AIMC Topic: Cone-Beam Computed Tomography

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Reproducibility analysis of automated deep learning based localisation of mandibular canals on a temporal CBCT dataset.

Scientific reports Aug 29, 2023
Preoperative radiological identification of mandibular canals is essential for maxillofacial surgery. This study demonstrates the reproducibility of a deep learning system (DLS) by evaluating its localisation performance on 165 heterogeneous cone bea...
Humans Cone-Beam Computed Tomography Mandibular Canal Spiral Cone-Beam Computed Tomography Reproducibility of Results Deep Learning
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Detection of extracranial and intracranial calcified carotid artery atheromas in cone beam computed tomography using a deep learning convolutional neural network image segmentation approach.

Oral surgery, oral medicine, oral pathology and oral radiology Aug 17, 2023
OBJECTIVE: We leveraged an artificial intelligence deep-learning convolutional neural network (DL CNN) to detect calcified carotid artery atheromas (CCAAs) on cone beam computed tomography (CBCT) images.
Aged Male Carotid Artery Diseases Deep Learning Radiographic Image Interpretation, Computer-Assisted Cone-Beam Computed Tomography Plaque, Atherosclerotic Middle Aged Neural Networks, Computer Female Humans
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A hybrid method of correcting CBCT for proton range estimation with deep learning and deformable image registration.

Physics in medicine and biology Jul 31, 2023
. This study aimed to develop a novel method for generating synthetic CT (sCT) from cone-beam CT (CBCT) of the abdomen/pelvis with bowel gas pockets to facilitate estimation of proton ranges.. CBCT, the same-day repeat CT, and the planning CT (pCT) o...
Protons Spiral Cone-Beam Computed Tomography Carmustine Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Cone-Beam Computed Tomography Image Processing, Computer-Assisted Deep Learning Humans Child
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Deep learning-based segmentation of dental implants on cone-beam computed tomography images: A validation study.

Journal of dentistry Jul 28, 2023
OBJECTIVES: To train and validate a cloud-based convolutional neural network (CNN) model for automated segmentation (AS) of dental implant and attached prosthetic crown on cone-beam computed tomography (CBCT) images.
Humans Neural Networks, Computer Image Processing, Computer-Assisted Deep Learning Dental Implants Cone-Beam Computed Tomography Tooth
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Accuracy and efficiency of robotic dental implant surgery with different human-robot interactions: An in vitro study.

Journal of dentistry Jul 28, 2023
OBJECTIVES: This study aims to compare the surgical efficiency (preparation and operation time) and accuracy of implant placement between robots with different human-robot interactions.
Robotics Robotic Surgical Procedures Dental Implants Dental Implantation, Endosseous Surgery, Computer-Assisted Cone-Beam Computed Tomography Imaging, Three-Dimensional Humans Computer-Aided Design
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A deep-learning assisted bioluminescence tomography method to enable radiation targeting in rat glioblastoma.

Physics in medicine and biology Jul 24, 2023
. A novel solution is required for accurate 3D bioluminescence tomography (BLT) based glioblastoma (GBM) targeting. The provided solution should be computationally efficient to support real-time treatment planning, thus reducing the x-ray imaging dos...
Animals Rats Glioblastoma Models, Animal Deep Learning Cone-Beam Computed Tomography Tomography
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Generating missing patient anatomy from partially acquired cone-beam computed tomography images using deep learning: a proof of concept.

Physical and engineering sciences in medicine Jul 18, 2023
The patient setup technique currently in practice in most radiotherapy departments utilises on-couch cone-beam computed tomography (CBCT) imaging. Patients are positioned on the treatment couch using visual markers, followed by fine adjustments to th...
Cone-Beam Computed Tomography Neoplasms Radiotherapy Planning, Computer-Assisted Deep Learning Humans Tomography, X-Ray Computed
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Automated segmentation of the mandibular canal and its anterior loop by deep learning.

Scientific reports Jul 4, 2023
Accurate mandibular canal (MC) detection is crucial to avoid nerve injury during surgical procedures. Moreover, the anatomic complexity of the interforaminal region requires a precise delineation of anatomical variations such as the anterior loop (AL...
Mandible Cone-Beam Computed Tomography Mandibular Canal Artificial Intelligence Deep Learning
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Deep learning framework to improve the quality of cone-beam computed tomography for radiotherapy scenarios.

Medical physics Jun 22, 2023
BACKGROUND: The application of cone-beam computed tomography (CBCT) in image-guided radiotherapy and adaptive radiotherapy remains limited due to its poor image quality.
Image Processing, Computer-Assisted Deep Learning Humans Radiotherapy Planning, Computer-Assisted Cone-Beam Computed Tomography Neural Networks, Computer
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A deep learning-based automatic segmentation of zygomatic bones from cone-beam computed tomography images: A proof of concept.

Journal of dentistry Jun 13, 2023
OBJECTIVES: To investigate the efficiency and accuracy of a deep learning-based automatic segmentation method for zygomatic bones from cone-beam computed tomography (CBCT) images.
Image Processing, Computer-Assisted Deep Learning Zygoma Cone-Beam Computed Tomography Algorithms
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