| A novel method for evaluating and improving the 1H-MRSI glioma data quality |
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| 作者姓名： | YUAN Kehong LU Hongyu BAO Shanglian CHEN Qiansheng LI Shaowu DUAN Chaijie |
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| 作者单位： | Key Laboratory of Pure and Applied Mathematics, School of Mathematical Sciences, Beijing 100871, China;The Research Center for Tumor Diagnosis and Therapeutical Physics & the Beijing Key Laboratory of Medical Physics and Engineering, Peking University, Beijing 100871, China;,The Research Center for Tumor Diagnosis and Therapeutical Physics & the Beijing Key Laboratory of Medical Physics and Engineering, Peking University, Beijing 100871, China,The Research Center for Tumor Diagnosis and Therapeutical Physics & the Beijing Key Laboratory of Medical Physics and Engineering, Peking University, Beijing 100871, China,Key Laboratory of Pure and Applied Mathematics, School of Mathematical Sciences, Beijing 100871, China,The Tian Tan Hospital, Beijing 100050, China,The Research Center for Tumor Diagnosis and Therapeutical Physics & the Beijing Key Laboratory of Medical Physics and Engineering, Peking University, Beijing 100871, China |
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| 摘 要： | Metabolic information obtained by proton magnetic resonance spectroscopic imaging (1H-MRSI) has been approved to be a powerful tool to identify either benign or malignant glioma, as well as to confirm the tumor level. However, 1H-MRSI data are affected by various factors, such as the thermal noise, eddy currents, susceptibility artifacts, and rigid body motion. To get accurate quantitative metabolic information, the key problem is to assess the 1H-MRSI data quality. In this paper, we introduce a new evaluating system to filter the data, and a new method, called wavelet denoising method, to improve the data quality under the evaluating system. Experimental results on 1H-MRSI glioma data demonstrate that preprocessing is prerequisite and the proposed algorithm with evaluating system is effective.
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| 关 键 词： | 1H-MRSI evaluating system glioma data quality wavelet denoising. |
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