dental-panoramic-detector

Dental Panoramic X-Ray Detector

YOLO11-N model trained to detect dental pathologies on panoramic radiographs.

Classes

Performance

Trained on 9,928 panoramic X-rays, validated on DENTEX val set (46 images, 182 boxes).

Training converged at epoch 27/57 (early stopping, patience=30).

Training Data

liodon-ai/dental-panoramic-xray-yolo — combined DENTEX + OralXrays-9 (CVPR 2025), 9,928 train images, 39,715 annotated boxes.

Files

Recommended Inference Settings

At conf=0.25 the model over-fires on caries (adjacent teeth flagged together). At conf=0.45 output is clean and clinically readable.

Usage

from ultralytics import YOLO

model = YOLO("best.pt")
results = model("panoramic.jpg", imgsz=640, conf=0.45, iou=0.35)
results[0].show()

Or with ONNX:

import onnxruntime as ort
sess = ort.InferenceSession("best.onnx")

Per-Class Notes

impacted_tooth — highest quality class. Consistently detects impacted wisdom teeth with tight boxes and 0.66–0.84 confidence. Closest to clinical-grade.

periapical_lesion — fires correctly when present, but limited by small val set. Treat as a flag to look closer, not a diagnosis.

caries — directionally correct (right quadrant, right teeth) but recall is limited at panoramic resolution. Use as a screening hint, not a count.

Citation

@model{liodonai2026dentalpanoramic,
  title={Dental Panoramic X-Ray Detector},
  author={Liodon AI},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/liodon-ai/dental-panoramic-detector}
}