Aim The goal was to use a deep convolutional neural network to measure the radiographic
alveolar bone level to aid periodontal diagnosis. Materials and Methods A deep learning …

Background The purpose of this investigation was to develop a computer-assisted detection
system based on a deep convolutional neural network (CNN) algorithm and to evaluate the …

Objective Successful application of deep machine learning could reduce time-consuming
and labor-intensive clinical work of calculating the amount of radiographic bone loss (RBL) …

Background Radiographic periodontal bone loss is one of the most important basis for
periodontitis staging, with problems such as limited accuracy, inconsistency, and low …

We applied deep convolutional neural networks (CNNs) to detect periodontal bone loss
(PBL) on panoramic dental radiographs. We synthesized a set of 2001 image segments from …

We developed an automatic method for staging periodontitis on dental panoramic
radiographs using the deep learning hybrid method. A novel hybrid framework was …

In this study, a deep learning-based method for developing an automated diagnostic support
system that detects periodontal bone loss in the panoramic dental radiographs is proposed …

Purpose Periodontitis is the sixth most prevalent disease worldwide and periodontal bone
loss (PBL) detection is crucial for its early recognition and establishment of the correct …

Purpose The aim of the current study was to develop a computer-assisted detection system
based on a deep convolutional neural network (CNN) algorithm and to evaluate the …

Objectives Periapical periodontitis and caries are common chronic oral diseases affecting
most teenagers and adults worldwide. The purpose of this study was to develop an …