dental-radiography

This repository contains code and resources for developing and implementing computer vision and machine learning models for dental radiography analysis, including techniques for anomaly detection and image segmentation.

Object detection for tooth decay (dental caries) using YOLOv5s and Detectron2 Faster R-CNN. Trained on a custom dental radiograph dataset with three classes: Healthy Tooth, Decayed Tooth, and Cavity. Includes training notebooks, model weights, and reproducible inference pipelines.

Supervised machine learning on dental X‑ray images: regression and classification models with cross‑validation and evaluation (Jupyter notebooks).