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Updated: Jun 13, 2026

Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images
Published on: February 23, 2024
Novel information theory based method for superimposition of lateral head radiographs and cone beam computed
W Jacquet1, E Nyssen, P Bottenberg
1Department of Mathematics, Operational Research, Statistics and Information Systems, Vrije Universiteit Brussel, B-1050 Brussels, Belgium. wjacquet@vub.ac.be
Objectives:
The aim was to introduce a novel alignment criterion, focus mutual information (FMI), for the superimposition of lateral cephalometric radiographs and three dimensional (3D) cone beam computed images as well as the assessment of the alignment characteristics of the new method and comparison of the novel methodology with the region of interest (ROI) approach.
Methods:
Implementation of a FMI criterion-based methodology that only requires the approximate indication of stable structures in one single image. The robustness of the method was first addressed in a phantom experiment comparing the new technique with a ROI approach. Two consecutive cephalometric radiographs were then obtained, one before and one after functional twin block application. These images were then superimposed using alignment by FMI where the following were focused on, in several ways: (1) cranial base and acoustic meatus, (2) palatal plane and (3) mandibular symphysis. The superimposed images were subtracted and coloured. The applicability to cone beam CT (CBCT) is illustrated by the alignment of CBCT images acquired before and after craniofacial surgery.
Results:
The phantom experiment clearly shows superior alignment when compared to the ROI approach (Wilcoxon n = 17, Z = -3.290, and P = 0.001), and robustness with respect to the choice of parameters (one-sample t-test n = 50, t = -12.355, and P = 0.000). The treatment effects are revealed clearly in the subtraction image of well-aligned cephalometric radiographs. The colouring scheme of the subtraction image emphasises the areas of change and visualizes the remodelling of the soft tissue.
Conclusions:
FMI allows for cephalometry without tracing, it avoids the error inherent to the use of landmarks and the interaction of the practitioner is kept to a minimum. The robustness to focal distribution variations limits the influence of possible examiner inaccuracy.
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