An Effective Approach for Classification of Dental Caries using Convolutional Neural Networks

Abstract

In 20th century, Dental Caries have become a major health issue globally. According to WHO, 2.3 billion adults and 530 million children are suffering from dental caries-related issues. This problem can be controlled by early accurate detection and treatments. There exist many approaches in the literature to classify dental caries. But accuracy of these approaches is still a challenge. This paper proposes an effective approach using convolutional neural networks by adopting VGG16 and VGG19 models. The patient’s X-Ray images have been collected and labeled. The proposed models have been compared on the collected datasets. The results over this dataset indicate the superiority of VGG19 based model with 95% accuracy as compared to VGG16 based model with 91% accuracy.