AIMC Topic: Mandibular Condyle
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Deep learning classification performance for diagnosing condylar osteoarthritis in patients with dentofacial deformities using panoramic temporomandibular joint projection images.
Oral radiology
Jul 11, 2024
OBJECTIVE: The present study aimed to assess the consistencies and performances of deep learning (DL) models in the diagnosis of condylar osteoarthritis (OA) among patients with dentofacial deformities using panoramic temporomandibular joint (TMJ) pr...
Deep learning for automated segmentation of the temporomandibular joint.
Journal of dentistry
Mar 2, 2023
OBJECTIVE: Quantitative analysis of the volume and shape of the temporomandibular joint (TMJ) using cone-beam computed tomography (CBCT) requires accurate segmentation of the mandibular condyles and the glenoid fossae. This study aimed to develop and...
Fully automated condyle segmentation using 3D convolutional neural networks.
Scientific reports
Nov 29, 2022
The aim of this study was to develop an auto-segmentation algorithm for mandibular condyle using the 3D U-Net and perform a stress test to determine the optimal dataset size for achieving clinically acceptable accuracy. 234 cone-beam computed tomogra...
Classifying Temporomandibular Disorder with Artificial Intelligent Architecture Using Magnetic Resonance Imaging.
Annals of biomedical engineering
Aug 29, 2022
This study proposes a new diagnostic tool for automatically extracting discriminative features and detecting temporomandibular joint disc displacement (TMJDD) accurately with artificial intelligence. We analyzed the structural magnetic resonance imag...
An Artificial Intelligence-Based Cosmesis Evaluation for Temporomandibular Joint Reconstruction.
The Laryngoscope
Jun 3, 2022
OBJECTIVE: Management of the temporomandibular joint (TMJ) following condylar resection remains challenging in the field of mandibular reconstruction. A simple reconstruction of the TMJ with a contoured end of a fibular graft placed into the joint sp...
Automatic segmentation of the temporomandibular joint disc on magnetic resonance images using a deep learning technique.
Dento maxillo facial radiology
Aug 4, 2021
OBJECTIVES: The aims of the present study were to construct a deep learning model for automatic segmentation of the temporomandibular joint (TMJ) disc on magnetic resonance (MR) images, and to evaluate the performances using the internal and external...
Automated cortical thickness measurement of the mandibular condyle head on CBCT images using a deep learning method.
Scientific reports
Jul 21, 2021
This study proposes a deep learning model for cortical bone segmentation in the mandibular condyle head using cone-beam computed tomography (CBCT) and an automated method for measuring cortical thickness with a color display based on the segmentation...
Performance of deep learning models constructed using panoramic radiographs from two hospitals to diagnose fractures of the mandibular condyle.
Dento maxillo facial radiology
Mar 26, 2021
OBJECTIVE: The present study aimed to verify the classification performance of deep learning (DL) models for diagnosing fractures of the mandibular condyle on panoramic radiographs using data sets from two hospitals and to compare their internal and ...
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