A 3D Slicer extension to use AMASSS, ALI-CBCT and ALI-IOS
DilatedToothSegNet: Tooth Segmentation Network on 3D Dental Meshes Through Increasing Receptive Vision
A web app for tracing and analyzing cephalograms and photographs used in the planning of orthodontic treatment.
Automatic landmark identification in CBCT scans
A Benchmark Dataset for Automatic Cephalometric Landmark Detection and CVM Stage Classification
A DICOM Implementation for Orthodontic Images
CEPHA29 Automatic Cephalometric Landmark Detection Challenge
Extraction decision in orthodontic treatments using machine learning
Full CV pipeline for orthodontic skeletal age & gender prediction on 1,294 clinical X-rays. Attention U-Net segmentation · SHAP · XGBoost · Flask REST API + React frontend. Best Project EXPRO 2025-26.
MORDENT.AI is an automated platform for cephalometric landmark detection and orthodontic analysis that leverages deep learning and graph neural networks. It integrates smoothly with clinical workflows through a DICOM viewer and medical image management system, enabling efficient and accurate orthodontic diagnosis and treatment planning.
AI-assisted orthodontic treatment planning pipeline for clear aligners with dual-agent deep learning and 4D staging simulation.
Code to reproduce all the experiments in the paper "CHaRM: Conditioned Heatmap Regression Methodology for Accurate and Fast Dental Landmark Localization"
A suite of applications for tracking orthodontic device wear time.
software for the operation of an orthodontic office
🦷 Develop a biomechanical dental extraction device to enhance efficiency and precision in dental procedures, leveraging advanced engineering techniques.
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