TOOTH DECAY DIAGNOSIS USING BACK PROPAGATION NEURAL NETWORK

摘要：

Artificial neural network (ANN), with its high performances in handling complex problems, has been widely used in medical image processing for clinical diagnostic application. In this paper, an ANN tooth decay diagnostic strategy was proposed and carefully experimented. A back propagation (BP) neural network was formed to analyze the X-ray image of patients teeth. With inter-pixel autocorrelation coefficients as its input feature vector, the network achieved considerable good performance in making differential diagnoses between decayed and normal teeth. The tooth decay detection accuracy was significantly improved comparing to the diagnosis made by a rule-based computer assisted program and a group of dentists 1.

关键词： Back propagation neural network Tooth decay diagnosis Medical image processing

作者: YANG YU YUN LI YU-JING LI JIAN-MING WANG DONG-HUI LIN WE-PING YE

作者单位: School of Information Science and Technology, Beijing Normal University, Beijing 100875,China;Basic Department of Operative Dentistry and Endodontics Faculty of Stomatology,Capital University of Medical Sciences, Beijing 100050,China School of Information Science and Technology, Beijing Normal University, Beijing 100875,China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 3956-3959

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）