数字中医药（英文）2022，Vol.5Issue(1)：49-58,10.DOI:10.1016/j.dcmed.2022.03.005
基于多尺度卷积神经网络的舌象点刺识别模型建立与验证
Establishing and validating a spotted tongue recognition and extraction model based on multiscale convolutional neural network
摘要
Abstract
Objective In tongue diagnosis, the location, color, and distribution of spots can be used to speculate on the viscera and severity of the heat evil. This work focuses on the image analysis method of artificial intelligence (AI) to study the spotted tongue recognition of traditional Chinese medicine (TCM).Methods A model of spotted tongue recognition and extraction is designed, which is based on the principle of image deep learning and instance segmentation. This model includes multiscale feature map generation, region proposal searching, and target region recognition. Firstly, deep convolution network is used to build multiscale low- and high-abstraction fea-ture maps after which, target candidate box generation algorithm and selection strategy are used to select high-quality target candidate regions. Finally, classification network is used for classifying target regions and calculating target region pixels. As a result, the region segmenta-tion of spotted tongue is obtained. Under non-standard illumination conditions, various tongue images were taken by mobile phones, and experiments were conducted. Results The spotted tongue recognition achieved an area under curve (AUC) of 92.40％, an accuracy of 84.30％ with a sensitivity of 88.20％, a specificity of 94.19％, a recall of 88.20％, a regional pixel accuracy index pixel accuracy (PA) of 73.00％, a mean pixel accuracy (mPA) of 73.00％, an intersection over union (IoU) of 60.00％, and a mean intersection over union (mIoU) of 56.00％. Conclusion The results of the study verify that the model is suitable for the application of the TCM tongue diagnosis system. Spotted tongue recognition via multiscale convolutional neur-al network (CNN) would help to improve spot classification and the accurate extraction of pixels of spot area as well as provide a practical method for intelligent tongue diagnosis of TCM.关键词
点刺识别提取/舌象特征/实例分割/卷积神经网络/中医舌诊系统/人工智能Key words
Spotted tongue recognition and extrac-tion/The feature of tongue/Instance segmentation/Multiscale convolutional neural net-work (CNN)/Tongue diagnosis system/Artificial intelligence (AI)引用本文复制引用
彭成东,汪莉,蒋冬梅,杨诺,陈仁明,董昌武..基于多尺度卷积神经网络的舌象点刺识别模型建立与验证[J].数字中医药（英文）,2022,5(1):49-58,10.基金项目
Anhui Province College Natural Science Fund Key Project of China(KJ2020ZD77),and the Project of Education De-partment of Anhui Province(KJ2020A0379). （KJ2020ZD77）
