Study on the Quantification of Traditional Chinese Medicine Tongue Color Classification Based on Hyperspectral Images
Objective Traditional Chinese medicine tongue diagnosis plays an important role in the clinical diagnosis and treatment of diseases,but the current research results are not applicable to the evaluation of clinical efficacy.This study conducted a hierarchical quantitative study on tongue color based on hyperspectral data of tongue images,making it suitable for clinical efficacy evaluation.Methods Establish inclusion and exclusion criteria,obtain tongue images of different spectral wavelengths within the visible light range of 400-1000 nm,and use traditional Chinese medicine clinical experts to distinguish between red tongue and yellow coating in four different color levels(mild,moderate,severe,and severe).Finally,establish a quantitative prediction model for the grade of red tongue and yellow coating based on machine learning models.Results There were significant differences in hyperspectral curve characteristics between red tongue and yellow coating with different color levels,which could be used as the basis for grade quantification.With the help of principal component analysis+random forest model,85.79%and 88.34%of the red tongue and yellow coating with different color levels could be predicted.Conclusion The use of hyperspectral image data features and machine learning models for predicting different color levels of tongue color has achieved good accuracy.
Traditional Chinese medicine tongue diagnosisHyperspectral featuresRed tongue and yellow coatingQuantification of indicatorsfeature extraction
NETL
NSTL
万方数据
