Deep Learning Techniques for Dental Image Diagnostics: A Survey

Nowadays, due to advancement in computer technology, there is an interest amongst researcher for use of Artificial Intelligence in medical field. Deep learning computational models are made out of various layers to find significant patterns from enormous images. Therefore, Deep learning techniques like CNN, R-CNN, LSTM were increasingly used in medical image diagnosis. CNN had proved to have noteworthy forthcoming to help specialists in different clinical fields. This growing trend of using CNN has also ventured into dental study. Various CNN architectures were used in dentistry like u-net, ResNet, VGG16, AlexNet for dental disease classification, tooth classification, caries detection, tooth segmentation. The motivation behind this survey paper is to visualize the best in class of deep learning techniques primarily CNN in dental applications/dentistry, such as the detection of caries, teeth, vertical root fracture, filled teeth, dental implants, and crown treatment. This will help researchers who are just starting out in dentistry field to grasp the various deep learning algorithms for dental disease classification and their performance metrics. Keywords: Artificial intelligence, CNN, dental application, images, classification, performance evaluation