AIMC Topic: Tooth

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A relation-based framework for effective teeth recognition on dental periapical X-rays.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Dec 2, 2021
Dental periapical X-rays are used as a popular tool by dentists for diagnosis. To provide dentists with diagnostic support, in this paper, we achieve automated teeth recognition of dental periapical X-rays by using deep learning techniques, including...
X-Rays Radiography Tooth Neural Networks, Computer
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Toward Clinically Applicable 3-Dimensional Tooth Segmentation via Deep Learning.

Journal of dental research Nov 1, 2021
Digital dentistry plays a pivotal role in dental health care. A critical step in many digital dental systems is to accurately delineate individual teeth and the gingiva in the 3-dimension intraoral scanned mesh data. However, previous state-of-the-ar...
Humans Malocclusion Tooth Deep Learning
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Automated chart filing on panoramic radiographs using deep learning.

Journal of dentistry Oct 29, 2021
OBJECTIVE: The aim of this study is to automatically detect, segment and label teeth, crowns, fillings, root canal fillings, implants and root remnants on panoramic radiographs (PR(s)).
Filing Deep Learning Algorithms Tooth Radiography, Panoramic
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A novel deep learning system for multi-class tooth segmentation and classification on cone beam computed tomography. A validation study.

Journal of dentistry Oct 26, 2021
OBJECTIVES: Automatic tooth segmentation and classification from cone beam computed tomography (CBCT) have become an integral component of the digital dental workflows. Therefore, the aim of this study was to develop and validate a deep learning appr...
Cone-Beam Computed Tomography Tooth Image Processing, Computer-Assisted Artificial Intelligence Deep Learning
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Detection of Dental Apical Lesions Using CNNs on Periapical Radiograph.

Sensors (Basel, Switzerland) Oct 24, 2021
Apical lesions, the general term for chronic infectious diseases, are very common dental diseases in modern life, and are caused by various factors. The current prevailing endodontic treatment makes use of X-ray photography taken from patients where ...
Humans Radiography Neural Networks, Computer Tooth
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Deep learning for automated detection and numbering of permanent teeth on panoramic images.

Dento maxillo facial radiology Oct 13, 2021
OBJECTIVE: This study aimed to evaluate an automated detection system to detect and classify permanent teeth on orthopantomogram (OPG) images using convolutional neural networks (CNNs).
Neural Networks, Computer Deep Learning Humans Tooth Radiography, Panoramic Radiography
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Performance of a convolutional neural network algorithm for tooth detection and numbering on periapical radiographs.

Dento maxillo facial radiology Oct 8, 2021
OBJECTIVES: The present study aimed to evaluate the performance of a Faster Region-based Convolutional Neural Network (R-CNN) algorithm for tooth detection and numbering on periapical images.
Humans Retrospective Studies Tooth Artificial Intelligence Neural Networks, Computer Algorithms
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Deep Learning-Based Three-Dimensional Oral Conical Beam Computed Tomography for Diagnosis.

Journal of healthcare engineering Sep 21, 2021
In order to deeply study oral three-dimensional cone beam computed tomography (CBCT), the diagnosis of oral and facial surgical diseases based on deep learning was studied. The utility model related to a deep learning-based classification algorithm f...
Cone-Beam Computed Tomography Algorithms Tooth Humans Image Processing, Computer-Assisted Deep Learning Imaging, Three-Dimensional
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Micro-Computed Tomography-Guided Artificial Intelligence for Pulp Cavity and Tooth Segmentation on Cone-beam Computed Tomography.

Journal of endodontics Sep 11, 2021
INTRODUCTION: This study proposes a novel data pipeline based on micro-computed tomographic (micro-CT) data for training the U-Net network to realize the automatic and accurate segmentation of the pulp cavity and tooth on cone-beam computed tomograph...
X-Ray Microtomography Tooth Cone-Beam Computed Tomography Image Processing, Computer-Assisted Dental Pulp Cavity Artificial Intelligence
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Tooth and Bone Parameters in the Assessment of the Chronological Age of Children and Adolescents Using Neural Modelling Methods.

Sensors (Basel, Switzerland) Sep 8, 2021
The analog methods used in the clinical assessment of the patient's chronological age are subjective and characterized by low accuracy. When using those methods, there is a noticeable discrepancy between the chronological age and the age estimated ba...
Humans Artificial Intelligence Tooth Child Adolescent
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