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

The OrthoAid

A DICOM Implementation for Orthodontic Images

Image comparison for orthodontists

CEPHA29 Automatic Cephalometric Landmark Detection Challenge

Extraction decision in orthodontic treatments using machine learning

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.

Code to reproduce all the experiments in the paper "CHaRM: Conditioned Heatmap Regression Methodology for Accurate and Fast Dental Landmark Localization"

AI-assisted orthodontic treatment planning pipeline for clear aligners with dual-agent deep learning and 4D staging simulation.

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.

A suite of applications for tracking orthodontic device wear time.

Official code for "Tracing Like a Clinician" (arXiv:2605.03358). Anatomy-guided spatial priors for cephalometric landmark detection. 1.04mm MRE on 25 landmarks.

software for the operation of an orthodontic office

OrthoRL — first RL environment for orthodontic aligner staging. 24-step SE(3) planning, 5 algorithmic rewards, 1,063 real Tsinghua patients. OpenEnv Hackathon India 2026.

Open, safety-boundary-first clear-aligner treatment-planning research toolkit.