Advances in Tongue Diagnosis Objectification of Traditional Chinese Medicine

Tongue diagnosis is a non-invasive,efficient,and accurate method for determining a person’s physical condition,and plays an essential role in disease diagnosis and health management.However,tongue diagnosis is easily influenced by the subjective experience of the practitioner and the light environment.In addition,tongue diagnosis lacks clear quantitative indicators and objective records.This all limits the transmission and development of tongue diagnosis.Therefore,the acquisition and analysis of tongue information using image equipment,image processing and computer vision have become a hot research topic for the objectification of tongue diagnosis.This paper reviews the research progress of tongue diagnosis objectification in Traditional Chinese medicine.The tongue image acquisition,color correction,segmentation,feature extraction and analysis,and disease prediction included in the study of tongue diagnosis objectification are reviewed.The shortcomings of current automated tongue diagnosis systems and future research ideas are also summarized to provide a reference for further development of tongue diagnosis objectification.

Application of artificial intelligence in tongue diagnosis of traditional Chinese medicine:A review

Tongue diagnosis is an important process to non-invasively assess the condition of a patient’s internal organs in traditional Chinese medicine(TCM)and each part of the tongue is related to corresponding internal organs.Due to continuing computer technological advances,especially the artificial intelligence(AI)methods have achieved significant success in tackling tongue image acquisition,processing,and classification,novel AI methods are being introduced in traditional Chinese medicine tongue diagnosis medical practices.Traditional tongue diagnose depends on observations of tongue characteristics,such as color,shape,texture,moisture,etc.by traditional Chinese medicine physicians.The appearance of the tongue color,texture and coating reflects the improvement or deterioration of patient’s conditions.Moreover,AI can now distinguish patient’s condition through tongue images,texture or coating,which is all possible increasingly with help from traditional Chinese medicine physicians under the traditional Chinese medicine tongue theory.AI has enabled humans to do what was previously unimagined:traditional Chinese medicine tongue diagnosis with feeding a large amount of tongue image and tongue texture/coating data to train the AI modes.This review focuses on the research advances of AI in TCM tongue diagnosis thus far to identify the major scientific methods and prospects.In this article,we tried to review the AI application in resolving the tongue diagnosis of traditional Chinese medicine on color correction,tongue image extraction,tongue texture/coating segmentation.

Tongue diagnosis based on hue-saturation value color space: controlled study of tongue appearance in patients treated with percutaneous coronary intervention for coronary heart disease

Objective To analyze the characteristics of tongue imaging color parameters in patients treated with percutaneous coronary intervention(PCI)and non-PCI for coronary atherosclerotic heart disease(CHD),and to observethe effects of PCI on the tongue images of patients as a basis for the clinical diagnosis and treatment of patientswith CHD.Methods This study used a retrospective cross-sectional survey to analyze tongue photographs and medicalhistory information from 204 patients with CHD between November 2018 and July 2020.Tongue images ofeach subject were obtained using the Z-BOX Series traditional Chinese medicine(TCM)intelligent diagnosisinstruments,the SMX System 2.0 was used to transform the image data into parameters in the HSV color space,and finally the parameters of the tongue image between patients in the PCI-treated and non-PCI-treated groupsfor CHD were analyzed.Results Among the 204 patients,112 were in the non-PCI treatment group(38 men and 74 women;average age of(68.76±9.49)years),92 were in the PCI treatment group(66 men and 26 women;average age of(66.02±10.22)years).In the PCI treatment group,the H values of the middle and tip of the tongue and the overall coating of thetongue were lower(P<0.05),while the V values of the middle,tip,both sides of the tongue,the whole tongueand the overall coating of the tongue were higher(P<0.05).Conclusion The color parameters of the tongue image could reflect the physical state of patients treated withPCI,which may provide a basis for the clinical diagnosis and treatment of patients with CHD.

A historical evaluation of Chinese tongue diagnosis in the treatment of septicemic plague in the pre-antibiotic era, and as a new direction for revolutionary clinical research applications

Chinese tongue diagnosis was initially developed to quickly and efficiently diagnose and prescribe medicine, while at the same time allowing the doctor to have minimal contact with the patient. At the time of its compiling, the spread of Yersinia pestis, often causing septicaemia and gangrene of the extremities,may have discouraged doctors to come in direct contact with their patients and take the pulse.However, in recent decades, modern developments in the field of traditional Chinese medicine, as well as the spread of antibiotics in conjunction with the advancements of microbiology, have overshadowed the original purpose of this methodology. Nevertheless, the fast approaching post-antibiotic era and the development of artificial intelligence may hold new applications for tongue diagnosis. This article focuses on the historical development of what is the world＇s earliest tongue diagnosis monograph, and discusses the directions that such knowledge may be used in future clinical research.

Boym’s "De Indiciis Morborum ex Linguae Coloribus et Affectionibus" : The Earliest Chinese Tongue Diagnosis Manual Published in Europe, Identification of Original Chinese Text, Peculiarities of Printed Edition and Its Impact on European Medicine

Upon his untimely death,Michal Boym(1612–1659)left behind an enormous written legacy;covering a diverse range of interests in fields such as Chinese linguistics,cartography,botany,zoology,philosophy and medicine.This article attempts to examine Boym’s De indiciis morborum ex linguae coloribus&affectionibus(The signs of disease on the tongue,colors and affections),a translation of a previously unidentified Chinese text.The text specifically deals with the subject of tongue diagnosis,in relation to contagious diseases that were still raging in the17 th century China.Arriving to China at the end of the Ming Dynasty(1368–1644),Boym was able to personally witness the early development of tongue examination as an independent specialty;he recognized its significance and tried to incorporate it into his ultimately unfinished Chinese medical corpus.Boym’s work eventually facilitated the assimilation of tongue observation in European medicine during the 19 th century.

Establishing and validating a spotted tongue recognition and extraction model based on multiscale convolutional neural network

Objective In tongue diagnosis,the location,color,and distribution of spots can be used to speculate on the viscera and severity of the heat evil.This work focuses on the image analysis method of artificial intelligence(AI)to study the spotted tongue recognition of traditional Chinese medicine(TCM).Methods A model of spotted tongue recognition and extraction is designed,which is based on the principle of image deep learning and instance segmentation.This model includes multiscale feature map generation,region proposal searching,and target region recognition.Firstly,deep convolution network is used to build multiscale low-and high-abstraction feature maps after which,target candidate box generation algorithm and selection strategy are used to select high-quality target candidate regions.Finally,classification network is used for classifying target regions and calculating target region pixels.As a result,the region segmentation of spotted tongue is obtained.Under non-standard illumination conditions,various tongue images were taken by mobile phones,and experiments were conducted.Results The spotted tongue recognition achieved an area under curve(AUC)of 92.40%,an accuracy of 84.30%with a sensitivity of 88.20%,a specificity of 94.19%,a recall of 88.20%,a regional pixel accuracy index pixel accuracy(PA)of 73.00%,a mean pixel accuracy(m PA)of73.00%,an intersection over union(Io U)of 60.00%,and a mean intersection over union(mIo U)of 56.00%.Conclusion The results of the study verify that the model is suitable for the application of the TCM tongue diagnosis system.Spotted tongue recognition via multiscale convolutional neural network(CNN)would help to improve spot classification and the accurate extraction of pixels of spot area as well as provide a practical method for intelligent tongue diagnosis of TCM.

Recent Progresses in Analysis of Tongue Manifestation for Traditional Chinese Medicine

Tongue diagnosis is one of the most precious and widely used diagnostic methods in Traditional Chinese Medicine (TCM). However, due to its subjective, qualitative and experience-dependent nature, the studies on tongue characterization have been widely emphasized. This paper surveys recent progresses in analysis of tongue manifestation. These new developments include the cross-network and cross-media color reproduction of tongue image, the automatic segmentation of tongue body based on knowledge, the automatic analysis of curdiness and griminess for the tongue fur and the automatic analysis of plumpness, wryness and dot -thorn of tongue body. The clinic experiments verify the validity of these new methods.

Fusion Based Tongue Color Image Analysis Model for Biomedical Applications

Tongue diagnosis is a novel and non-invasive approach commonly employed to carry out the supplementary diagnosis over the globe.Recently,several deep learning(DL)based tongue color image analysis models have existed in the literature for the effective detection of diseases.This paper presents a fusion of handcrafted with deep features based tongue color image analysis(FHDF-TCIA)technique to biomedical applications.The proposed FDHF-TCIA technique aims to investigate the tongue images using fusion model,and thereby determines the existence of disease.Primarily,the FHDF-TCIA technique comprises Gaussian filtering based preprocessing to eradicate the noise.The proposed FHDF-TCIA model encompasses a fusion of handcrafted local binary patterns(LBP)withMobileNet based deep features for the generation of optimal feature vectors.In addition,the political optimizer based quantum neural network(PO-QNN)based classification technique has been utilized for determining the proper class labels for it.A detailed simulation outcomes analysis of the FHDF-TCIA technique reported the higher accuracy of 0.992.

Template Guided Live Wire and Its Application on Automatic Extraction of Tongue in Digital Image

In this paper, we propose a novel automatic object extraction algorithm, named the Template Guided Live Wire, based on the popularly used live-wire techniques. We discuss in details the novel method’s applications on tongue extraction in digital images. With the guides of a given template curve which approximates the tongue’s shape, our method can finish the extraction of tongue without any human intervention. In the paper, we also discussed in details how the template guides the live wire, and why our method functions more effectively than other boundary based segmentation methods especially the snake algorithm. Experimental results on some tongue images are as well provided to show our method’s better accuracy and robustness than the snake algorithm.

Noninvasive Diagnostic Technique for Nonalcoholic Fatty Liver Disease Based on Features of Tongue Images

Objective:To investigate a new noninvasive diagnostic model for nonalcoholic fatty liver disease(NAFLD) based on features of tongue images.Methods:Healthy controls and volunteers confirmed to have NAFLD by liver ultrasound were recruited from China-Japan Friendship Hospital between September 2018 and May 2019,then the anthropometric indexes and sampled tongue images were measured.The tongue images were labeled by features,based on a brief protocol,without knowing any other clinical data,after a series of corrections and data cleaning.The algorithm was trained on images using labels and several anthropometric indexes for inputs,utilizing machine learning technology.Finally,a logistic regression algorithm and a decision tree model were constructed as 2 diagnostic models for NAFLD.Results:A total of 720 subjects were enrolled in this study,including 432 patients with NAFLD and 288 healthy volunteers.Of them,482 were randomly allocated into the training set and 238 into the validation set.The diagnostic model based on logistic regression exhibited excellent performance:in validation set,it achieved an accuracy of 86.98%,sensitivity of 91.43%,and specificity of 80.61%;with an area under the curve(AUC) of 0.93 [95% confidence interval(CI) 0.68–0.98].The decision tree model achieved an accuracy of 81.09%,sensitivity of 91.43%,and specificity of 66.33%;with an AUC of 0.89(95% CI 0.66–0.92) in validation set.Conclusions:The features of tongue images were associated with NAFLD.Both the 2 diagnostic models,which would be convenient,noninvasive,lightweight,rapid,and inexpensive technical references for early screening,can accurately distinguish NAFLD and are worth further study.

Dark red tongue color formation caused by hyperglycemia is attributed to decreased blood flow of tongue tissue partially due to nuclear factor-kappa B pathway activation

OBJECTIVE:To investigate the potential mechanisms underlying the dark red tongue color formation induced by hyperglycemia.METHODS:A high-fat diet and intraperitoneal injection of streptozotocin were used to establish a diabetes model.The color and blood flow of tongues were analyzed by the Tongue Diagnosis Analysis System and laser Doppler flowmetry,respectively.Inflammatory factors and adhesion factors were measured in the circulation and tongue tissue by an enzyme-linked immunosorbent assay.Western blotting was employed to evaluate nuclear factor-kappa B(NF-κB)p50 and inhibitor of kappa B kinase protein expression levels in the tongue.Then,the NF-κB inhibitor,pyrrolidine dithiocarbamic acid ammonium salt was utilized to repress NF-κB pathway activation to validate that the NF-κB pathway plays a key role in blood flow and dark red tongue color formation.RESULTS:The diabetic rats displayed a dark red tongue color that was accompanied by NF-κB pathway activation and decreased blood flow in the tongue.These effects could be reversed by the NF-κB inhibitor.CONCLUSIONS:Our investigation demonstrated that hyperglycemia led to dark red tongue color formation by decreasing blood flow in the tongue,which was partly due to NF-κB pathway activation.

Objectified Study on Tongue Images of Patients with Lung Cancer of Different Syndromes

Objective：To describe the characteristic of tongue images of patients with lung cancer of different Chinese medicine（CM） syndromes and to reveal the elemental rule on the changes of the tongue images. Methods：A total of 207 patients with lung cancer were divided into four syndrome groups according to the theory of CM：Fei（肺） and Shen（肾） deficiency syndrome（Group A,72 cases）,Pi（脾） deficiency and phlegm dampness syndrome（Group B,57 cases）,phlegm-heat retention in Fei（Group C,36 cases） and yin asthenia generating intrinsic heat syndrome（Group D,42 cases）.The tongue parameters were detected by tongue image digital analysis instrument,and the tongue images were described with qualitative,tongue color and quantitative analysis,respectively.The International Commission on Illumination（CIE） L~＊a~＊b~＊（CIELAB） color model was used for the quantitative classification.Results：There was a significant statistical difference between different syndrome groups of lung cancer on tongue color,coating color,and thickness of tongue coating（P0.01）,and there was significant statistical difference between the four syndrome groups on Lab values of the tongue and coating（P0.05）.The correct identification rate of discriminant function on the raw data was 65.7%,including 72.2%for Group C,69.4%for Group A,69.0%for Group D and 54.4%for Group B.Conclusions：A tongue image digital analysis instrument can objectively describe the tongue features of patients with different syndromes of lung cancer.The tongue diagnosis is very important to syndrome differentiation in CM.Tongue diagnosis should be combined with some important characteristics of syndromes in the future to establish a＂combination of four examination methods,including inspection,auscultation,interrogation,and pulse-feeling and palpation＂in the tongue diagnostic system.

Pathological Change of Chronic Hepatitis B Patients with Different Tongue Coatings by Circular Multi-omics Integrated Analysis

Objective:To compare the circular pathological changes of chronic hepatitis B(CHB)patients according to the tongue diagnosis.Methods:Totally 41 CHB patients with typical white tongue coating(WTC)or yellow tongue coating(YTC)were enrolled and 14 healthy volunteers with normal tongue manifestation served as controls.The mRNA expression of peripheral leukocytes was detected by GeneChips,and 9 genes were randomly selected for expression validation.Circular metabolites were detected by gas chromatographymass spectrometry.Biological information was analyzed based on ingenuity pathways analysis or metabolomics database and the integrated networks were constructed by ClueGO.Results:A total of 945 and 716 differentially expressed genes were found in patients with WTC and YTC relative to healthy volunteers respectively.The biological information analysis indicated that CHB patients had obviously increased functions in cell death,apoptosis and necrosis(Z-score 2,P<0.05)and decreased activation in T lymphocytes(Z-score–2,P<0.05),regardless of the tongue manifestation.Compared to patients with WTC,the YTC patients were predicted to be more active in functions related to virus replication(Z-score 2,P<0.05),and the content of circular fatty acids,such as oleic acid(P=0.098)and lauric acid(P=0.035),and citric acid cycle-related metabolites were higher in the YTC patients(P<0.1).The integrated analysis based on differential genes and metabolites indicated that the most difference in the biological function network between the WTC and YTC patients was tumor necrosis factor receptor associated factor 6 mediated-nuclear factor kappa-B activation process.Conclusions:CHB patients with YTC had more severe inflammation and fatty acids metabolism aberrant than patients with WTC.The results facilitate the modern pathological annotation of Chinese medicine tongue diagnosis theory and provide a reference for the interpretation of pharmacological mechanisms of Chinese medicine treatment.

Digital tongue image analyses for health assessment

Traditional Chinese Medicine(TCM),as an effective alternativemedicine,utilizes tongue diagnosis as a major method to assess the patient’shealthstatusbyexaminingthe tongue’s color,shape,and texture.Tongue images can also give the pre-disease indications without any significant disease symptoms,which provides a basis for preventive medicine and lifestyle adjustment.However,traditional tongue diagnosis has limitations,as the process may be subjective and inconsistent.Hence,computer-aided tongue diagnoses have a great potential to provide more consistent and objective health assessments.This paper reviewed the current trends in TCMtongue diagnosis,including tongue image acquisition hardware,tongue segmentation,feature extraction,color correction,tongue classification,and tongue diagnosis system.We also present a case of TCM constitution classification based on tongue images.

Effect of Salivary Antimicrobial Factors on Microbial Composition of Tongue Coating in Patients with Coronary Heart Disease with Phlegm-Stasis Syndrome

Objective: Phlegm-stasis syndrome is one of the most common traditional Chinese medicine(TCM) syndromes and found in 59% of patients with coronary heart disease(CHD) in routine TCM clinical practice in China. One of the diagnostic criteria of phlegm-stasis syndrome is its characteristic white-greasy and thin tongue coating. We have previously reported that different types of tongue coating have different microbiome characteristics that can be used as diagnostic markers. However, the microbial characteristics of tongue coating of CHD patients with phlegm-stasis syndrome, including coating feature and underlying reason of formation, have rarely been reported. Herein, we examined the characteristic microbiome of tongue coating, and discussed the cause of tongue coating formation via salivary proteins in patients with phlegm-stasis syndrome. Methods: We examined white-greasy and thin tongue coatings obtained from 10 patients with CHD having phlegm-stasis syndrome(n = 10), and compared with those of patients with almost no coating – patients with Qi-Yin deficiency syndrome(n = 10) – and healthy controls(n = 10). 16S r RNA sequencing of tongue coating microbiome and isobaric tags for relative and absolute quantitation(i TRAQ)-based quantitative analysis of salivary proteins were used to detect tongue coating and salivary protein separately. Salivary levels of s Ig A, lysozyme, and amylase were detected by ELISA. Results: We identified Candidatus_Saccharimonas and Candidate_division_TM7_norank as the prominent members of tongue coating in patients with CHD having phlegm-stasis syndrome. Salivary proteins involved in biological processes, pentose phosphate pathway, and complement and coagulation cascades were among the differentially expressed proteins identified in patients with CHD having phlegm-stasis syndrome on i TRAQ analysis. Moreover, the formation of microbiota in tongue coating was associated with salivary s Ig A, lysozyme, and saliva flow rate. Conclusions: We explored the characteristics of microbial composition of tongue coating patients with CHD having phlegm-stasis syndrome and identified correlations between salivary proteins and microbiome formation, providing a theoretical and mechanistic basis for tongue coating formation.

Research on Tongue Image Collection and Analysis Based on Smartphone

Tongue diagnosis is a diagnostic method to understand the physiological functions and pathological changes of the human body by observing human tongue quality,tongue coating,and sublingual collateral veins.Tongue elephant research is an important part of objective Chinese medicine.Based on the research of tongue image analysis method,the design of a tongue image collection analysis system based on the smartphone platform was demonstrated.This research uses a smartphone camera to collect tongue images,upload them to the server and complete tongue image analysis on the server.Finally,the tongue image analysis results are generated,and the results are transmitted from the server to the smartphone mobile terminal.We used HTTP protocol for communication between mobile client and server.We asked professional TCM doctors to evaluate the results of tongue analysis in 100 cases,and the final anastomosis rate was above 80%.This study fills in the gaps in the mobile platform of objectification of tongue diagnosis,which is conducive to the use of mobile phones to collect tongue images anytime,anywhere,and to conveniently share the results of tongue diagnosis with physicians.With an Internet connection,users can use their smartphones to remotely diagnose their tongues,who can store and generate their own personal diagnostic reports.

Treatment on 2 cases of pain in the heel based on syndrome differentiation by wrist-ankle acupuncture

Two patients with pain in the heel were treated by new methods based on symptom differentiation after regular wrist-ankle acupuncture were invalid. According to the manifestations in tongue diagnosis and symptoms,the 2 cases both belonged to bladder excess syndrome,the acupuncture was carried out on area 6 of low limb（external anterior border of achilles tendon at three finger wide above the lateral malleolus）,and acupuncture was also carried out on Zútōnggǔ（足通谷 BL 66）,Jīnmén（金门 BL 63） and Shēnmài（申脉 BL 62） at the le side. The results showed that the therapeu c effi cacy of treatments on the 2 pa ents was sa sfactory and thus the clinical values for new methods for using wrist-ankle acupuncture based on syndrome differentiation were verified.