Comparison of AudaxCeph®'s fully automated cephalometric tracing technology to a semi-automated approach by human examiners
Document Type
Article
Publication Date
12-1-2022
Publication Title
International orthodontics
Abstract
OBJECTIVE: To compare the reliability of cephalometric landmark identification by an automated tracing software based on convolutional neural networks to human tracers. MATERIALS AND METHODS: Sixty cephalograms were traced by two board-certified orthodontists and AudaxCeph®'s artificial intelligence software. The following thirteen landmarks were identified in each tracing: Sella, Nasion, A point, B point, Porion, Menton, Pogonion, Orbitale, Gonion, Upper Central Incisor Incisal Edge (U1 Tip), Upper Central Incisor Root Apex (U1 apex), Lower Central Incisor Incisal Edge (L1 Tip), Lower Central Incisor Root Apex (L1 apex). An x-y axis was positioned in the bottom left corner of each cephalogram, and the x- and y-coordinates for the landmarks were exported into Excel. Distributions of landmarks (X, Y, radial distance) were compared using t-tests of equivalence with a 2mm equivalence bound. These compared the AI position to the two orthodontists - and the orthodontists' reliability by comparing equivalence against each other. RESULTS: There was no statistical difference between the orthodontists and AudaxCeph®'s automatic tracing software except for the x- and y-dimension of Porion and the y-dimension of L1 apex. The two orthodontists had good intra-examiner reliability with no statistical difference found when comparing them. CONCLUSION: AudaxCeph®'s automated cephalometric tracing software is a good adjunctive tool to use when diagnosing and treatment planning orthodontic cases.
First Page
100691
DOI
10.1016/j.ortho.2022.100691
Recommended Citation
Ristau, Britta; Coreil, Mark; Chapple, Andrew; Armbruster, Paul; and Ballard, Richard, "Comparison of AudaxCeph®'s fully automated cephalometric tracing technology to a semi-automated approach by human examiners" (2022). LSU-LCMC Cancer Center Faculty Publications. 29.
https://digitalscholar.lsuhsc.edu/llcc_facpubs/29
10.1016/j.ortho.2022.100691