脑血管病患者舌象特征的提取与分析方法

Collection and analysis of characteristics of tongue manifestations in patients with cerebrovascular diseases

目的将图像分析技术引入中医舌诊的研究,提高舌诊的量化、客观化以及可重复性水平。方法利用舌象形态模型对舌苔、舌质的代表性区域进行了自动分割和提取,计算了包括颜色、形态、润燥程度在内的8维特征量,并对49例脑血管病患者和39例健康人的舌象进行了分析。结果k-means聚类方法和人工神经网络方法的分类正确率分别达到87.5%和92.0%,明显高于仅用舌苔或舌质的颜色特征量进行分类时的正确率。结论本文提取的8维特征量较为全面地描述了舌象的特征。本研究有助于推动图像分析技术在中医舌诊中的应用及研究。

Objective The technique of image analysis was introduced to die study of tongue inspection of Chinese medicine to improve the level of quantification, objectification and repeatability of tongue inspection. Methods The representative regions of tongue body and coating were separated and collected automatically in the model of tongue manifestations. Eight characteristic quantity variables of tongue manifestations, including colour, shape, wetnessdryness, etc., were computed and the tongue manifestations were analyzed in 49 patients with cerebrovascular diseases and 39 health people respectively. Results The correct rate reached 87.5% in the k-means and 92% in the method of artificial neural network respectively, which was obviously higher than that in the classification method according only to the colour characteristics of tongue body or coating. Conclusion Above eight characteristics reflect comprehensively the characteristics of tongue manifestations and are good for improving the application and research of the techniques of image analysis in tongue inspection of Chinese medicine.