基于多元图表示的中药指纹图谱可视化模式分析方法研究
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摘要
中药现代化是目前国内外医药界研究的一大热点。中药指纹图谱技术是中药现代化的有力工具，可以用来鉴别中药的真伪，控制中药质量及评价其安全性和有效性。中药指纹图谱的解析与处理通常借助于计算机，分析其化学成分测定值及相关的药理作用，快速、准确地寻找出内在规律，作为中药材质量控制的指标。由于中药是多种成分协同作用，所以图谱数据的整体性对研究至关重要。但是，在当前的研究中，有的在分析过程中打破了这一整体性，有的保证了数据的整体性却又直观性差，不易理解。因此，在中药指纹图谱的研究中，如何在保证图谱数据整体性的前提下实现分析过程的可视化是一个重要课题。
本文基于多元图表示的理论基础，针对中药指纹图谱的数据处理问题，提出了一种可视化的模式分析新方法，实现了中药指纹图谱数据处理的整体性和可视性的统一，为中药的鉴别及评价提供了一种新的信息处理手段。主要研究了三个基本方面的问题：多元数据的多元图表示方法及特征提取方法；中药指纹图谱的雷达图分类模型的建立；标准指纹图谱的建立。
1.研究了多元数据多元图的表示方法及基于多元图表示原理的特征提取方法。提出了多元数据的类间重叠系数矩阵以剔除方差大而分类信息差的向量；对传统散布矩阵进行了优化以区分类别均值与全局均值之间距离比较相近的向量；采用样本点与各个类别之间的距离表示样本点，再进行分类研究；对人机交互在多元图特征提取中的应用进行了研究。实验证明了这些方法的可行性及优越性。
2.研究了基于雷达图表示原理的中药指纹图谱的分类。在多元数据雷达图表示及特征提取的基础上，将雷达图的重心图特征进行了拓展，并对相邻幅值比图特征进行了优化。针对中药指纹图谱的分类问题，提出了重心特征峰参数以及多层雷达图表示的分类模型。实验取得了较好的效果。
3.研究了标准指纹图谱的建立。针对标准指纹图谱传统构建方法存在的问题，基于聚类原理，将多参数距离融合聚类规则作为标准指纹图谱。该方法以分类为目的，结果生成的不再是传统的有意义的特征指纹图谱或是特征库，而是一种分类标准。实验分析了该方法的可行性和优越性。
4.利用近红外光谱仪分别获得了葛根（纯葛根粉及掺假葛根粉）以及不同种类的人参的指纹图谱，采用多层雷达图模型及相关技术对葛根的真伪及人参的种类进行了鉴别研究，结果验证了本文提出的可视化中药指纹图谱模式分析方法的可行性和有效性。
The study on the modernization of Traditional Chinese Medicine (TCM)is a hot topic.The fingerprint technology is a powerful tool for modernizing the TCM, and it can be usedto identify the authenticity, control the quality and evaluate the safety and effectiveness.We process the TCM fingerprint by means of computer usually, analyzing their chemicalcomposition measured values and the related pharmacological effects, and finding out theinherent laws quickly and accurately as an indicator of quality control of TCM. Theintegrity of the fingerprint data is essential to the research because the TCM is synergisticeffect by multiple components. However, some researches break the integrity in analysisprocess, and some researches ensure the data integrity but with poor intuitive and hard tounderstand in the current study. Therefore, how to realize the visualization of the analysisprocess on the basis of ensuring the integrity of TCM data is an important issue in theTCM fingerprint research.
Aiming at the data process problems of the TCM, in this thesis, a novel visualizationmethod of pattern analysis based on the multiple graph representation theory wasadvanced, which will help to ensure the unity of integrity and obscurity of the TCM andprovided a novel information process means for the identification and evaluation of theTCM. Three basic problems were focused on in the work of this thesis, multiple graphrepresentation and feature extraction of multivariate data, the construction of classificationmodel in radar plot of the TCM fingerprint data and the construction of the standardfingerprint.
Firstly, the multivariate graph representation method of the multivariate data and thefeature extraction method based on the multivariate graph principle were studied. Thesorted overlap coefficient matrix was proposed to eliminate the variables with biggervariance and little classification information. The traditional scatter matrix was optimizedto separate the viables with similar sorted mean and whole mean. The sample wasrepresented by the distance between the sample and the class hyperplane and the distancewas as feature for classification. The application of Human-Computer Interaction (HCI)in feature extraction was studied. Experiments demonstrated the feasibility and advantages ofthese methods.
Secondly, the classification of the TCM fingerprint based on the principle of radardiagram representation was studied. The center feature was expanded and the adjacentamplitude ratio was optimized based on the representation and feature extraction of theradar plot of multivariate data. Aiming at the classification problem of the TCMfingerprint, the center feature peak and the multi-layer radar plot representationclassification model were proposed firstly. Experiments had achieved good results.
Thirdly, the construction of the standard fingerprint was studied. Aiming at theproblems of traditional methods for building the standard fingerprint, based on theclustering theory, a novel standard fingerprint that uses the clustering rules of themulti-parameter distance was put forward. Because classification is the purpose of themethod, the result is no longer a characteristic fingerprint or library with traditionalmeanings, but a classification standard. Experiments analyzed the feasibility andsuperiority.
Finally, using the near infrared spectroscopy, the fingerprints of the Radix Puerariae(pure and adulterated goods)and ginseng (different types)were obtained. The distinction ofthe authenticity of radix Puerariae and the species of ginseng were studied. Theexperimental results verified the feasibility and effectiveness of the proposed visualizationanalysis method of TCM fingerprint.
本文基于多元图表示的理论基础，针对中药指纹图谱的数据处理问题，提出了一种可视化的模式分析新方法，实现了中药指纹图谱数据处理的整体性和可视性的统一，为中药的鉴别及评价提供了一种新的信息处理手段。主要研究了三个基本方面的问题：多元数据的多元图表示方法及特征提取方法；中药指纹图谱的雷达图分类模型的建立；标准指纹图谱的建立。
1.研究了多元数据多元图的表示方法及基于多元图表示原理的特征提取方法。提出了多元数据的类间重叠系数矩阵以剔除方差大而分类信息差的向量；对传统散布矩阵进行了优化以区分类别均值与全局均值之间距离比较相近的向量；采用样本点与各个类别之间的距离表示样本点，再进行分类研究；对人机交互在多元图特征提取中的应用进行了研究。实验证明了这些方法的可行性及优越性。
2.研究了基于雷达图表示原理的中药指纹图谱的分类。在多元数据雷达图表示及特征提取的基础上，将雷达图的重心图特征进行了拓展，并对相邻幅值比图特征进行了优化。针对中药指纹图谱的分类问题，提出了重心特征峰参数以及多层雷达图表示的分类模型。实验取得了较好的效果。
3.研究了标准指纹图谱的建立。针对标准指纹图谱传统构建方法存在的问题，基于聚类原理，将多参数距离融合聚类规则作为标准指纹图谱。该方法以分类为目的，结果生成的不再是传统的有意义的特征指纹图谱或是特征库，而是一种分类标准。实验分析了该方法的可行性和优越性。
4.利用近红外光谱仪分别获得了葛根（纯葛根粉及掺假葛根粉）以及不同种类的人参的指纹图谱，采用多层雷达图模型及相关技术对葛根的真伪及人参的种类进行了鉴别研究，结果验证了本文提出的可视化中药指纹图谱模式分析方法的可行性和有效性。
The study on the modernization of Traditional Chinese Medicine (TCM)is a hot topic.The fingerprint technology is a powerful tool for modernizing the TCM, and it can be usedto identify the authenticity, control the quality and evaluate the safety and effectiveness.We process the TCM fingerprint by means of computer usually, analyzing their chemicalcomposition measured values and the related pharmacological effects, and finding out theinherent laws quickly and accurately as an indicator of quality control of TCM. Theintegrity of the fingerprint data is essential to the research because the TCM is synergisticeffect by multiple components. However, some researches break the integrity in analysisprocess, and some researches ensure the data integrity but with poor intuitive and hard tounderstand in the current study. Therefore, how to realize the visualization of the analysisprocess on the basis of ensuring the integrity of TCM data is an important issue in theTCM fingerprint research.
Aiming at the data process problems of the TCM, in this thesis, a novel visualizationmethod of pattern analysis based on the multiple graph representation theory wasadvanced, which will help to ensure the unity of integrity and obscurity of the TCM andprovided a novel information process means for the identification and evaluation of theTCM. Three basic problems were focused on in the work of this thesis, multiple graphrepresentation and feature extraction of multivariate data, the construction of classificationmodel in radar plot of the TCM fingerprint data and the construction of the standardfingerprint.
Firstly, the multivariate graph representation method of the multivariate data and thefeature extraction method based on the multivariate graph principle were studied. Thesorted overlap coefficient matrix was proposed to eliminate the variables with biggervariance and little classification information. The traditional scatter matrix was optimizedto separate the viables with similar sorted mean and whole mean. The sample wasrepresented by the distance between the sample and the class hyperplane and the distancewas as feature for classification. The application of Human-Computer Interaction (HCI)in feature extraction was studied. Experiments demonstrated the feasibility and advantages ofthese methods.
Secondly, the classification of the TCM fingerprint based on the principle of radardiagram representation was studied. The center feature was expanded and the adjacentamplitude ratio was optimized based on the representation and feature extraction of theradar plot of multivariate data. Aiming at the classification problem of the TCMfingerprint, the center feature peak and the multi-layer radar plot representationclassification model were proposed firstly. Experiments had achieved good results.
Thirdly, the construction of the standard fingerprint was studied. Aiming at theproblems of traditional methods for building the standard fingerprint, based on theclustering theory, a novel standard fingerprint that uses the clustering rules of themulti-parameter distance was put forward. Because classification is the purpose of themethod, the result is no longer a characteristic fingerprint or library with traditionalmeanings, but a classification standard. Experiments analyzed the feasibility andsuperiority.
Finally, using the near infrared spectroscopy, the fingerprints of the Radix Puerariae(pure and adulterated goods)and ginseng (different types)were obtained. The distinction ofthe authenticity of radix Puerariae and the species of ginseng were studied. Theexperimental results verified the feasibility and effectiveness of the proposed visualizationanalysis method of TCM fingerprint.
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101 Darinka Brodnjak Voncina, Zdenka Cencic Kodba, Marjana Novic. Multivariate data analysis inclassification of vegetable oils characterized by the content of fatty acids. Chemometrics andIntelligent Laboratory Systems, 2005, 75(1): 31-43.
102 El bieta P kalska, Robert P. W. Duin. The Dissimilarity Representation for Pattern Recognition.World Scientific Publishing,2005.6.
103钟珞,潘昊,封筠,等.模式识别.武汉:武汉大学出版社, 2006.
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111 Suykens J.A.K., Van Gestel T., De Brabanter J. Least Squares Support Vector Machines. Singapore:World Scientific, 2002.
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113张福良.聚类分析与中药质量研究.北京:人民卫生出版社, 1994.
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