Dental caries detection: Datasets & Models

Manually reviewing radiographs for early-stage caries is time-consuming, and subtle interproximal lesions are easy to miss under time pressure or across high patient volumes. Automating caries detection with computer vision gives clinicians a consistent second read that flags suspicious regions before they are overlooked, reducing variability between reviewers. In a healthcare imaging setting, this means faster triage of scans and documented, reproducible findings that support the diagnostic workflow rather than replacing the dentist's judgment.

An automated detection pipeline can screen every image the same way, surface hard-to-see lesions, and produce annotated outputs that slot into existing dental practice management and PACS systems. Because it works on the images your sensors and X-ray equipment already produce, it integrates without new hardware and scales from a single clinic to a multi-site network. Recommended model RF-DETR delivers strong localization accuracy on dense dental imagery while remaining practical to deploy.

1. Upload an image: Drop any photo into the widget above to try dental caries detection for free, right on this page.
2. Preview instant results: The model detects caries lesion, tooth, dental filling, cavity, bitewing radiograph within seconds and returns an annotated image with structured predictions, so you can immediately see how well it works. Adjust the detection classes and re-run until the results fit your scenario.
3. Like what you see?: With a free Roboflow account, you can deploy this workflow with the Serverless Cloud API, customize it in your workspace, or train RF-DETR on your own images for production accuracy.
4. Get started for free: No code or training data required to begin: upload, review the results, and make it part of your stack in a single click.