The Classification of Tongue Colors with Standardized Acquisition and ICC Profile Correction in Traditional Chinese Medicine.

Background and Goal. The application of digital image processing techniques and machine learning methods in tongue image classification in Traditional Chinese Medicine (TCM) has been widely studied nowadays. However, it is difficult for the outcomes to generalize because of lack of color reproducibi...

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Publicado en:BioMed Research International Vol. 2016; pp. 1 - 10
Autores principales: Qi, Zhen, Tu, Li-ping, Chen, Jing-bo, Hu, Xiao-juan, Xu, Jia-tuo, Zhang, Zhi-feng
Formato: equations & formulas research tables/charts Journal Article
Publicado: Wiley-Blackwell 12/6/2016
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 12/6/2016
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      pub: Wiley-Blackwell
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        10.1155/2016/3510807
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        atl: The Classification of Tongue Colors with Standardized Acquisition and ICC Profile Correction in Traditional Chinese Medicine.
      aug:
        au:
          Qi, Zhen
          Tu, Li-ping
          Chen, Jing-bo
          Hu, Xiao-juan
          Xu, Jia-tuo
          Zhang, Zhi-feng
        affil: Department of Basic Medical College, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Pudong New Area, Shanghai 201203, China
      sug:
        subj:
          Medicine, Chinese Traditional
          Tongue Anatomy and Histology
          Color
          Digital Imaging
          Technology, Medical
          Human
          Funding Source
      ab: Background and Goal. The application of digital image processing techniques and machine learning methods in tongue image classification in Traditional Chinese Medicine (TCM) has been widely studied nowadays. However, it is difficult for the outcomes to generalize because of lack of color reproducibility and image standardization. Our study aims at the exploration of tongue colors classification with a standardized tongue image acquisition process and color correction. Methods. Three traditional Chinese medical experts are chosen to identify the selected tongue pictures taken by the TDA-1 tongue imaging device in TIFF format through ICC profile correction. Then we compare the mean value of L*a*b* of different tongue colors and evaluate the effect of the tongue color classification by machine learning methods. Results. The L*a*b* values of the five tongue colors are statistically different. Random forest method has a better performance than SVM in classification. SMOTE algorithm can increase classification accuracy by solving the imbalance of the varied color samples. Conclusions. At the premise of standardized tongue acquisition and color reproduction, preliminary objectification of tongue color classification in Traditional Chinese Medicine (TCM) is feasible.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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