AlphaDent: A dataset for automated tooth pathology detection
This provides a new dataset for dental research, enabling automated tooth pathology detection, but it is incremental as it applies existing methods to new data.
The authors introduced AlphaDent, a dataset of over 1200 DSLR images from 295 patients for tooth pathology detection, labeled for instance segmentation into 9 classes, and reported high-quality predictions from neural network experiments.
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.