Revolutionizing Cephalometric Analysis: Enhancing Accuracy with CNN-Based Algorithm for Malocclusion Patients

Posted: December 28, 2024
The article discusses the accuracy of estimating cephalometric landmarks and conducting cephalometric analysis from lateral facial photographs using a CNN-based algorithm. The study evaluated the algorithm's performance on patients with skeletal Class II and III malocclusion, achieving a high level of accuracy with errors less than 0.5 mm. The algorithm showed superior accuracy compared to previous methods using normal occlusion data. The findings suggest a practical approach to automating cephalometric analysis without relying on traditional X-ray cephalograms.
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