AIMC Topic: Cone-Beam Computed Tomography

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Detection of vertical root fractures by cone-beam computed tomography based on deep learning.

Dento maxillo facial radiology Feb 1, 2023
OBJECTIVES: This study aims to evaluate the performance of ResNet models in the detection of and vertical root fractures (VRF) in Cone-beam Computed Tomography (CBCT) images.
ROC Curve Cone-Beam Computed Tomography Tooth Fractures Humans Deep Learning Tooth Root
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Learning Needle Placement in Soft Tissue With Robot-assisted Navigation.

In vivo (Athens, Greece) Jan 1, 2023
BACKGROUND/AIM: The aim of this phantom study was to evaluate the learning curves of novices practicing how to place a cone-beam computed tomography (CBCT)-guided needle using a novel robotic assistance system (RAS).
Cone-Beam Computed Tomography Humans Robotics Punctures
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[Automatic Delineation of Clinical Target Volume and Organ at Risk by Deep Learning for Prostate Cancer Adaptive Radiotherapy].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation Nov 30, 2022
Adaptive radiotherapy can modify the treatment plan online based on the clinical target volume (CTV) and organ at risk (OAR) contours on the cone-beam CT (CBCT) before treatment, improving the accuracy of radiotherapy. However, manual delineation of ...
Humans Neural Networks, Computer Male Radiotherapy Planning, Computer-Assisted Image Processing, Computer-Assisted Prostatic Neoplasms Deep Learning Cone-Beam Computed Tomography
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Performance of artificial intelligence using oral and maxillofacial CBCT images: A systematic review and meta-analysis.

Nigerian journal of clinical practice Nov 1, 2022
BACKGROUND: Artificial intelligence (AI) has the potential to enhance health care efficiency and diagnostic accuracy.
Humans Cone-Beam Computed Tomography Spiral Cone-Beam Computed Tomography Artificial Intelligence
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Deep Learning-Based Internal Target Volume (ITV) Prediction Using Cone-Beam CT Images in Lung Stereotactic Body Radiotherapy.

Technology in cancer research & treatment Jan 1, 2022
This study aims to develop a deep learning (DL)-based (Mask R-CNN) method to predict the internal target volume (ITV) in cone beam computed tomography (CBCT) images for lung stereotactic body radiotherapy (SBRT) patients and to evaluate the predictio...
Lung Neoplasms Radiotherapy Planning, Computer-Assisted Respiration Deep Learning Cone-Beam Computed Tomography Radiosurgery Four-Dimensional Computed Tomography Humans Lung
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Automatic Segmentation of Mandibular Ramus and Condyles.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
In order to diagnose TMJ pathologies, we developed and tested a novel algorithm, MandSeg, that combines image processing and machine learning approaches for automatically segmenting the mandibular condyles and ramus. A deep neural network based on th...
Cone-Beam Computed Tomography Mandible Image Processing, Computer-Assisted Neural Networks, Computer Machine Learning
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Fully automatic segmentation of sinonasal cavity and pharyngeal airway based on convolutional neural networks.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics Jun 1, 2021
INTRODUCTION: This study aimed to test the accuracy of a new automatic deep learning-based approach on the basis of convolutional neural networks (CNN) for fully automatic segmentation of the sinonasal cavity and the pharyngeal airway from cone-beam ...
Cone-Beam Computed Tomography Female Pharynx Reproducibility of Results Adult Humans Male Young Adult Neural Networks, Computer Artificial Intelligence
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Model Experimental Study of Man-Machine Interactive Robot-Assisted Craniotomy.

The Journal of craniofacial surgery May 1, 2021
To evaluate the feasibility, safety, and accuracy of the new man-machine interactive robotic system in model experiment. The implantation of the 8 to 10 bone screws over the skull model obtained from real patient's digital imaging and communications ...
Humans Reproducibility of Results Imaging, Three-Dimensional Cone-Beam Computed Tomography Skull Robotics Craniotomy
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Cone Beam CT (CBCT) Based Synthetic CT Generation Using Deep Learning Methods for Dose Calculation of Nasopharyngeal Carcinoma Radiotherapy.

Technology in cancer research & treatment Jan 1, 2021
To generate synthetic CT (sCT) images with high quality from CBCT and planning CT (pCT) for dose calculation by using deep learning methods. 169 NPC patients with a total of 20926 slices of CBCT and pCT images were included. In this study the Cycle...
Image Processing, Computer-Assisted Neoplasm Staging Adolescent Cone-Beam Computed Tomography Radiotherapy Dosage Nasopharyngeal Carcinoma Radiotherapy, Image-Guided Neoplasm Grading Radiotherapy Planning, Computer-Assisted Young Adult Adult Middle Aged Deep Learning Humans Female Male Algorithms Aged
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[Automated system of the determination of maxillary sinus morphometric parameters].

Vestnik otorinolaringologii Jan 1, 2021
THE AIM OF THE STUDY: Was to compare manual, semi-automatic and automatic methods for determining the maxillary sinus volume using cone beam computed tomography (CBCT).
Cone-Beam Computed Tomography Humans Maxillary Sinus Artificial Intelligence
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