资源类型：
期刊/会议
文章类型：
会议论文
机构：
[a]Tsinghua National Laboratory for Information Science and Technology, Dept. of Electronic Engineering, Tsinghua University, Beijing, 100084, China
[b]Neuroimaging Center of Tiantan Hospital, Capital Medical University, Beijing, China
首都医科大学附属天坛医院
[c]Unité d'Irm, EA3916, CHRU, Caen, France
关键词：
Brain
Chemical shift imaging
Combination
Glioma
Image
Modeling
MR spectroscopy
MRI
摘要：
This paper presents a glioma modelization method and a regression-like model to create a gradually glioma image (Glio Im). Multimodal signal, images of magnetic resonance imaging (MRI) and in vivo multivoxel MR spectroscopy (MRS) are combined by the regression-like model with spatial resolution registration. This modeling method consists of feature models of glioma such as the signal intensity of MR image and the metabolite changes of MRS, the correlation model noted as metabolites ratio (MetaR) and the combined regression-like model. The estimated Glio Im includes both brain structure and glioma grade information. A nonlinear model is proposed and validated in this paper. The testing data is acquired by Siemens Trio Tim (3T) and Syngo MR B15 at Beijing Tiantan hospital of China. The MRS of three glioma patients, two affected by astrocytoma and one by glioma, and the chemical shift imaging (CSI) reference T2 images were considered in our validation experiment. The resulting Glio Ims are compared with ground truth provided by neuroradiologists of Tiantan and verified with their pathology report. They report that our method and model are very efficient. © 2010 IEEE.
第一作者：
Dou, W
推荐引用方式(GB/T 7714)：
Dou W,Dong A,Chi P,et al.Glioma tissue modeling by combing the information of MRI and in vivo multivoxel MRS[J].2010,doi:10.1109/ICBBE.2010.5517478.
APA：
Dou, W,Dong, A,Chi, P,Li, S&Constans, J.-M.(2010).Glioma tissue modeling by combing the information of MRI and in vivo multivoxel MRS.,,
MLA：
Dou, W,et al."Glioma tissue modeling by combing the information of MRI and in vivo multivoxel MRS". .(2010)
