AIMC Topic: Mandible

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An AI-assisted explainable mTMCNN architecture for detection of mandibular third molar presence from panoramic radiography.

International journal of medical informatics Nov 23, 2024
OBJECTIVE: This study aimed to design and systematically evaluate an architecture, proposed as the Explainable Mandibular Third Molar Convolutional Neural Network (E-mTMCNN), for detecting the presence of mandibular third molars (m-M3) in panoramic r...
Neural Networks, Computer Deep Learning Mandible Molar, Third Radiography, Panoramic Humans
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Comparison Between Conventional and Artificial Intelligence-Assisted Setup for Digital Implant Planning: Accuracy, Time-Efficiency, and User Experience.

Clinical oral implants research Nov 21, 2024
OBJECTIVES: To investigate the reliability and time efficiency of the conventional compared to the automatic artificial intelligence (AI) segmentation of the mandibular canal and registration of the CBCT with the model scan data, in relation to clini...
Artificial Intelligence Reproducibility of Results Time Factors Mandible Cone-Beam Computed Tomography Patient Care Planning Humans Dental Implantation, Endosseous
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AI-driven segmentation of the pulp cavity system in mandibular molars on CBCT images using convolutional neural networks.

Clinical oral investigations Nov 21, 2024
OBJECTIVE: To develop and validate an artificial intelligence (AI)-driven tool for automated segmentation of the pulp cavity system of mandibular molars on cone-beam computed tomography (CBCT) images.
Dental Pulp Cavity Cone-Beam Computed Tomography Imaging, Three-Dimensional Humans Mandible Neural Networks, Computer Molar Artificial Intelligence
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Automatic detection and proximity quantification of inferior alveolar nerve and mandibular third molar on cone-beam computed tomography.

Clinical oral investigations Nov 20, 2024
OBJECTIVES: During mandibular third molar (MTM) extraction surgery, preoperative analysis to quantify the proximity of the MTM to the surrounding inferior alveolar nerve (IAN) is essential to minimize the risk of IAN injury. This study aims to propos...
Humans Cone-Beam Computed Tomography Algorithms Mandible Mandibular Nerve Tooth Extraction Female Mandibular Nerve Injuries Middle Aged Adult Male Deep Learning Molar, Third
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Detection of C-shaped mandibular second molars on panoramic radiographs using deep convolutional neural networks.

Clinical oral investigations Nov 18, 2024
OBJECTIVES: The C-shaped mandibular second molars (MSMs) may pose an endodontic challenge. The aim of this study was to develop a convolutional neural network (CNN)-based deep learning system for the diagnosis of C-shaped MSMs on panoramic radiograph...
Cone-Beam Computed Tomography Mandible Radiography, Panoramic Molar Middle Aged Deep Learning China Female Adult Male Humans Neural Networks, Computer
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Sex prediction through machine learning utilizing mandibular condyles, coronoid processes, and sigmoid notches features.

PloS one Nov 15, 2024
Characteristics of the mandible structures have been relevant in anthropological and forensic studies for sex prediction. This study aims to evaluate the coronoid process, condyle, and sigmoid notch patterns in sex prediction through supervised machi...
Sex Determination by Skeleton Mandibular Condyle Male Female Humans ROC Curve Support Vector Machine Machine Learning Cephalometry Young Adult Algorithms Middle Aged Mandible Adult Adolescent
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A new approach for sex prediction by evaluating mandibular arch and canine dimensions with machine-learning classifiers and intraoral scanners (a retrospective study).

Scientific reports Nov 14, 2024
In circumstances where antemortem information concerning the deceased individual is unavailable, forensic experts prepare biological profiling for unidentified human remains that aids in narrowing the search for identity. Biological profiling include...
Male Middle Aged Adolescent Female Young Adult Adult Sex Characteristics Cuspid ROC Curve Imaging, Three-Dimensional Mandible Machine Learning Retrospective Studies Humans
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A two-stage deep-learning model for determination of the contact of mandibular third molars with the mandibular canal on panoramic radiographs.

BMC oral health Nov 13, 2024
OBJECTIVES: This study aimed to assess the accuracy of a two-stage deep learning (DL) model for (1) detecting mandibular third molars (MTMs) and the mandibular canal (MC), and (2) classifying the anatomical relationship between these structures (cont...
Humans Female Radiography, Panoramic Mandibular Nerve Adult Male Molar, Third Deep Learning Cone-Beam Computed Tomography Mandible
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Automated dentition segmentation: 3D UNet-based approach with MIScnn framework.

Journal of the World federation of orthodontists Nov 2, 2024
INTRODUCTION: Advancements in technology have led to the adoption of digital workflows in dentistry, which require the segmentation of regions of interest from cone-beam computed tomography (CBCT) scans. These segmentations assist in diagnosis, treat...
Maxilla Image Processing, Computer-Assisted Dentition Tooth Humans Imaging, Three-Dimensional Mandible Neural Networks, Computer Cone-Beam Computed Tomography
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Application of 3D neural networks and explainable AI to classify ICDAS detection system on mandibular molars.

The Journal of prosthetic dentistry Oct 22, 2024
STATEMENT OF PROBLEM: Considerable variations exist in cavity preparation methods and approaches. Whether the extent and depth of cavity preparation because of the extent of caries affects the overall accuracy of training deep learning models remains...
Humans Neural Networks, Computer Mandible Computer-Aided Design Molar Deep Learning Dental Caries Dental Cavity Preparation Imaging, Three-Dimensional
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