AIMC Topic: Cone-Beam Computed Tomography

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Virtual and real-world implementation of deep-learning-based image denoising model on projection domain in digital tomosynthesis and cone-beam computed tomography data.

Biomedical physics & engineering express Oct 21, 2022
Reducing the radiation dose will cause severe image noise and artifacts, and degradation of image quality will also affect the accuracy of diagnosis. To find a solution, we comprise a 2D and 3D concatenating convolutional encoder-decoder (CCE-3D) and...
Computer Simulation Cone-Beam Computed Tomography Artifacts Tomography, X-Ray Computed Deep Learning
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Automatic multi-anatomical skull structure segmentation of cone-beam computed tomography scans using 3D UNETR.

PloS one Oct 12, 2022
The segmentation of medical and dental images is a fundamental step in automated clinical decision support systems. It supports the entire clinical workflow from diagnosis, therapy planning, intervention, and follow-up. In this paper, we propose a no...
Head Cone-Beam Computed Tomography Skull Image Processing, Computer-Assisted Radionuclide Imaging Artificial Intelligence
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Present status and future directions: Imaging techniques for the detection of periapical lesions.

International endodontic journal Sep 20, 2022
Diagnosing and treating apical periodontitis (AP) in an attempt to preserve the natural dentition, and to prevent the direct and indirect systemic effects of this condition, is the major goal in endodontics. Considering that AP is frequently asymptom...
Humans Artificial Intelligence Periapical Periodontitis Cone-Beam Computed Tomography Magnetic Resonance Imaging Tomography, X-Ray Computed
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The effect of a deep-learning tool on dentists' performances in detecting apical radiolucencies on periapical radiographs.

Dento maxillo facial radiology Sep 12, 2022
OBJECTIVES: To determine the efficacy of a deep-learning (DL) tool in assisting dentists in detecting apical radiolucencies on periapical radiographs.
Tooth, Nonvital Radiography Dentists Humans Deep Learning Cone-Beam Computed Tomography
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Automated analysis of three-dimensional CBCT images taken in natural head position that combines facial profile processing and multiple deep-learning models.

Computer methods and programs in biomedicine Sep 9, 2022
BACKGROUND AND OBJECTIVES: Analyzing three-dimensional cone beam computed tomography (CBCT) images has become an indispensable procedure for diagnosis and treatment planning of orthodontic patients. Artificial intelligence, especially deep-learning t...
Imaging, Three-Dimensional Image Processing, Computer-Assisted Cephalometry Spiral Cone-Beam Computed Tomography Deep Learning Cone-Beam Computed Tomography Reproducibility of Results Humans Artificial Intelligence
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Diagnosis of in vivo vertical root fracture using deep learning on cone-beam CT images.

BMC oral health Sep 5, 2022
OBJECTIVES: Evaluating the diagnostic efficiency of deep learning models to diagnose vertical root fracture in vivo on cone-beam CT (CBCT) images.
Deep Learning Cone-Beam Computed Tomography Humans Retrospective Studies Tooth Fractures Tooth Root
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Deep learning-based segmentation in prostate radiation therapy using Monte Carlo simulated cone-beam computed tomography.

Medical physics Aug 31, 2022
PURPOSE: Segmenting organs in cone-beam CT (CBCT) images would allow to adapt the radiotherapy based on the organ deformations that may occur between treatment fractions. However, this is a difficult task because of the relative lack of contrast in C...
Deep Learning Prostate Cone-Beam Computed Tomography Humans Male
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Development of artificial intelligence model for supporting implant drilling protocol decision making.

Journal of prosthodontic research Aug 25, 2022
Purpose This study aimed to develop an artificial intelligence (AI) model to support the determination of an appropriate implant drilling protocol using cone-beam computed tomography (CBCT) images.Methods Anonymized CBCT images were obtained from 60 ...
Cone-Beam Computed Tomography Decision Making Artificial Intelligence Humans
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Deep learning method for reducing metal artifacts in dental cone-beam CT using supplementary information from intra-oral scan.

Physics in medicine and biology Aug 25, 2022
Recently, dental cone-beam computed tomography (CBCT) methods have been improved to significantly reduce radiation dose while maintaining image resolution with minimal equipment cost. In low-dose CBCT environments, metallic inserts such as implants, ...
Algorithms Prostheses and Implants Artifacts Cone-Beam Computed Tomography Deep Learning Image Processing, Computer-Assisted Metals
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Deep learning-based fully automatic segmentation of the maxillary sinus on cone-beam computed tomographic images.

Scientific reports Aug 17, 2022
The detection of maxillary sinus wall is important in dental fields such as implant surgery, tooth extraction, and odontogenic disease diagnosis. The accurate segmentation of the maxillary sinus is required as a cornerstone for diagnosis and treatmen...
Cone-Beam Computed Tomography Image Processing, Computer-Assisted Maxillary Sinus Neural Networks, Computer Deep Learning
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