DENSEN: a convolutional neural network for estimating chronological ages from panoramic radiographs.

ABSTRACT:

Background

Age estimation from panoramic radiographs is a fundamental task in forensic sciences. Previous age assessment studies mainly focused on juvenile rather than elderly populations (> 25 years old). Most proposed studies were statistical or scoring-based, requiring wet-lab experiments and professional skills, and suffering from low reliability.

Result

Based on Soft Stagewise Regression Network (SSR-Net), we developed DENSEN to estimate the chronological age for both juvenile and older adults, based on their orthopantomograms (OPTs, also known as orthopantomographs, pantomograms, or panoramic radiographs). We collected 1903 clinical panoramic radiographs of individuals between 3 and 85 years old to train and validate the model. We evaluated the model by the mean absolu

SUBMITTER: Wang X 

PROVIDER: S-EPMC9569056 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature