中国中医药信息杂志2024，Vol.31Issue(1)：147-151,5.DOI:10.19879/j.cnki.1005-5304.202301297
舌下络脉的客观识别与颜色分类研究
Study on Objective Recognition and Color Classification of Sublingual Veins
摘要
Abstract
Objective To explore the method of objective identification of color information in sublingual veins diagnosis of TCM.Methods Combined with computer vision,compact fully convolution networks(CFCNs)and 19 deep learning classification models were used for study,and a double pulse rectangle algorithm was designed as a means of segmentation and recognition of sublingual veins and color information extraction.Results The accuracy of segmentation of tongue bottom obtained by the method of removing reflection + data expanding + data post-processing was 0.955 9,F1 value was 0.947 3,and mIoU value was 0.900 0.The accuracy of segmentation of sublingual veins obtained by the method of removing reflection + tongue input + data expanding + corrosion expansion was 0.778 4,F1 value was 0.738 3 and mIoU value was 0.585 1,which were obviously superior to the current classic or improved U-net model.On the color classification of sublingual veins,the best classification model was DenseNet161-bc-early_stopping with an accuracy rate of 0.803 7.Conclusion The deep learning method has a certain effect on identifying the color information of sublingual veins in TCM,which provides a new method for the research of quantitative color detection technology of sublingual veins diagnosis in TCM.关键词
舌下络脉诊/颜色特征/特征提取/深度学习Key words
sublingual veins diagnosis/color feature/feature extraction/deep learning分类
医药卫生引用本文复制引用
王立娟,钱鹏,杨帅,徐华,李福凤..舌下络脉的客观识别与颜色分类研究[J].中国中医药信息杂志,2024,31(1):147-151,5.基金项目
国家重点研发计划-中医药现代化研究重点专项(2018YFC1707602) （2018YFC1707602）
国家自然科学基金(81774205) （81774205）
上海中医药大学预算内项目(18TS083) （18TS083）
上海中医药大学杏林青年学者培养资助计划(2017年) （2017年）
