Identifying the margin of glioma using 1H-MRSI data
(0) Glioma is one of malign tumors due to the special construction of the glia cell and its character of infiltration. The treatment, such as surgical resection and radiotherapy, needs the precise tumor boundary. To identify noninvasively the margin of the tumor, using metabolic information by proton magnetic resonance spectroscopic imaging (1H-MRSI) has been approved to be a powerful tool. In this paper we adopt 1H-MRSI data for feature extraction and employ support vector machine(SVM) to classify every voxel in the region of interest (ROI) into either glioma or normal tissue, and then to infer the margin of glioma.Experimental results on 1H-MRSI glioma data demonstrate that proposed method is effective and show a better performance compared with recent popular method.
1H-MRSI SVM glioma feature extraction
Kehong Yuan Weixiang Liu Shaowei Jia Ping Xiao Shanglian Bao
Life Science Division Graduate School at Shenzhen Tsinghua University Shenzhen, 518055, China The Center of Medical Image Shenzhen Hospital of Peking University Shenzhen, 518036, China Beijing Key Lab of Medical Physics and Engineering Beijing 100871, China
国际会议
武汉
英文
1224-1227
2007-07-06（万方平台首次上网日期，不代表论文的发表时间）