We develop a Computer Aided Diagnosis (CAD) system, which enhances the performance of dentists in detecting wide range of dental caries. The CAD System achieves this by acting as a second opinion for the dentists with way higher sensitivity on the task of detecting cavities than the dentists themselves. We develop annotated dataset of more than 3000 bitewing radiographs and utilize it for developing a system for automated diagnosis of dental caries. Our system consists of a deep fully convolutional neural network (FCNN) consisting 100+ layers, which is trained to mark caries on bitewing radiographs. We have compared the performance of our proposed system with three certified dentists for marking dental caries. We exceed the average performance of the dentists in both recall (sensitivity) and F1-Score (agreement with truth) by a very large margin. Working example of our system is shown in Figure 1.

开发了一种计算机辅助诊断系统(CAD)，可通过作为牙医的第二意见，显著提高检测牙齿龋齿的能力；该系统由深度完全卷积神经网络(FCNN)组成，可对近3000个全口X光片进行自动诊断。与三名牙医的平均表现相比，我们的系统在召回和F1-Score方面的表现显著更好。

基于深度学习的牙齿龋齿位翼射线照片检测