中国组织工程研究

中国组织工程研究 ›› 2011, Vol. 15 ›› Issue (4): 683-686.doi: 10.3969/j.issn.1673-8225.2011.04.027

• 骨与关节图像与影像 bone and joint imaging • 上一篇    下一篇

基于HLSVD和AMARES磁共振波谱数据量化方法的比较

包  晨1，齐  静2，翁得河3，孙  钰1，万遂人1   

  1. 1东南大学生物科学与医学工程学院医学电子学实验室，江苏省南京市，210096
    2江苏省人民医院放射科，江苏省南京市  210029
    3西门子迈迪特(深圳)磁共振有限公司，广东省深圳市  518057
  • 收稿日期:2010-07-28 修回日期:2010-09-12 出版日期:2011-01-22 发布日期:2011-01-22
  • 作者简介:包晨★，男，1983年生，山东省蓬莱市人，汉族，东南大学在读硕士，主要从事医学电子学方面的研究。 baochen_seu@yahoo.com.cn

HLSVD versus AMARES for magnetic resonance spectroscopy data quantification

Bao Chen1, Qi Jing2, Weng De-he3, Sun Yu1, Wan Sui-ren1   

  1. 1Medical Electronics Laboratory, Department of Biology Science and Medical Engineering, Southeast University, Nanjing  210096, Jiangsu Province, China
    2Radiology Department of Jiangsu People’s Hospital, Nanjing  210029, Jiangsu Province, China
    3Siemens Mindit (Shenzhen) Magnetic Resonance Ltd., Shenzhen  518057, Guangdong Province, China
  • Received:2010-07-28 Revised:2010-09-12 Online:2011-01-22 Published:2011-01-22
  • About author:Bao Chen★, Studying for master’s degree, Medical Electronics Laboratory, Department of Biology Science and Medical Engineering, Southeast University, Nanjing 210096, Jiangsu Province, China baochen_seu@yahoo.com.cn

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被引次数

2

摘要：

背景：磁共振波谱在临床医学诊断上正成为越来越重要的辅助诊断工具，目前应用最广泛的就是人脑的氢质子磁共振波谱，其在脑肿瘤的诊断上有重要的临床价值。
目的：基于一定量数据的基础上，通过比较HLSVD和AMARES两种方法在量化结果的准确性和量化过程的时间性上的差异，找到更适用于临床辅助诊断的方法。
方法：在分析软件JMRUI中分别运用两种量化方法，得到频率，幅值，相位等物理参数，这些参数即量化结果的表现形式，以此完成对数据信号的解读。
结果及结论：HLSVD方法是根据波形的特征情况进行量化；而AMARES方法，由于使用了人工定义的先验知识，在图形的反应上就会出现偏差，导致量化的结果发生偏离。结果提示，HLSVD方法比AMARES方法在准确性和时间性上都更适合于应用到临床诊断上。

关键词: 人脑1HMRS, HLSVD, AMARES, JMRUI, 辅助诊断

Abstract:

BACKGROUND: Magnetic resonance spectroscopy (MRS) has become important auxiliary diagnosis tool in clinical diagnosis. At present, 1H MRS in human brain has been frequently used, which has important clinical value in diagnosis of brain tumor.
OBJECTIVE: To quantify the human brain 1HMRS data based on HLSVD and AMARES methods separately, by comparing the two methods through a certain amount of data to find the method which is more suitable for the clinical auxiliary diagnosis.
METHODS: We used the two methods separately in the JMRUI analysis software, and then the physical parameters such as frequency, amplitude and phrase, were obtained, which were results of the quantification in terms of these parameters, so we could deal with the interpretation of the signal.
RESULTS AND CONCLUSION: HLSVD quantifies data according waveform features, while AMARES produced deviation in images. Therefore, HLSVD is more suitable than AMARES for the clinical diagnosis, both in accuracy and timeliness.

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