A New Clustering Segmentation Algorithm of 3D Medical Data Field Based on Data Mining

摘要：

Direct 3D volume segmentation is one of the difficult and hot research fields in 3D medical data field processing. Using the clustering and analyzing techniques of data mining, a new clustering and segmentation algorithm is presented. Firstly, According to the physical means of the medical data, the data field is preprocessed to speed up succeed processing. Secondly, the paper deduces and analyzes the clustering and segmentation algorithm and presents some methods to increase the process speed. Finally, the experimental results show that the algorithm has high accuracy when used to segment complicated medical tissue and can improve process speed greatly.

关键词： medical data field segmentation data mining density-isoline clustering

作者: LI Xin-Wu YE Han-Kun

作者单位: Biomedical Engineering Institute of Northwestern Polytechnical University, Xian 710072

会议类型: 国际会议

会议名称: Yangtze River 2009 International Conference on Medical Imaging Physics & The 5th National Annual Meeting of Medical Imaging Physics(长江2009国际医学影像物理和工程大会暨第五届中国医学影像物理学术年会ICMIP2009)

会议地点: 南京

会议语种:英文

页码: 121-128

在线出版日期: 2009-10-23（万方平台首次上网日期，不代表论文的发表时间）