Dental caries in bitewing radiographs

Published: 31 October 2023| Version 1 | DOI: 10.17632/4fbdxs7s7w.1
Jan Kybic,


The dataset contains 100 images of bitewing radiographs, each image showing several human teeth. Carious lesions were annotated by rectangular bounding boxes drawn around the lesions by 8 annotators - 5 experienced and 3 less experienced dentists. Images are of size 1068x847 pixels, sometimes with black top and bottom margins, in the PNG format. Annotations are in the COCO JSON format and contain the bounding boxes created by all annotators. The data can be used for evaluating the variability between human annotators as well as to evaluate machine learning algorithms for carious lesion detection. An article "Tichý, Kunt, Nagyová, Kybic: Automatic caries detection in bitewing radiographs. Part II: Experimental comparison" using this dataset was submitted to the Clincial Oral Investigations journal.


Steps to reproduce

Gather bitewing radiographs from a hospital information system. Rescale and pad them to the same size. Use the CVAT annotation tool to draw bounding boxes, each annotator independently.


Univerzita Karlova 1 lekarska fakulta, Ceske Vysoke Uceni Technicke Fakulta elektrotechnicka


Clinical Dentistry


Všeobecná Fakultní Nemocnice v Praze

GIP-21- SL-01-232

Ministerstvo Školství, Mládeže a Tělovýchovy

CZ.02.1.01/0.0/0.0/16 019/0000765