Comparison between a human judge and automatic landmark identification on digital models

Accurate landmark identification is a prerequisite for accurate and reliable biomedical image analysis. Orthodontic study models are valuable tools for diagnosis, treatment planning, and maintaining complete records. The purpose of this study was to evaluate the reliability and validity of a software program (Align Technology, Inc) as a tool for automatic landmark location.

Using digital intraoral scans of 10 dental arches, 4 calibrated human judges independently located cusp tips and interproximal contacts. The same landmarks were automatically identified by the software. Intraclass correlation coefficient (Cronbach α), absolute mean errors, and regression analysis were calculated. In addition, Bland-Altman 95% confidence limits were also applied to the data to graphically display agreement on landmark identification between the human judges and the software.

The intraclass correlation coefficient between the software and the human judges' average for the x-, y-, and z-coordinates for all landmarks was excellent, at 1.0, 1.0, and 0.98, respectively. The regression analysis and Bland-Altman plots show no systematic errors for agreement on landmark identification between the human judges and the software.

Landmark location was nearly identical between the software and the human judges, making the methods interchangeable.