Computer tomographic differential diagnosis of ameloblastoma and odontogenic keratocyst: classification using a convolutional neural network.

Objective: To analyse the automatic classification performance of a convolutional neural network (CNN), Google Inception v3, using tomographic images of odontogenic keratocysts (OKCs) and ameloblastomas (AMs).

Methods: For construction of the database, we selected axial multidetector CT images from patients with confirmed AM ( = 22) and OKC ( = 18) based on a conclusive histopathological report. The images ( = 350) were segmented manually and data augmentation algorithms were applied, totalling 2500 images.