Deep learning-based identification of mesiodens using automatic maxillary anterior region estimation in panoramic radiography of children.

ABSTRACT:

Objectives

The purpose of this study is to develop and evaluate the performance of a model that automatically sets a region of interest (ROI) and diagnoses mesiodens in panoramic radiographs of growing children using deep learning technology.

Methods

Out of 988 panoramic radiographs, 489 patients with mesiodens were classified as an experimental group, and 499 patients without mesiodens were classified as a control group. This study consists of two networks. The first network (DeeplabV3plus) is a segmentation model that uses the posterior molar space to set the ROI in the maxillary anterior region with the mesiodens in the panoramic radiograph. The second network (Inception-resnet-v2) is a classification model that uses cropped maxillary anterior teeth to determine the prese

SUBMITTER: Kim J 

PROVIDER: S-EPMC9522977 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature