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AlphaDent: A dataset for automated tooth pathology detection
E.I. Sosnin 1, Y.L. Vasil’ev 1, R.A. Solovyev 2, A.L. Stempkovskiy 2, D.V. Telpukhov 2, A.A. Vasil’ev 2, A.A. Amerikanov 3, A.Y. Romanov 3

1 Sechenov University,
Bolshaya Pirogovskaya Ulitsa, 2, Building 4, Moscow, 119991, Russia;
2 AlphaChip LLC,
Zelenograd building 438A, Moscow, 124498, Russia;
3 HSE University,
20 Myasnitskaya Ulitsa, Moscow, 101000, Russia

  PDF, 2297 kB

DOI: 10.18287/COJ1802

Страницы: 1129-1137.

Язык статьи: English.

Аннотация:
In this article, we present a new unique dataset for dental research – AlphaDent. This dataset is based on the DSLR camera photographs of the teeth of 295 patients and contains over 1200 images. The dataset is labeled for solving the instance segmentation problem and is divided into 9 classes. The article provides a detailed description of the dataset and the labeling format. The article also provides the details of the experiment on neural network training for the Instance Segmentation problem using this dataset. The results obtained show high quality of predictions. The dataset is published under an open license; and the training/inference code and model weights are also available under open licenses.

Ключевые слова:
tooth segmentation, dataset for dental research, artificial intelligence, instance segmentation.

Citation:
Sosnin EI, Vasil’ev YL, Solovyev RA, Stempkovskiy AL, Telpukhov DV, Vasil’ev AA, Amerikanov AA, Romanov AY. AlphaDent: A dataset for automated tooth pathology detection. Computer Optics 2025; 49(6): 1129-1137. DOI: 10.18287/COJ1802.

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