Panoramic Dental Xray Dataset

This dataset is divided into three distinct parts:

The first part includes 107 images, each with a resolution of 2964 × 1464 pixels, accompanied by annotations enabling tooth instance segmentation.

The second part contains 60 images, each with a resolution of 1024 × 512 pixels, annotated with the following classes: canine, central incisor, first molar, first premolar, lateral incisor, second molar, second premolar, and third molar.

The third part consists of 54 high-resolution panoramic radiographs, each with a resolution of 2888 × 1309 pixels.

The first two parts were acquired using the Orthoralix 9200 system (70 kV, 8 mA, and a 0.5 mm focal point). In contrast, the third part was obtained using the Dentio III digital panoramic and cephalometric imaging equipment (50-90 kV, CMOS sensor).

This dataset is used in a project aimed at leveraging deep convolutional neural networks (CNNs) to automate the segmentation and identification of teeth in panoramic dental radiographs.

When using this dataset, please cite the following two papers:

Brahmi, W., Jdey, I., & Drira, F. (2024). Exploring the role of Convolutional Neural Networks (CNN) in dental radiography segmentation: A comprehensive Systematic Literature Review. Engineering Applications of Artificial Intelligence, 133, 108510.

Brahmi, W., & Jdey, I. (2024). Automatic tooth instance segmentation and identification from panoramic X-Ray images using deep CNN. Multimedia Tools and Applications, 83(18), 55565–55585.