计算机舌诊中裂纹舌图像的诊断分类研究
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摘要
舌诊是传统中医中非常有价值和被广泛使用的诊断方法之一。然而由于传统中医舌诊的不量化、主观性强以及诊断结果依赖于医生的知识和经验等缺点,阻碍了中医舌诊在临床医学上的应用。为了克服这些缺点,一些研究人员使用计算机技术开展了舌诊的自动化和客观化研究。
虽然计算机化舌诊研究已经取得了一些可喜的进步,然而这些研究主要集中在舌苔舌质分析方面,对舌面上一个重要的舌象特征——舌裂纹的研究甚少。在计算机化舌诊研究中,虽然已有少量文献介绍了一些舌裂纹的特征提取和分析方面的工作,但远远不够系统和深入,并且目前关于舌裂纹量化特征与临床疾病映射关系研究方面的文献报道几乎没有。
舌裂纹是一个重要的舌象特征,它是舌面上多少不等、深浅不一、形状各异的明显裂沟。舌裂纹象的变化不仅能客观准确地反映若干典型疾病和中医证候的变化情况,还可以联合其它舌象特征来进一步提高系统的识别精度。由于在彩色裂纹舌图像上舌裂纹与其周围组织的颜色对比度往往不明显以及舌裂纹周围组织颜色分布的复杂性,使得舌裂纹区域提取以及舌裂纹特征分析等问题非常困难和具有挑战性。到目前为止,在计算机化舌裂纹研究中出现的这些问题已经严重制约了舌裂纹特征在计算机化舌诊中的使用。
为了解决这些问题,本文系统深入地研究了舌裂纹增强、舌裂纹区域提取,舌裂纹特征描述、面向疾病和中医证候的诊断分类等问题,并提出了一系列的解决方案。主要有以下内容:
首先,为了改变临床上医生不愿意看和不会看舌裂纹的现状,本文提出了一种基于3阶单位矩阵代数特征的彩色裂纹舌图像颜色变换算法。使用这个算法,能够增强舌裂纹与其周围组织的颜色对比度,辅助临床医生对裂纹舌图像进行诊断。为了正确、完整地提取出舌裂纹区域,本文提出了基于间隔差异度和先验知识的舌裂纹提取算法。这个舌裂纹区域提取算法充分利用了像素颜色和灰度变化两方面信息提取舌裂纹区域。这个算法为计算机化舌裂纹研究提供了较为可靠的技术支持。
其次,提出了一个诊断分类生理裂纹舌图像和病理裂纹舌图像的算法。首先,基于分形几何学技术的舌裂纹区域形状提取算法提取出舌裂纹区域的形状特征;然后,使用舌图像在RGB颜色空间上三个分量位于舌裂纹区域内数据的均值和标准差串接而成的向量表示舌裂纹颜色-纹理特征;最后舌裂纹区域的形状特征和舌裂纹颜色-纹理特征串接成向量融合成舌裂纹特征,基于这个舌裂纹融合特征使用线性支持向量机分类器对生理裂纹舌图像和病理裂纹舌图像进行诊断分类。实验结果表明,这个诊断分类生理裂纹舌图像和病理裂纹舌图像算法对生理裂纹舌图像和病理裂纹舌图像诊断的灵敏度都超过90%。
第三,提出了一种计算机化的舌裂纹诊病模型,在这个模型的框架指导下提出了一个对中重度慢性浅表性胃炎患者、慢性萎缩性胃炎患者、胃溃疡患者的三类人群的裂纹舌图像进行诊断分类的算法。这个算法使用Gabor小波变换和弹性判别分析提取出舌裂纹特征,使用线性支持向量机分类器对中重度慢性浅表性胃炎患者、慢性萎缩性胃炎患者、胃溃疡患者的三类人群的裂纹舌图像进行诊断分类。实验结果表明,这个诊断分类算法对三类人群裂纹舌图像诊断的灵敏度都超过80%。
最后,提出了一种像素强度计算算法,使用这个算法得到灰度图像的强度图像,并进而构造出灰度-强度共生矩阵。基于灰度-强度共生矩阵获得舌象特征,再使用线性支持向量机分类器对中医阴虚证和气血两虚证的裂纹舌图像进行诊断分类研究。实验结果表明,使用这个算法对阴虚证和气血两虚证裂纹舌图像的诊断分类灵敏度皆为85%以上。
虽然在20世纪80年代中期首次开始使用计算机技术对中医舌诊进行客观化研究,但是直到21世纪初期才有人开始对舌裂纹这一重要的舌象特征使用计算机数字图像处理等技术进行研究。到目前为止,虽然也有一些关于舌裂纹计算机化研究的文献报道,但无论是在数量上还是在研究深度上仍然显得较为薄弱。本学位论文在一定程度上填补了计算机化舌诊研究中关于舌裂纹研究的一些空白点,所取得的研究成果促进了计算机舌诊研究中关于舌裂纹方面的应用研究,同时在医学临床实践上也具有潜在的应用价值。
Tongue diagnosis is one of the most valuable and widely used diagnostic methods in traditional Chinese medicine (TCM). However, due to its qualitative, subjective and experience-based nature, traditional tongue diagnosis has a very limited application in clinical medicine. Some researchers do automatically and objectively research on tongue diagnosis by using computerized technology.
Despite considerable progress in the computerized tongue diagnosis, few are about tongue crack which is an important feature of tongue states whereas most researches focuse mainly on analysis for tongue coat and tongue proper. Even though there are few reports about feature extraction and analysis for tongue crack in computerized tongue diagnosis, these works are short of system and are shallower and at present there are hardly any reports about mapping from quantitative features of tongue crack to clinic disease.
Tongue crack is an important feature of tongue states and it is obvious fissure with varied amounts, depths and shapes on tongue surface. Change of tongue crack states does not only reflect objectively and accurately changed circumstance of some typical diseases and TCM syndrome but also it can combine the other fearures of tongue states to increase higher system classification accuracy. Due to lower color contrast between tongue crack region and its surrounding tissues and the complexity of color distribution of tissues surrounding tongue cracks on color fissured tongue images, it is very hard and challenging for region extraction and feature analysis of tongue crack. So far these problems emerged in computerized tongue crack diagnosis have restricted badly use of tongue crack in computerized tongue diagnosis.
To overcome these problems emerged in computerized tongue crack diagnosis, this dissertation does systematic and in-depth researches about these topics such as tongue crack enhancement, tongue crack region extraction, tongue crack feature description and tongue crack diagnostic classification oriented to diseases and TCM syndrome. Moreover aiming at these topics this dissertation proposes a series of settlements and schemes . Main contents of this dissertation are as follows:
First, to change the actuality which doctors are unwilling and unable to see tongue crack in clinic, this dissertation proposes color transformation based on algebraic feature of three order unit matrix for color fissured tongue image. This algorithmic makes apparent color contrast between tongue crack and its surrounding tissues so that it can assist clinic doctors to diagnose fissured tongue image. To extract correctly and completely region of tongue crack this dissertation proposes detection of tongue crack based on distant gradient and prior knowledge. This algorithmic uses information of pixel color and gray change fully. This algorithmic of tongue crack region extraction offers credible technology which benefits computerized researches of tongue crack.
Second, this dissertation proposes algorithm of diagnostic classification for physiological and pathological fissured tongue images. Firstly this dissertation extracts shape feature of tongue crack region using a method of extracting shape feature of tongue crack region based on technology of fractal geometry. Then this dissertation computes mean and standard deviation of three components of tongue image in RGB color space within tongue crack region and strings them to form a vector as color-texture feature of tongue crack. Finally this dissertation fuses shape feature of tongue crack region and color-texture feature of tongue crack to form tongue crack feature. Use tongue crack feature and linear support vector machine classifier to classify diagnostically physiological and pathological fissured tongue images. Experimental results demonstrate sensitivities of diagnosis and classification for physiological and pathological fissured tongue images are over 90% by using the approach proposed in this dissertation.
Third, this dissertation proposes a diagnostic model of tongue crack and under the guidance of the model this dissertation proposes algorithm of diagnostic classification for fissured tongue images of moderate-severe chronic superficial gastritis, chronic atrophic gastritis and gastric ulcer. The algorithm extracts tongue state feature by using Gabor wavelet transformation and springy discriminant analysis and takes linear support vector machine classifier to classify clinically these three kinds of fissured tongue images. Experimental results demonstrate sensitivities of diagnosis and classification for these three kinds of fissured tongue images are over 80% by using the approach proposed in this dissertation.
Finally, this dissertation proposes algorithm of computing pixel strength and gets strength image using it. This dissertation forms a gray-strength co-occurrence matrix and gets feature of tongue states by using the gray-strength co-occurrence matrix. Then this dissertation takes linear support vector machine classifier to classify clinically fissured tongue images diagnosed as yin deficiency syndrome and qi-blood deficiency syndrome according to TCM theory. Experimental results demonstrate sensitivities of diagnosis and classification for fissured tongue images diagnosed as yin deficiency syndrome and syndrome of qi-blood deficiency are over 85% by using the approach proposed in this dissertation.
Even though TCM tongue diagnosis was researched by using computerized technology in 1980's for the first time, people did not use tongue crack in computerized tongue diagnosis until the initial stages of 21 century. Up to now, there are only few papers about the use of tongue crack in computerized tongue diagnosis, and most of them are incomplete and not systematically. Thus, in-depth study is necessary. This dissertation fills up some blank areas about tongue crack in computerized tongue diagnosis to a certain extent. Research fruits of this dissertation would accelerate practical research on tongue crack in computerized tongue diagnosis and also possess potential application in medical clinic practice simultaneously.
虽然计算机化舌诊研究已经取得了一些可喜的进步,然而这些研究主要集中在舌苔舌质分析方面,对舌面上一个重要的舌象特征——舌裂纹的研究甚少。在计算机化舌诊研究中,虽然已有少量文献介绍了一些舌裂纹的特征提取和分析方面的工作,但远远不够系统和深入,并且目前关于舌裂纹量化特征与临床疾病映射关系研究方面的文献报道几乎没有。
舌裂纹是一个重要的舌象特征,它是舌面上多少不等、深浅不一、形状各异的明显裂沟。舌裂纹象的变化不仅能客观准确地反映若干典型疾病和中医证候的变化情况,还可以联合其它舌象特征来进一步提高系统的识别精度。由于在彩色裂纹舌图像上舌裂纹与其周围组织的颜色对比度往往不明显以及舌裂纹周围组织颜色分布的复杂性,使得舌裂纹区域提取以及舌裂纹特征分析等问题非常困难和具有挑战性。到目前为止,在计算机化舌裂纹研究中出现的这些问题已经严重制约了舌裂纹特征在计算机化舌诊中的使用。
为了解决这些问题,本文系统深入地研究了舌裂纹增强、舌裂纹区域提取,舌裂纹特征描述、面向疾病和中医证候的诊断分类等问题,并提出了一系列的解决方案。主要有以下内容:
首先,为了改变临床上医生不愿意看和不会看舌裂纹的现状,本文提出了一种基于3阶单位矩阵代数特征的彩色裂纹舌图像颜色变换算法。使用这个算法,能够增强舌裂纹与其周围组织的颜色对比度,辅助临床医生对裂纹舌图像进行诊断。为了正确、完整地提取出舌裂纹区域,本文提出了基于间隔差异度和先验知识的舌裂纹提取算法。这个舌裂纹区域提取算法充分利用了像素颜色和灰度变化两方面信息提取舌裂纹区域。这个算法为计算机化舌裂纹研究提供了较为可靠的技术支持。
其次,提出了一个诊断分类生理裂纹舌图像和病理裂纹舌图像的算法。首先,基于分形几何学技术的舌裂纹区域形状提取算法提取出舌裂纹区域的形状特征;然后,使用舌图像在RGB颜色空间上三个分量位于舌裂纹区域内数据的均值和标准差串接而成的向量表示舌裂纹颜色-纹理特征;最后舌裂纹区域的形状特征和舌裂纹颜色-纹理特征串接成向量融合成舌裂纹特征,基于这个舌裂纹融合特征使用线性支持向量机分类器对生理裂纹舌图像和病理裂纹舌图像进行诊断分类。实验结果表明,这个诊断分类生理裂纹舌图像和病理裂纹舌图像算法对生理裂纹舌图像和病理裂纹舌图像诊断的灵敏度都超过90%。
第三,提出了一种计算机化的舌裂纹诊病模型,在这个模型的框架指导下提出了一个对中重度慢性浅表性胃炎患者、慢性萎缩性胃炎患者、胃溃疡患者的三类人群的裂纹舌图像进行诊断分类的算法。这个算法使用Gabor小波变换和弹性判别分析提取出舌裂纹特征,使用线性支持向量机分类器对中重度慢性浅表性胃炎患者、慢性萎缩性胃炎患者、胃溃疡患者的三类人群的裂纹舌图像进行诊断分类。实验结果表明,这个诊断分类算法对三类人群裂纹舌图像诊断的灵敏度都超过80%。
最后,提出了一种像素强度计算算法,使用这个算法得到灰度图像的强度图像,并进而构造出灰度-强度共生矩阵。基于灰度-强度共生矩阵获得舌象特征,再使用线性支持向量机分类器对中医阴虚证和气血两虚证的裂纹舌图像进行诊断分类研究。实验结果表明,使用这个算法对阴虚证和气血两虚证裂纹舌图像的诊断分类灵敏度皆为85%以上。
虽然在20世纪80年代中期首次开始使用计算机技术对中医舌诊进行客观化研究,但是直到21世纪初期才有人开始对舌裂纹这一重要的舌象特征使用计算机数字图像处理等技术进行研究。到目前为止,虽然也有一些关于舌裂纹计算机化研究的文献报道,但无论是在数量上还是在研究深度上仍然显得较为薄弱。本学位论文在一定程度上填补了计算机化舌诊研究中关于舌裂纹研究的一些空白点,所取得的研究成果促进了计算机舌诊研究中关于舌裂纹方面的应用研究,同时在医学临床实践上也具有潜在的应用价值。
Tongue diagnosis is one of the most valuable and widely used diagnostic methods in traditional Chinese medicine (TCM). However, due to its qualitative, subjective and experience-based nature, traditional tongue diagnosis has a very limited application in clinical medicine. Some researchers do automatically and objectively research on tongue diagnosis by using computerized technology.
Despite considerable progress in the computerized tongue diagnosis, few are about tongue crack which is an important feature of tongue states whereas most researches focuse mainly on analysis for tongue coat and tongue proper. Even though there are few reports about feature extraction and analysis for tongue crack in computerized tongue diagnosis, these works are short of system and are shallower and at present there are hardly any reports about mapping from quantitative features of tongue crack to clinic disease.
Tongue crack is an important feature of tongue states and it is obvious fissure with varied amounts, depths and shapes on tongue surface. Change of tongue crack states does not only reflect objectively and accurately changed circumstance of some typical diseases and TCM syndrome but also it can combine the other fearures of tongue states to increase higher system classification accuracy. Due to lower color contrast between tongue crack region and its surrounding tissues and the complexity of color distribution of tissues surrounding tongue cracks on color fissured tongue images, it is very hard and challenging for region extraction and feature analysis of tongue crack. So far these problems emerged in computerized tongue crack diagnosis have restricted badly use of tongue crack in computerized tongue diagnosis.
To overcome these problems emerged in computerized tongue crack diagnosis, this dissertation does systematic and in-depth researches about these topics such as tongue crack enhancement, tongue crack region extraction, tongue crack feature description and tongue crack diagnostic classification oriented to diseases and TCM syndrome. Moreover aiming at these topics this dissertation proposes a series of settlements and schemes . Main contents of this dissertation are as follows:
First, to change the actuality which doctors are unwilling and unable to see tongue crack in clinic, this dissertation proposes color transformation based on algebraic feature of three order unit matrix for color fissured tongue image. This algorithmic makes apparent color contrast between tongue crack and its surrounding tissues so that it can assist clinic doctors to diagnose fissured tongue image. To extract correctly and completely region of tongue crack this dissertation proposes detection of tongue crack based on distant gradient and prior knowledge. This algorithmic uses information of pixel color and gray change fully. This algorithmic of tongue crack region extraction offers credible technology which benefits computerized researches of tongue crack.
Second, this dissertation proposes algorithm of diagnostic classification for physiological and pathological fissured tongue images. Firstly this dissertation extracts shape feature of tongue crack region using a method of extracting shape feature of tongue crack region based on technology of fractal geometry. Then this dissertation computes mean and standard deviation of three components of tongue image in RGB color space within tongue crack region and strings them to form a vector as color-texture feature of tongue crack. Finally this dissertation fuses shape feature of tongue crack region and color-texture feature of tongue crack to form tongue crack feature. Use tongue crack feature and linear support vector machine classifier to classify diagnostically physiological and pathological fissured tongue images. Experimental results demonstrate sensitivities of diagnosis and classification for physiological and pathological fissured tongue images are over 90% by using the approach proposed in this dissertation.
Third, this dissertation proposes a diagnostic model of tongue crack and under the guidance of the model this dissertation proposes algorithm of diagnostic classification for fissured tongue images of moderate-severe chronic superficial gastritis, chronic atrophic gastritis and gastric ulcer. The algorithm extracts tongue state feature by using Gabor wavelet transformation and springy discriminant analysis and takes linear support vector machine classifier to classify clinically these three kinds of fissured tongue images. Experimental results demonstrate sensitivities of diagnosis and classification for these three kinds of fissured tongue images are over 80% by using the approach proposed in this dissertation.
Finally, this dissertation proposes algorithm of computing pixel strength and gets strength image using it. This dissertation forms a gray-strength co-occurrence matrix and gets feature of tongue states by using the gray-strength co-occurrence matrix. Then this dissertation takes linear support vector machine classifier to classify clinically fissured tongue images diagnosed as yin deficiency syndrome and qi-blood deficiency syndrome according to TCM theory. Experimental results demonstrate sensitivities of diagnosis and classification for fissured tongue images diagnosed as yin deficiency syndrome and syndrome of qi-blood deficiency are over 85% by using the approach proposed in this dissertation.
Even though TCM tongue diagnosis was researched by using computerized technology in 1980's for the first time, people did not use tongue crack in computerized tongue diagnosis until the initial stages of 21 century. Up to now, there are only few papers about the use of tongue crack in computerized tongue diagnosis, and most of them are incomplete and not systematically. Thus, in-depth study is necessary. This dissertation fills up some blank areas about tongue crack in computerized tongue diagnosis to a certain extent. Research fruits of this dissertation would accelerate practical research on tongue crack in computerized tongue diagnosis and also possess potential application in medical clinic practice simultaneously.
引文
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