基于SVD的快速组匹配“磁共振指纹”新方法

发布时间：2018-05-29 21:13

本文选题：磁共振指纹 + 奇异值分解　；参考：《生物医学工程研究》2017年02期

【摘要】：传统MRI一次扫描只能得到一种加权像,"磁共振指纹"成像新方法可同时获得组织的T1,T2及质子密度图像,但它需要采用全新的数据处理方式。直接匹配法将每个体素的信号与"字典"中的所有信号进行逐条匹配,得到参数值所需的时间很长。我们采用基于SVD的"磁共振指纹"快速分组匹配法来提高匹配效率。首先建立头部和模型"字典",从"字典"选取一条时间信号,根据该信号与字典的相关系数对字典进行分组,以大幅压缩字典的大小;再对分组后的字典进行奇异值分解,提取字典的特征信息,加速匹配速度。采用大脑和模型数据进行测试的结果表明,该方法可以快速准确地得到各种组织参数图像。
[Abstract]:Traditional MRI can only get one weighted image at a time. A new method of "magnetic resonance fingerprint" imaging can obtain T1T _ 2 and proton density images simultaneously, but it needs a new data processing method. The direct matching method matches each voxel signal with all the signals in the dictionary one by one, and it takes a long time to get the parameter value. We use SVD-based fast grouping matching method to improve the matching efficiency. First, the dictionary and the model "dictionary" are set up, a time signal is selected from the dictionary, the dictionary is grouped according to the correlation coefficient between the signal and the dictionary, and the size of the dictionary is greatly compressed, and then the singular value of the classified dictionary is decomposed. The feature information of the dictionary is extracted and the matching speed is accelerated. The results of brain and model data show that the method can get various tissue parameter images quickly and accurately.
【作者单位】：中南民族大学生物医学工程学院;华中科技大学光学与电子信息学院;
【基金】：国家自然科学基金资助项目(30970782) 湖北省自然科学基金项目(2014CFB918) 中南民族大学中央高校基本科研业务费专项资金资助项目(CZY17012)
【分类号】：R445.2

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