Title :
Clinical X-Ray Image Based Tooth Decay Diagnosis using SVM
Author :
Li, Wei ; Kuang, Wei ; Li, Yun ; Li, Yu-jing ; Ye, Wei-ping
Author_Institution :
Beijing Normal Univ., Beijing
Abstract :
Automatic tooth decay diagnosis achieved the satisfying results on the extracted tooth diagnosis by rule-based system and Artificial Neural Network (ANN). This paper, focusing on clinical tooth decay detection, introduces a Support Vector Machine (SVM) based diagnosis method. For comparison, an additional back propagation neural network (BPNN) tooth decay diagnosis experiment is reported. Comparative results indicate that SVM based method gives better performance than the one BPNN based.
Keywords :
backpropagation; image processing; neural nets; support vector machines; artificial neural network; back propagation neural network; clinical x-ray image; support vector machine; tooth decay diagnosis; Artificial neural networks; Cybernetics; Dentistry; Feature extraction; Image analysis; Machine learning; Support vector machine classification; Support vector machines; Teeth; X-ray imaging; BPNN; Clinical X-ray image; SVM; Tooth decay diagnosis;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370404
