng, Yunhong Wang, Lihua Wang, Zhengrong Liang

Proceedings Volume 9035, Medical Imaging 2014: Computer-Aided Diagnosis; 90352W (2014) https://doi.org/10.1117/12.2043556
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

Colorectal cancer is the third most common type of cancer. However, this disease can be prevented by detection and removal of precursor adenomatous polyps after the diagnosis given by experts on computer tomographic colonography (CTC). During CTC diagnosis, the radiologist looks for colon polyps and measures not only the size but also the malignancy. It is a common sense that to segment polyp volumes from their complicated growing environment is of much significance for accomplishing the CTC based early diagnosis task. Previously, the polyp volumes are mainly given from the manually or semi-automatically drawing by the radiologists. As a result, some deviations cannot be avoided since the polyps are usually small (6~9mm) and the radiologists’ experience and knowledge are varying from one to another. In order to achieve automatic polyp segmentation carried out by the machine, we proposed a new method based on the colon decomposition strategy. We evaluated our algorithm on both phantom and patient data. Experimental results demonstrate our approach is capable of segment the small polyps from their complicated growing background.

Citation Download Citation

Huafeng Wang, Lihong C. Li, Hao Han, Bowen Song, Hao Peng, Yunhong Wang, Lihua Wang, and Zhengrong Liang "A novel colonic polyp volume segmentation method for computer tomographic colonography", Proc. SPIE 9035, Medical Imaging 2014: Computer-Aided Diagnosis, 90352W (18 March 2014); https://doi.org/10.1117/12.2043556

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