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Model performing detection and classification of teeth in Panoramic X-rays.

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tudordascalu/2d-teeth-detection-challenge

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Scope

This project aims to build an object detection model that identifies teeth with abnormalities.

Dataset description

The dataset consists of 2D panoramic X-rays: https://zenodo.org/record/7812323#.ZDQE1uxBwUG.

Our model

We proposed a multi-step framework that consists of: detection of dental instances, filtering of healthy instances, and classification of abnormal instances.

  1. Detection of dental instances: We apply Faster-RCNN to identify all teeth in the panoramic X-ray.
  2. Filtering of healthy instances: We integrate the encoding path from a pretrained U-net for dental lesion detection into the Vgg16 architecture for binary classification of cropped teeth.
  3. Classification of abnormal instances: We use the same architecture as in 2 to classify the abnormal teeth.

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Model performing detection and classification of teeth in Panoramic X-rays.

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