title: The Classification of Tongue Colors with Standardized Acquisition and ICC Profile Correction in Traditional Chinese Medicine.
abstract: 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 ofL*a*b*of different tongue colors and evaluate the effect of the tongue color classification by machine learning methods.Results. TheL*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.
authors.affiliation: Department of Basic Medical College, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Pudong New Area, Shanghai 201203, China.
authors.forename: Zhen
authors.identifier: 0000-0002-2032-2985
authors.initials: Z
authors.lastname: Qi
authors.affiliation: Department of Basic Medical College, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Pudong New Area, Shanghai 201203, China.
authors.forename: Li-Ping
authors.initials: LP
authors.lastname: Tu
authors.affiliation: College of Computer Science and Technology, Jilin University, Jilin 130012, China.
authors.forename: Jing-Bo
authors.initials: JB
authors.lastname: Chen
authors.affiliation: Shanghai Collaborative Innovation Center of Health Service in Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Shanghai 201203, China.
authors.forename: Xiao-Juan
authors.initials: XJ
authors.lastname: Hu
authors.affiliation: Department of Basic Medical College, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Pudong New Area, Shanghai 201203, China.
authors.forename: Jia-Tuo
authors.identifier: 0000-0002-1738-4245
authors.initials: JT
authors.lastname: Xu
authors.affiliation: Department of Basic Medical College, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Pudong New Area, Shanghai 201203, China.
authors.forename: Zhi-Feng
authors.initials: ZF
authors.lastname: Zhang
mesh_terms: D019540:Area Under Curve; D003116:Color; D057225:Data Mining; D006801:Humans; D000069550:Machine Learning; D008516:Medicine, Chinese Traditional / Q000379:methods*; D060388:Support Vector Machine; D014059:Tongue / Q000502:physiology*