Objectives To evaluate a fully deep learning mask region-based convolutional neural
network (R-CNN) method for automated tooth segmentation using individual annotation of …

This paper presents a system for assisting in human identification using dental radiographs.
The goal of the system is to archive antemortem (AM) dental images and enable content …

We propose a dental classification and numbering system to effectively segment, classify,
and number teeth in dental bitewing radiographs. An image enhancement method that …

Chairside manufacturing based on digital image acquisition is gainingincreasing importance
in dentistry. For the standardized application of these methods, it is paramount to have …

Dental caries is one of the most chronic diseases involving the majority of the population
during their lifetime. Caries lesions are typically diagnosed by general dentists relying only …

We present an algorithm to classify and assign numbers to teeth in bitewing dental images.
The goal is to use the result of this algorithm in an automated dental identification system …

Dental caries is one of the most chronic diseases involving the majority of the population
during their lifetime. Caries lesions are typically diagnosed by radiologists relying only on …

Dental biometrics deal with human identification from dental characteristics. In this paper, we
present a new technique for identifying people based upon shapes and appearances of …

Objectives Improved tools based on deep learning can be used to accurately number and
identify teeth. This study aims to review the use of deep learning in tooth numbering and …

This paper presents an enhanced dental identification method based on both the contours of
teeth and dental works. To reduce the alignment error caused from unreliable contours, we …