brunosalme/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}
}