Saved in:
Bibliographic Details
Main Authors: Sosnin, Evgeniy I., Vasilev, Yuriy L., Solovyev, Roman A., Stempkovskiy, Aleksandr L., Telpukhov, Dmitry V., Vasilev, Artem A., Amerikanov, Aleksandr A., Romanov, Aleksandr Y.
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2507.22512
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866908933969412096
author Sosnin, Evgeniy I.
Vasilev, Yuriy L.
Solovyev, Roman A.
Stempkovskiy, Aleksandr L.
Telpukhov, Dmitry V.
Vasilev, Artem A.
Amerikanov, Aleksandr A.
Romanov, Aleksandr Y.
author_facet Sosnin, Evgeniy I.
Vasilev, Yuriy L.
Solovyev, Roman A.
Stempkovskiy, Aleksandr L.
Telpukhov, Dmitry V.
Vasilev, Artem A.
Amerikanov, Aleksandr A.
Romanov, Aleksandr Y.
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2507_22512
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle AlphaDent: A dataset for automated tooth pathology detection
Sosnin, Evgeniy I.
Vasilev, Yuriy L.
Solovyev, Roman A.
Stempkovskiy, Aleksandr L.
Telpukhov, Dmitry V.
Vasilev, Artem A.
Amerikanov, Aleksandr A.
Romanov, Aleksandr Y.
Computer Vision and Pattern Recognition
Machine Learning
Image and Video Processing
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.
title AlphaDent: A dataset for automated tooth pathology detection
topic Computer Vision and Pattern Recognition
Machine Learning
Image and Video Processing
url https://arxiv.org/abs/2507.22512