北京生物醫(yī)學(xué)工程

基于中醫(yī)舌象特征的痤瘡證型分類的初步研究

Preliminary study of acne syndrome classification based on the characteristics of tongue in TCM

作者：張新峰王虹貴明俊胡廣芹

單位：北京工業(yè)大學(xué)電子信息與控制工程學(xué)院（北京100124）

關(guān)鍵詞：中醫(yī)診斷；痤瘡；證型分類；舌象；圖像處理；貝葉斯網(wǎng)絡(luò)

分類號(hào)：R318.04

出版年·卷·期（頁(yè)碼）：2016·35·5（464-468）

摘要：

目的舌診是中醫(yī)診斷痤瘡的有效途徑，目前中醫(yī)通過(guò)觀察舌象來(lái)確定痤瘡患者的證候類型。由于痤瘡患者眾多，完全基于人工診斷的效率較低。本文提出一種基于圖像處理的痤瘡證型識(shí)別方法來(lái)輔助中醫(yī)診斷。方法首先，分別提取舌象的顏色、紋理和齒痕特征，然后使用貝葉斯網(wǎng)絡(luò)建模，找出特征與特征，特征與證型之間的關(guān)系，其中將齒痕提取算法進(jìn)行改進(jìn)，將計(jì)算凸包面積改進(jìn)為找到每個(gè)凸包的關(guān)鍵點(diǎn)，最后使用該算法對(duì)舌象進(jìn)行齒痕數(shù)量提取，并與中醫(yī)診斷結(jié)果相比較。結(jié)果對(duì)比醫(yī)生診斷結(jié)果，基于圖像處理的痤瘡證型自動(dòng)分類，分3類的正確率達(dá)83.87%，并直觀地表示出特征與特征，特征與證型之間的關(guān)系。結(jié)論使用圖像處理的方法進(jìn)行痤瘡證型的識(shí)別具有可行性，對(duì)計(jì)算機(jī)輔助痤瘡診斷的發(fā)展有一定幫助。

Objective Tongue diagnosis is one of the effective ways to diagnose acne. Traditional Chinese medicine (TCM) in treatment of acne is currently mainly determined by doctors to be observed in patients’ tongues. Because the number of patients with acne is numerous, the efficiency completely based on the artificial diagnosis is low. This paper presents a novel method for the diagnosis of acne syndromes with a computer to assist TCM diagnosis. Methods First of all, features of color, texture and teeth marks were extracted from acne tongues. Then we used Bayesian network to simulate the relationship between the features and syndromes, and completed the classification. The original extraction algorithm for teeth marks was improved from calculation of convex hull area to finding each key point of convex hull. Finally we used the algorithm to extract the number of teeth marks and compared with TCM diagnosis. Results The extraction results were consistented with TCM diagnosis. Compared with the TCM diagnosis, the accuracy of acne syndrome classification based on image processing was 83.87%, and intuitively showed the interaction between features and features, features and syndromes. Conclusions The results show the feasibility of image processing for the diagnosis of acne syndromes, which is beneficial to the development of auxiliary diagnosis of acne syndromes in TCM.

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