Periodontal Disease Detection Using Convolutional Neural Networks

In this paper, we propose a classification method of periodontal disease based on CNN. The data to used were the actual periodontal images and non-periodontal images. Data processing techniques such as resize, crop and zero-centralizing are used to improve data learning efficiency. The CNN Structure proposed in this paper has 224 × 224 × 3 size image as input data and 4 outputs according to periodontal state. We also use momentum optimization technique for neural network optimization.