Estimation of Alveolar Bone Loss in Periodontitis Using Machine Learning.

ABSTRACT:

Aim

The objective of this research was to perform a pilot study to develop an automatic analysis of periapical radiographs from patients with and without periodontitis for the percentage alveolar bone loss (ABL) on the approximal surfaces of teeth using a supervised machine learning model, that is, convolutional neural networks (CNN).

Material and methods

A total of 1546 approximal sites from 54 participants on mandibular periapical radiographs were manually annotated (MA) for a training set (n = 1308 sites), a validation set (n = 98 sites), and a test set (n = 140 sites). The training and validation sets were used for the development of a CNN algorithm. The algorithm recognised the cemento-enamel junction, the most apical extent of the alveolar crest, the apex, and the surr

SUBMITTER: Tsoromokos N 

PROVIDER: S-EPMC9485533 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature