An Automatic Method for Colon Segmentation in Virtual Colonoscopy
Colon segmentation from computed tomography (CT) data is a requirement for the construction of threedimensional (3D) colon in the virtual colonoscopy (VC) system. There are two main challenges in the colon segmentation: 1) many non-colonic objects might attach to the colon, 2) under-distension of the colon might lead to numbers of collapsed portions. In this paper, we proposed a method that can remove noncolonic attachments and connect collapsed colonic segments together for the VC examination. The proposed method is mainly composed by a non-colonic attachment classification algorithm and a heuristic connection algorithm. We use 30 CT scans to evaluate our method. Computer-generated colons are compared with human-generated colons which are manually extracted by two radiologists. The proposed method could achieve 92.86％ coverage of human-generated colons, which is of 13.68％ higher than the conventional method.
virtual colonoscopy automatic segmentation non-colonic objects under distention.
Lin Lu Jun Zhao
Department of Biomedical Engineering Shanghai Jiao Tong University Shanghai, 200240, China
国际会议
上海
英文
107-110
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）