Dental Tooth Segmentation EfficientNet U-Net
This repository contains the trained Keras model for the course assignment "Development of a Dental Tooth Segmentation System Using U-Net and Flask".
The checkpoint is an EfficientNetB0 encoder U-Net trained and fine-tuned on dental panoramic X-ray segmentation data. It predicts a binary tooth-region mask from a panoramic dental radiograph.
Model File
best_model.keras
Inference Recipe
- Resize image to 256x512.
- Convert grayscale radiograph to three channels for the EfficientNet encoder.
- Predict with horizontal-flip test-time augmentation.
- Use threshold 0.65 for the final combined test result.
- Remove connected components smaller than 32 pixels.
Metrics
Final combined held-out test result:
- Precision: 89.54%
- Recall: 91.93%
- F1/Dice: 90.72%
- IoU: 83.02%
- Pixel accuracy: 96.99%
HITL held-out split:
- Precision: 89.45%
- Recall: 91.41%
- F1/Dice: 90.42%
- IoU: 82.51%
This model is for education and demonstration only. It is not a medical device and must not be used for clinical diagnosis.