Automated polyp measurement based on colon structure decomposition for CT colonography

Huafeng Wang; Lihong C. Li; Hao Han; Hao Peng; Bowen Song; Xinzhou Wei; Zhengrong Liang

doi:10.1117/12.2043648

20 March 2014 Automated polyp measurement based on colon structure decomposition for CT colonography

Huafeng Wang, Lihong C. Li, Hao Han, Hao Peng, Bowen Song, Xinzhou Wei, Zhengrong Liang

Proceedings Volume 9035, Medical Imaging 2014: Computer-Aided Diagnosis; 90350B (2014) https://doi.org/10.1117/12.2043648
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

Accurate assessment of colorectal polyp size is of great significance for early diagnosis and management of colorectal cancers. Due to the complexity of colon structure, polyps with diverse geometric characteristics grow from different landform surfaces. In this paper, we present a new colon decomposition approach for polyp measurement. We first apply an efficient maximum a posteriori expectation-maximization (MAP-EM) partial volume segmentation algorithm to achieve an effective electronic cleansing on colon. The global colon structure is then decomposed into different kinds of morphological shapes, e.g. haustral folds or haustral wall. Meanwhile, the polyp location is identified by an automatic computer aided detection algorithm. By integrating the colon structure decomposition with the computer aided detection system, a patch volume of colon polyps is extracted. Thus, polyp size assessment can be achieved by finding abnormal protrusion on a relative uniform morphological surface from the decomposed colon landform. We evaluated our method via physical phantom and clinical datasets. Experiment results demonstrate the feasibility of our method in consistently quantifying the size of polyp volume and, therefore, facilitating characterizing for clinical management.

Citation Download Citation

Huafeng Wang, Lihong C. Li, Hao Han, Hao Peng, Bowen Song, Xinzhou Wei, and Zhengrong Liang "Automated polyp measurement based on colon structure decomposition for CT colonography", Proc. SPIE 9035, Medical Imaging 2014: Computer-Aided Diagnosis, 90350B (20 March 2014); https://doi.org/10.1117/12.2043648

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