DOI QR코드

DOI QR Code

Medical Diagnosis Algorithm Based on Tongue Image on Mobile Device

  • Zhou, Zibo (School of Software, Nanchang Hangkong University) ;
  • Peng, Dongliang (School of Software, Nanchang Hangkong University) ;
  • Gao, Fumeng (Science and Technology College, Nanchang Hangkong University) ;
  • Leng, Lu (School of Software, Nanchang Hangkong University)
  • Received : 2019.04.24
  • Accepted : 2019.05.09
  • Published : 2019.06.30

Abstract

In traditional Chinese medical (TCM) science, tongue images can be observed for medical diagnosis; however, the tongue diagnosis of TCM is influenced by the subjective factors of doctors, and the diagnosis results vary from person to person. Quantitative TCM tongue diagnosis can improve the accuracy of diagnosis and increase the application value. In this paper, digital image processing and pattern recognition technologies are employed on mobile device to classify tongue images collected in different health states. First, through grayscale integral projection processing, the trough is found to localize the tongue body. Then the tongue body image is transferred from RGB color space to HSV color space, and the average H and S values are considered as the color features. Finally, the diagnosis results are obtained according to the relationship between the color characteristics and physical symptoms.

Keywords

tongue diagnosis;traditional Chinese medicine;image processing;mobile device

Acknowledgement

Supported by : National Natural Science Foundation of China, Jiangxi Provincial Department of Science and Technology, Ministry of Public Security of P. R. China

References

  1. Zhang B, Wang X, You J, et al. "Tongue color analysis for medical application." Evidence-Based Complementary and Alternative Medicine, pp. 1-11, Mar. 2013.
  2. Wei C C, Wang C H, Huang S W. "Using threshold method to separate the edge, coating and body of tongue in automatic tongue diagnosis. " The 6th International Conference on Networked Computing and Advanced Information Management, IEEE, pp. 653-656, Aug. 2010.
  3. Du J Q, Lu Y S, Zhu M F, Zhang K, Ding C H. "A novel algorithm of color tongue image segmentation based on HSI. " 2008 International Conference on BioMedical Engineering and Informatics, IEEE, vol. 1, pp. 733-737, May. 2008.
  4. Kass M, Witkin A, Terzopoulos D. "Snakes: Active contour models." International Journal of Computer Vision, vol. 1, no. 4, pp. 321-331, Jan. 1988. https://doi.org/10.1007/BF00133570
  5. Zhang H, Zuo W, Wang K, et al. "A snake-based approach to automated segmentation of tongue image using polar edge detector. " International Journal of Imaging Systems and Technology, vol. 16, no. 4, pp. 103-112, Feb. 2007.
  6. Zhai X, Lu H, Zhang L. "Application of image segmentation technique in tongue diagnosis." International Forum on Information Technology and Applications, IEEE, vol. 2, pp. 768-771. 2009.
  7. Miao J S, Li G Z, Li F. "C2G2FSnake: automatic tongue image segmentation utilizing prior knowledge." Science China Information Sciences, vol. 56, no. 9, pp. 1-14, Sep. 2013.
  8. Gao Q H, Gang j, Wang Y H, et al. "Tongue image segmentation based on two-dimensional maximum inter-class variance and mathematical morphology." Computer and Digital Engineering, vol. 45, no. 6, pp. 1200-1203, 2017.
  9. Kanawong R, Xu W, Xu D, et al. "An automatic tongue detection and segmentation framework for computer-aided tongue image analysis." International Journal of Functional Informatics and Personalised Medicine, vol. 4, no. 1, pp. 56-58, Nov. 2012. https://doi.org/10.1504/IJFIPM.2012.050420
  10. Li Z, Yu Z, Liu W, et al. "Tongue image segmentation via thresholding and clustering." IEEE 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), pp. 1-5, Oct. 2017.
  11. Huang B, Wu J, Zhang D, et al. "Tongue shape classification by geometric features." Information Sciences, vol. 180, no. 2, Jan. 2010.
  12. Zhang H Z, Wang K Q, Zhang D, et al. "Computer aided tongue diagnosis system." 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, pp. 6754-6757, Jan. 2006.
  13. Wang Y, Zhou Y, Yang J, et al. "An image analysis system for tongue diagnosis in traditional Chinese medicine." International Conference on Computational and Information Science, Springer Berlin Heidelberg, pp. 1181-1186, 2004.
  14. Kanawong R. "Computer-aided tongue image diagnosis and analysis." University of Missouri-Columbia, 2012.
  15. Hu M C, Cheng M H, Lan K C. "Color correction parameter estimation on the smartphone and its application to automatic tongue diagnosis." Journal of medical systems, vol. 40, no. 1, pp. 18, Jan. 2016. https://doi.org/10.1007/s10916-015-0387-z
  16. Zhang Q, Shang H L, Zhu J, et al. "A new tongue diagnosis application on Android platform." 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE, pp.334-327, 2013.
  17. Han X, Fu Y, Zhang H. "A fast two-step marker-controlled watershed image segmentation method." IEEE International Conference on Mechatronics and Automation, pp. 1275-1380, Aug. 2012.
  18. Dhanalakshmi M, Premchand P, Goverdhan A. "Applying linear wavelet transforms and statistical feature analysis for digital tongue image" Pattern Recognition Letters, vol. 16, no. 1, pp. 95-102, 2014
  19. Wang Y G, Yang J, Zhou Y, et al. "Region partition and feature matching based color recognition of tongue image." Pattern Recognition Letters, vol. 28, no. 1, pp. 11-19, Jan. 2007.
  20. Pang B, Zhang D, Wang K. "Tongue image analysis for appendicitis diagnosis." Information Sciences, vol. 175, no. 3, pp. 160-176, Oct. 2005.
  21. Wang X, Zhang D. "A high quality color imaging system for computerized tongue image analysis." Expert systems with Applications, vol. 40, no. 15, pp. 5854-5866, Nov. 2013.