DanialSoleimany/YOLOv12-Tooth-Cavity-Detection

A deep learning project for detecting and classifying teeth as normal or cavity using YOLOv12m. The model is integrated into a web application for real-time dental screening. Designed to enhance early diagnosis accessibility, with future improvements planned for dataset expansion, annotation quality, and robustness to real-world conditions.

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Emerging

This web application helps dental professionals quickly screen dental images for cavities. You upload an X-ray or dental photograph, and the system identifies and highlights potential cavities in red and healthy teeth in green, along with confidence scores. It's designed for dentists, dental hygienists, or dental assistants seeking an accessible tool for early diagnostic support.

No commits in the last 6 months.

Use this if you need a rapid, visual assessment of dental images for cavity detection without installing complex software or saving files.

Not ideal if you require a certified medical diagnostic tool or need to process a very high volume of images for research purposes.

dental-screening cavity-detection oral-health dental-imaging diagnostic-support
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 4 / 25
Maturity 15 / 25
Community 13 / 25

How are scores calculated?

Stars

8

Forks

2

Language

Jupyter Notebook

License

MIT

Last pushed

Aug 15, 2025

Commits (30d)

0

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