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___________多標記學習在中醫(yī)舌象分類中的研究_________ Research on multi-label learning in the classification of tongue images in TCM |
| 作者： 張靜 張新峰 王亞真 蔡軼珩 胡廣芹 |
| 單位： 北京工業(yè)大學電子信息與控制工程學院(北京100124) |
| 關鍵詞： 中醫(yī)；舌象；舌質；舌苔；多標記學習 |
| 分類號： R318.04 |
| 出版年·卷·期（頁碼）：2016·35·2（111-116） |
| 摘要： |
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目的 中醫(yī)舌診中，一幅舌象對應舌色、苔色和苔厚等多個類別，而且舌象的多個類別間存在一定的相關性。傳統(tǒng)的數(shù)據(jù)挖掘技術無法利用這些相關性同時進行建模，本文擬探索用多標記學習方法解決舌象這種多標記數(shù)據(jù)的分類問題。方法 首先對舌象進行苔質分離，分別提取舌質和舌苔的顏色特征，再對舌苔圖像分塊，提取每一塊的紋理特征，隨后通過多標記學習算法(multi-label learning by exploiting label dependency, LEAD)進行分類。最后將LEAD的分類結果和ML-kNN的結果進行對比，評價指標為漢明損失（Hamming loss）、平均精度（average precision）和(-評估)（-evaluation）。結果 相對于SVM等傳統(tǒng)的單標記學習算法，LEAD可以將多個類別同時賦予一幅舌圖像，而且在三個指標上的分類效果均優(yōu)于ML-kNN。結論 多標記LEAD算法用于舌象分類能夠使得對舌象的描述更全面、準確，可以輔助中醫(yī)進行舌診。 |
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Objective In tongue inspection of traditional Chinese medicine (TCM), a tongue image is associated with multiple labels of tongue body color, tongue coat color, the coat thickness and so on, and there are certain correlations between these labels. Modeling can not be carried on with the correlation at the same time by traditional data mining technology. So, we explore with multi-label learning to solve the classification of tongue images with multiple labels. Methods First, color features are extracted after separating tongue coat and tongue body, then blocking is done on tongue coat only and texture features are extracted on each block, and multi-label learning algorithm LEAD is subsequently used for classification. Finally, the classification results of LEAD and ML-kNN are compared, and the evaluation metrics adopted are Hamming loss, average precision and -evaluation. Results A set of proper labels can be assigned to a tongue image simultaneously through this method compared with the traditional single-label learning such as SVM. What’s more, LEAD can achieve better classification results on all the three metrics than ML-kNN. Conclusions LEAD can make the description of the tongue image more comprehensive and more accurate, providing an objective reference for the TCM tongue diagnosis. |
| 參考文獻： |
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地址：北京安定門外安貞醫(yī)院內北京生物醫(yī)學工程編輯部 電話：010-64456508 傳真：010-64456661 電子郵箱：[email protected] |