dental-tooth-segmentation-efficientnet-unet

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.