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Tongue Image Analysis pp 3–18Cite as

Introduction to Tongue Image Analysis

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Abstract

Tongue diagnosis is one of the most important and widely used diagnostic methods in Chinese medicine. Visual inspection of the human tongue offers a simple, immediate, inexpensive, and noninvasive solution for various clinical applications and self-diagnosis. Increasingly, powerful information technologies have made it possible to develop a computerized tongue diagnosis (CTD) system that is based on digital image processing and analysis. In this chapter, we first introduced the current state of knowledge on tongue diagnosis and CTD. Then, for the computational perspective, we provided brief surveys on the progress of tongue image analysis technologies including tongue image acquisition, preprocessing, and diagnosis classification.

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References

  • Haller, J. S. (1982). The foul tongue: A 19th century index of disease. Western Journal of Medicine, 137(3), 258–264.

    Google Scholar 

  • Reamy, B. V., Richard, D., & Bunt, C. W. (2010). Common tongue conditions in primary care. American Family Physician, 81(5), 627–634.

    Google Scholar 

  • Matison, R., Mayeux, R., Rosen, J., & Fahn, S. (1982). “Tip-of-the-tongue” phenomenon in Parkinson disease. Neurology, 32(5), 567–570.

    Article  Google Scholar 

  • Jeghers, H. (1942). Nutrition: The appearance of the tongue as an index of nutritional deficiency. New England Journal of Medicine, 227, 221–228.

    Article  Google Scholar 

  • Faria, P. D., Vargas, P. A., Saldiva, P., Böhm, G. M., Mauad, T., & Almeida, O. D. (2005). Tongue disease in advanced AIDS. Oral Diseases, 11(2), 72–80.

    Article  Google Scholar 

  • Peng, B., & Xie, S. (2006). Atlas of tongue diagnosis for AIDS patients. Shelton: People’s Medical Publishing House.

    Google Scholar 

  • Ozgursoy, O. B., Ozgursoy, S. K., Tulunay, O., Kemal, O., Akyol, A., & Dursun, G. (2009). Melkersson-Rosenthal syndrome revisited as a misdiagnosed disease. American Journal of Otolaryngology, 30(1), 33–37.

    Google Scholar 

  • Avraham, K. B., Schickler, M., Sapoznikov, D., Yarom, R., & Groner, Y. (1988). Down’s syndrome: Abnormal neuromuscular junction in tongue of transgenic mice with elevated levels of human Cu/Zn-superoxide dismutase. Cell, 54(6), 823–829.

    Article  Google Scholar 

  • Farman, A. G. (1976). Atrophic lesions of the tongue: A prevalence study among 175 diabetic patients. Journal of Oral Pathology, 5(5), 255–264.

    Article  Google Scholar 

  • Grushka, M. W., Ching, V., & Polak, S. (2007). Retrospective study: Prevalence of geographic and fissured tongue in patients with burning mouth syndrome. Oral Surgery, Oral Medicine, Oral Pathology, Oral Radiology & Endodontology, 103(6), 789.

    Article  Google Scholar 

  • Zargari, O. (2006). The prevalence and significance of fissured tongue and geographical tongue in psoriatic patients. Clinical and Experimental Dermatology, 31(2), 192–195.

    Article  Google Scholar 

  • Scheper, M. A., Nikitakis, N. G., Sarlani, E., Sauk, J. J., & Meiller, T. F. (2006). Cowden syndrome: Report of a case with immunohistochemical analysis and review of the literature. Oral Surgery, Oral Medicine, Oral Pathology, Oral Radiology & Endodontology, 101(101), 625–631.

    Google Scholar 

  • Han, S., Yang, X. I., Quan, Q. I., Pan, Y., Chen, Y., Shen, J., et al. (2016). Potential screening and early diagnosis method for cancer: Tongue diagnosis. International Journal of Oncology, 48(6), 2257–2264.

    Google Scholar 

  • Maciocia, G. (1995). Tongue diagnosis in Chinese medicine. Seattle: Eastland Press.

    Google Scholar 

  • Maciocia, G. (2004). Diagnosis in Chinese medicine: A comprehensive guide. London: Churchill Livingstone.

    Google Scholar 

  • Giovanni, M. (2015). The foundations of Chinese medicine. Elsevier Science Health Science Div.

    Google Scholar 

  • Tang, J.-L., Liu, B.-Y., & Ma, K.-W. (2008). Traditional Chinese medicine. Lancet, 372(8), 1938–1940.

    Google Scholar 

  • Fei, Z., & Gu, Y. (2007). Mirror of health: Tongue diagnosis in Chinese medicine. Beijing, China: People’s Medical Publishing House.

    Google Scholar 

  • Yang, Z. H., Zhang, D. P., & Nai-Min, L. I. (2009). Physiological and pathological tongueprint images of human body. Journal of Harbin Institute of Technology, 41(12), 73–77.

    Google Scholar 

  • Pang, B., Zhang, D., & Wang, K. (2005). Tongue image analysis for appendicitis diagnosis. Information Sciences, 175(3), 160–176.

    Google Scholar 

  • Huang, B., Wu, J., Zhang, D., & Li, N. (2010). Tongue shape classification by geometric features. Information Sciences an International Journal, 180(2), 312–324.

    Google Scholar 

  • Nai-Min, L. I., Zhang, D., & Kuan-Quan, W. (2011). Tongue diagnostics. Academy Press (Xue Yuan).

    Google Scholar 

  • Lukman, S., He, Y., & Hui, S. C. (2008). Computational methods for traditional Chinese medicine: A survey. Computer Methods and Programs in Biomedicine, 88(3), 283–294.

    Article  Google Scholar 

  • Feng, Y., Wu, Z., Zhou, X., Zhou, Z., & Fan, W. (2006). Knowledge discovery in traditional Chinese medicine: State of the art and perspectives. Artificial Intelligence in Medicine, 38(3), 219–236.

    Google Scholar 

  • Chiu, C. (1996). The development of a computerized tongue diagnosis system. Biomedical Engineering Applications Basis Communications, 8, 342–350.

    Google Scholar 

  • Pang, B., et al. (2004). Computerized tongue diagnosis based on Bayesian networks. IEEE Transactions on Biomedical Engineering, 51(10), 1803–1810.

    Article  Google Scholar 

  • Chiu, C. (2000). A novel approach based on computerized image analysis for traditional Chinese medical diagnosis of the tongue. Computer Methods and Programs in Biomedicine, 61(2), 77–89.

    Article  Google Scholar 

  • Zhang, D., Pang, B., Li, N., Wang, K., & Zhang, H. (2005). Computerized diagnosis from tongue appearance using quantitative feature classification. The American Journal of Chinese Medicine, 33(06), 859–866.

    Google Scholar 

  • Zhang, H. Z., Wang, K. Q., Zhang, D., Pang, B., & Huang, B. (2005). Computer aided tongue diagnosis system (pp. 6754–6757). IEEE.

    Google Scholar 

  • Sonka, M., Hlavac, V., & Boyle, R. (2014). Image processing, analysis, and machine vision. Australia: Cengage Learning.

    Google Scholar 

  • Gonzalez, R. C., & Woods, R. E. (2007). Digital image processing (3rd ed): Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  • Anzai, Y. (2012). Pattern recognition and machine learning. Amsterdam: Elsevier.

    Google Scholar 

  • Duda, R. O., Hart, P. E., & Stork, D. G. (2012). Pattern classification. New York: Wiley.

    Google Scholar 

  • Chang, C. (2003). Hyperspectral imaging: Techniques for spectral detection and classification (Vol. 1). Springer Science & Business Media.

    Google Scholar 

  • Kim, M. S., Chen, Y. R., & Mehl, P. M. (2001). Hyperspectral reflectance and fluorescence imaging system for food quality and safety. Transactions of the ASAE, 44(3), 721.

    Google Scholar 

  • Mooradian, G., Weiderhold, M., Dabiri, A. E., & Coyle, C. (1998). Hyperspectral imaging methods and apparatus for non-invasive diagnosis of tissue for cancer. Google Patents.

    Google Scholar 

  • Vo-Dinh, T. (2004). A hyperspectral imaging system for in vivo optical diagnostics. Engineering in Medicine and Biology Magazine, IEEE, 23(5), 40–49.

    Article  Google Scholar 

  • Zavattini, G., Vecchi, S., Mitchell, G., Weisser, U., Leahy, R. M., Pichler, B. J., et al. (2006). A hyperspectral fluorescence system for 3D in vivo optical imaging. Physics in Medicine & Biology, 51(8), 2029.

    Article  Google Scholar 

  • Du, H., et al. (2007). A novel hyperspectral medical sensor for tongue diagnosis. Sensor Review, 27(1), 57–60.

    Article  Google Scholar 

  • Li, Q., Wang, Y., Liu, H., Sun, Z., & Liu, Z. (2010a). Tongue fissure extraction and classification using hyperspectral imaging technology. Applied Optics, 49(11), 2006–2013.

    Article  Google Scholar 

  • Li, Q., Wang, Y., Liu, H., & Sun, Z. (2010). AOTF based hyperspectral tongue imaging system and its applications in computer-aided tongue disease diagnosis (pp. 1424–1427).

    Google Scholar 

  • Li, Q., Liu, J., Xiao, G., & Xue, Y. (2008). Hyperspectral tongue imaging system used in tongue diagnosis (pp. 2579–2581). IEEE.

    Google Scholar 

  • Liu, Z., Yan, J. Q., Zhang, D., & Li, Q. L. (2007). Automated tongue segmentation in hyperspectral images for medicine. Applied Optics, 46(34), 8328–8334.

    Google Scholar 

  • Li, Q., & Liu, Z. (2009). Tongue color analysis and discrimination based on hyperspectral images. Computerized Medical Imaging and Graphics, 33(3), 217–221.

    Article  MathSciNet  Google Scholar 

  • Zhi, L., Zhang, D., Yan, J. Q., Li, Q. L., & Tang, Q. L. (2007). Classification of hyperspectral medical tongue images for tongue diagnosis. Computerized Medical Imaging and Graphics, 31(8), 672–678.

    Google Scholar 

  • Yu, X., Jin, Z., Tan, G., et al. (1994). System of Automatic Diagnosis by Tongue Feature in Traditional Chinese Medicine. Chinese Journal of Scientific Instrument, 1, 13.

    Google Scholar 

  • Wong, W., & Huang, S. (2001). Studies on externalization of application of tongue inspection of TCM. Engineering Science, 3(1), 78–82.

    Google Scholar 

  • Cai, Y. (2002). A novel imaging system for tongue inspection (pp. 159–164): IEEE; 1999.

    Google Scholar 

  • Jang, J. H., Kim, J. E., Park, K. M., Park, S. O., Chang, Y. S., & Kim, B. Y. (2002). Development of the digital tongue inspection system with image analysis (pp. 1033–1034). IEEE.

    Google Scholar 

  • Wei, B. G., Shen, L. S., Wang, Y. Q., Wang, Y. G., Wang, A. M., & Zhao, Z. X. (2002). A digital tongue image analysis instrument for Traditional Chinese Medicine. Chinese Journal of Medical Instrumentation [Zhongguo yi liao qi xie za zhi], 26(3), 164–166.

    Google Scholar 

  • Wang, Y., Zhou, Y., Yang, J., & Xu, Q. (2004). An image analysis system for tongue diagnosis in traditional Chinese medicine. In Computational and Information Science (pp. 1181–1186): Springer.

    Google Scholar 

  • Kim, J., Jung, Y., Park, K., & Park, J. (2009). A digital tongue imaging system for tongue coating evaluation in patients with oral malodour. Oral Diseases, 15(8), 565–569.

    Article  Google Scholar 

  • He, Y., Liu, C., & Shen, L. (2007). Digital camera based tongue manifestation acquisition platform. World Science and Technology-Modernization of Traditional Chinese Medicine and Materia Medica, 5.

    Google Scholar 

  • Chang, Y., & Reid, J. F. (1996). RGB calibration for color image analysis in machine vision. Image Processing, IEEE Transactions on, 5(10), 1414–1422.

    Article  Google Scholar 

  • Wandell, B. A. (1987). The synthesis and analysis of color images. IEEE Transactions on Pattern Analysis and Machine Intelligence, (1), 2–13.

    Google Scholar 

  • Finlayson, G. D. (1996). Color in perspective. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(10), 1034–1038.

    Article  Google Scholar 

  • Barnard, K., & Funt, B. (2002). Camera characterization for color research. Color Research & Application, 27(3), 152–163.

    Google Scholar 

  • Yamamoto, K., Kitahara, M., Kimata, H., Yendo, T., Fujii, T., Tanimoto, M., et al. (2007). Multiview video coding using view interpolation and color correction. IEEE Transactions on Circuits and Systems for Video Technology, 17(11), 1436–1449.

    Article  Google Scholar 

  • Vrhel, M. J., & Trussell, H. J. (1999). Color device calibration: a mathematical formulation. IEEE Transactions on Image Processing, 8(12), 1796–1806.

    Article  Google Scholar 

  • Yamamoto, K., Kitahara, M., Kimata, H., Yendo, T., Fujii, T., Tanimoto, M., et al. (2006). Color calibration for multicamera system without color pattern board. Monash University DECSE Technical Report MECSE-4-2006.

    Google Scholar 

  • Vrhel, M., Saber, E., & Trussell, H. J. (2005). Color image generation and display technologies.

    Google Scholar 

  • Luo, M. R., Hong, G., & Rhodes, P. A. (2001). A study of digital camera colorimetric characterization based on polynomial modeling. Color: Research and applications, 26(1), 76–84.

    Google Scholar 

  • Cheung, V., Westland, S., Connah, D., & Ripamonti, C. (2004). A comparative study of the characterisation of colour cameras by means of neural networks and polynomial transforms. Coloration Technology, 120(1), 19–25.

    Article  Google Scholar 

  • Zhang, H., Wang, K., Jin, X., & Zhang, D. (2005). SVR based color calibration for tongue image (pp. 5065–5070). IEEE.

    Google Scholar 

  • Hu, M. C., Cheng, M. H., & Lan, K. C. (2016). Color correction parameter estimation on the smartphone and its application to automatic tongue diagnosis. Journal of Medical Systems, 40(1), 1–8.

    Article  Google Scholar 

  • Zhuo, L., Zhang, P., Qu, P., Peng, Y., Zhang, J., & Li, X. (2015). A K-PLSR-based color correction method for TCM tongue images under different illumination conditions. Neurocomputing, 174(9), 815–821.

    Google Scholar 

  • Shi, J., et al. (2000). Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8), 888–905.

    Article  Google Scholar 

  • Pal, N. R., & Pal, S. K. (1993). A review on image segmentation techniques. Pattern Recognition, 26(9), 1277–1294.

    Article  Google Scholar 

  • Zhu, S. C., et al. (1996). Region competition: Unifying snakes, region growing, and Bayes/MDL for multiband image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(9), 884–900.

    Article  Google Scholar 

  • Felzenszwalb, P. F., & Huttenlocher, D. P. (2004). Efficient graph-based image segmentation. International Journal of Computer Vision, 59(2), 167–181.

    Article  Google Scholar 

  • Shi, M. J., Li, G. Z., Li, F. F., & Xu, C. (2014). Computerized tongue image segmentation via the double geo-vector flow. Chinese Medicine, 9(1), 1–10.

    Article  Google Scholar 

  • Cui, Z., Zhang, H., Zhang, D., Li, N., & Zuo, W. (2013). Fast marching over the 2D Gabor magnitude domain for tongue body segmentation. Journal on Advances in Signal Processing, 2013(1).

    Google Scholar 

  • Wu, K., & Zhang, D. (2015). Robust tongue segmentation by fusing region-based and edge-based approaches. Expert Systems with Applications, 42(21), 8027–8038.

    Article  Google Scholar 

  • Kass, M., Witkin, A., & Terzopoulos, D. (1988). Snakes: Active contour models. International Journal of Computer Vision, 1(4), 321–331.

    Article  MATH  Google Scholar 

  • Wu, J., Zhang, Y., & Bai, J. (2006). Tongue area extraction in tongue diagnosis of traditional Chinese medicine (pp. 4955–4957). IEEE.

    Google Scholar 

  • Zhang, H., Zuo, W., Wang, K., & Zhang, D. (2006). A snake-based approach to automated segmentation of tongue image using polar edge detector. International Journal of Imaging Systems and Technology, 16(4), 103–112.

    Article  Google Scholar 

  • Pang, B., Zhang, D., & Wang, K. (2005a). The bi-elliptical deformable contour and its application to automated tongue segmentation in Chinese medicine. IEEE Transactions on Medical Imaging, 24(8), 946–956.

    Google Scholar 

  • Pang, B., Wang, K., Zhang, F., & Zhang, F. (2002). On automated tongue image segmentation in Chinese medicine (pp. 616–619). IEEE.

    Google Scholar 

  • Wang, Y., Zhou, Y., Yang, J., & Wang, Y. (2004). JSEG based color separation of tongue image in traditional Chinese medicine. In Progress in pattern recognition, image analysis and applications (pp. 503–508). Springer.

    Google Scholar 

  • Yu, S., Yang, J., Wang, Y., & Zhang, Y. (2007). Color active contour models based tongue segmentation in traditional Chinese medicine (pp. 1065–1068). IEEE.

    Google Scholar 

  • Ning, J., Zhang, D., Wu, C., & Yue, F. (2012). Automatic tongue image segmentation based on gradient vector flow and region merging. Neural Computing and Applications, 21(8), 1819–1826.

    Article  Google Scholar 

  • Cui, Y., Liao, S., & Wang, H. (2015). ROC-Boosting: A feature selection method for health identification using tongue image. Computational & Mathematical Methods in Medicine, 2015(25), 1–8.

    Google Scholar 

  • Cui, Y., Liao, S., Wang, H., Liu, H., Wang, W., & Yin, L. (2014). Relationship between Hyperuricemia and Haar-Like Features on Tongue Images. Biomed Research International, 2015, 1–10.

    Google Scholar 

  • Kim, J., Han, G., Ko, S. J., Nam, D. H., Park, J. W., Ryu, B., et al. (2014). Tongue diagnosis system for quantitative assessment of tongue coating in patients with functional dyspepsia: A clinical trial. Journal of Ethnopharmacology, 155(1), 709–713.

    Article  Google Scholar 

  • Li, C. H., & Yuen, P. C. (2002). Tongue image matching using color content. Pattern Recognition, 35(2), 407–419.

    Article  MATH  Google Scholar 

  • Li, C. H., & Yuen, P. C. (2000). Regularized color clustering in medical image database. IEEE Transactions on Medical Imaging, 19(11), 1150–1155.

    Article  Google Scholar 

  • Huang, B., & Li, N. (2008). Pixel based tongue color analysis. In Medical biometrics (pp. 282–289). Berlin: Springer.

    Google Scholar 

  • Huang, B., Zhang, D., & Zhang, H., Li, Y., & Li, N. (2011). Tongue color visualization for local pixel (pp. 297–301). IEEE.

    Google Scholar 

  • Huang, B., Zhang, D., Li, Y., Zhang, H., & Li, N. (2011). Tongue coating image retrieval (pp. 292–296). IEEE.

    Google Scholar 

  • Rubner, Y., Tomasi, C., & Guibas, L. J. (2000). The earth mover’s distance as a metric for image retrieval. International Journal of Computer Vision, 40(2), 99–121.

    Article  MATH  Google Scholar 

  • Wang, Y. G., Yang, J., Zhou, Y., & Wang, Y. Z. (2007). Region partition and feature matching based color recognition of tongue image. Pattern Recognition Letters, 28(1), 11–19.

    Google Scholar 

  • Yuen, P. C., Kuang, Z. Y., Wu, W., & Wu, Y. T. (2000). Tongue texture analysis using Gabor Wavelet opponent colour features for tongue diagnosis in traditional Chinese medicine. Series in Machine Perception and Artificial Intelligence, 40, 179–188.

    Article  Google Scholar 

  • Yuen, P. C., Kuang, Z. Y., Wu, W., & Wu, Y. T. (1999). Tongue texture analysis using opponent color features for tongue diagnosis in traditional Chinese medicine. In Proceedings of TAMV (pp. 21–27).

    Google Scholar 

  • Haralick, R. M., Shanmugam, K., & Dinstein, I. H. (1973). Textural features for image classification. IEEE Transactions on Systems, Man and Cybernetics, (6), 610–621.

    Google Scholar 

  • Miao, H. E. (2007). Red-prickled tongue image classification based on Gabor Wavelet and weighed features. Progress in Modern Biomedicine.

    Google Scholar 

  • Huang, B., & Li, N. (2010). Tongue image identification system on congestion of fungiform papillae (CFP). In Medical biometrics (pp. 73–82). Berlin: Springer.

    Google Scholar 

  • Heckerman, D. (1997). Bayesian networks for data mining. Data Mining and Knowledge Discovery, 1(1), 79–119.

    Article  Google Scholar 

  • Wang, H., & Zong, X. (2006). A new computerized method for tongue classification (pp. 508–511). IEEE.

    Google Scholar 

  • Ikeda, N., & Uozumi, T. (2005). Tongue diagnosis support system. The Hokkaido Journal of Medical Science [Hokkaido igaku zasshi], 80(3), 269–277.

    Google Scholar 

  • Watsuji, T., Arita, S., Shinohara, S., & Kitade, T. (1999). Medical application of fuzzy theory to the diagnostic system of tongue inspection in traditional Chinese medicine (pp. 145–148). IEEE.

    Google Scholar 

  • Hui, S. C., He, Y., & Thach, D. T. C. (2007). Machine learning for tongue diagnosis (pp. 1–5). IEEE.

    Google Scholar 

  • Kim, K. H., Do, J. H., Ryu, H., & Kim, J. Y. (2008). Tongue diagnosis method for extraction of effective region and classification of tongue coating (pp. 1–7). IEEE.

    Google Scholar 

  • Park, Y. J., Lee, J. M., Yoo, S. Y., & Park, Y. B. (2016). Reliability and validity of tongue color analysis in the prediction of symptom patterns in terms of East Asian Medicine. Journal of Traditional Chinese Medicine, 36(2), 165–172.

    Article  Google Scholar 

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Authors and Affiliations

  1. The Hong Kong Polytechnic University, Hong Kong, China

    David Zhang

  2. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China

    Hongzhi Zhang

  3. Department of Computer and Information Science, The University of Macau, Taipa, Macao

    Bob Zhang

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  1. David Zhang
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Correspondence to David Zhang .

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Zhang, D., Zhang, H., Zhang, B. (2017). Introduction to Tongue Image Analysis. In: Tongue Image Analysis. Springer, Singapore. https://doi.org/10.1007/978-981-10-2167-1_1

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