Automating Periodontal bone loss measurement via dental landmark localisation.

ABSTRACT:

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 diagnosis and prognosis. Current radiographic assessment by clinicians exhibits substantial interobserver variation. Computer-assisted radiographic assessment can calculate bone loss objectively and aid in early bone loss detection. Understanding the rate of disease progression can guide the choice of treatment and lead to early initiation of periodontal therapy.

Methodology

We propose an end-to-end system that includes a deep neural network with hourglass architecture to predict dental landmarks in single, double and triple rooted teeth using periapical radiographs. We then estimate the PBL and di

SUBMITTER: Danks RP 

PROVIDER: S-EPMC8260405 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature