AI Medical Compendium Journal:
Journal of computer assisted tomography

Showing 11 to 20 of 55 articles

Prognostic Value of a Combined Nomogram Model Integrating 3-Dimensional Deep Learning and Radiomics for Head and Neck Cancer.

Journal of computer assisted tomography Feb 27, 2024
OBJECTIVE: The preoperative prediction of the overall survival (OS) status of patients with head and neck cancer (HNC) is significant value for their individualized treatment and prognosis. This study aims to evaluate the impact of adding 3D deep lea...
Female Aged Adult Radiomics Humans Prognosis Retrospective Studies Imaging, Three-Dimensional Male Nomograms Middle Aged Head and Neck Neoplasms Deep Learning Positron Emission Tomography Computed Tomography
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Estimating Body Weight From Measurements From Different Single-Slice Computed Tomography Levels: An Evaluation of Total Cross-Sectional Body Area Measurements and Deep Learning.

Journal of computer assisted tomography Feb 27, 2024
OBJECTIVE: This study aimed to evaluate the correlation between the estimated body weight obtained from 2 easy-to-perform methods and the actual body weight at different computed tomography (CT) levels and determine the best reference site for estima...
Body Weight Male Middle Aged Deep Learning Humans Retrospective Studies Tomography, X-Ray Computed Female Aged Aged, 80 and over Young Adult Adult
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Optimizing High-Resolution MR Angiography: The Synergistic Effects of 3D Wheel Sampling and Deep Learning-Based Reconstruction.

Journal of computer assisted tomography Feb 12, 2024
OBJECTIVE: The aim of this study was to assess the utility of the combined use of 3D wheel sampling and deep learning-based reconstruction (DLR) for intracranial high-resolution (HR)-time-of-flight (TOF)-magnetic resonance angiography (MRA) at 3 T.
Humans Prospective Studies Female Aged Deep Learning Adult Imaging, Three-Dimensional Male Image Processing, Computer-Assisted Middle Aged Magnetic Resonance Angiography
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Noninvasive Isocitrate Dehydrogenase 1 Status Prediction in Grade II/III Glioma Based on Magnetic Resonance Images: A Transfer Learning Strategy.

Journal of computer assisted tomography Jan 16, 2024
OBJECTIVE: The aim of this study was to evaluate transfer learning combined with various convolutional neural networks (TL-CNNs) in predicting isocitrate dehydrogenase 1 ( IDH1 ) status of grade II/III gliomas.
Isocitrate Dehydrogenase Glioma Magnetic Resonance Imaging Neoplasm Grading Adult Male Middle Aged Infant Adolescent Child, Preschool Child Machine Learning Female Infant, Newborn Young Adult Humans Neural Networks, Computer
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Visual Knowledge Domain of Artificial Intelligence in Computed Tomography: A Review Based on Bibliometric Analysis.

Journal of computer assisted tomography Jan 15, 2024
Artificial intelligence (AI)-assisted medical imaging technology is a new research area of great interest that has developed rapidly over the last decade. However, there has been no bibliometric analysis of published studies in this field. The presen...
Humans Artificial Intelligence Tomography, X-Ray Computed Bibliometrics
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Artificial Intelligence-Based Emphysema Quantification in Routine Chest Computed Tomography: Correlation With Spirometry and Visual Emphysema Grading.

Journal of computer assisted tomography Dec 18, 2023
OBJECTIVE: The aim of the study is to assess the correlation between artificial intelligence (AI)-based low attenuation volume percentage (LAV%) with forced expiratory volume in the first second to forced vital capacity (FEV1/FVC) and visual emphysem...
Adult Spirometry Male Middle Aged Retrospective Studies Humans Lung Tomography, X-Ray Computed Artificial Intelligence Severity of Illness Index Female Forced Expiratory Volume Aged Pulmonary Emphysema Radiography, Thoracic
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Multicenter Study of the Utility of Convolutional Neural Network and Transformer Models for the Detection and Segmentation of Meningiomas.

Journal of computer assisted tomography Nov 27, 2023
PURPOSE: This study aimed to investigate the effectiveness and practicality of using models like convolutional neural network and transformer in detecting and precise segmenting meningioma from magnetic resonance images.
Adult Male Middle Aged Deep Learning Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Meningioma Neural Networks, Computer Retrospective Studies Female Aged Humans Meningeal Neoplasms
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Deep Learning Image Reconstruction Algorithm for CCTA: Image Quality Assessment and Clinical Application.

Journal of computer assisted tomography Oct 11, 2023
OBJECTIVE: The increasing number of coronary computed tomography angiography (CCTA) requests raised concerns about dose exposure. New dose reduction strategies based on artificial intelligence have been proposed to overcome limitations of iterative r...
Radiation Dosage Computed Tomography Angiography Reproducibility of Results Deep Learning Image Processing, Computer-Assisted Humans Radiographic Image Interpretation, Computer-Assisted Artificial Intelligence Algorithms Prospective Studies
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The Feasibility of Deep Learning-Based Reconstruction for Low-Tube-Voltage CT Angiography for Transcatheter Aortic Valve Implantation.

Journal of computer assisted tomography Aug 11, 2023
OBJECTIVE: The purpose of this study is to evaluate the efficacy of deep learning reconstruction (DLR) on low-tube-voltage computed tomographic angiography (CTA) for transcatheter aortic valve implantation (TAVI).
Transcatheter Aortic Valve Replacement Radiographic Image Interpretation, Computer-Assisted Humans Feasibility Studies Algorithms Radiation Dosage Deep Learning Computed Tomography Angiography
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The Feasibility of Using a Deep Learning-Based Model to Determine Cardiac Computed Tomographic Contrast Dose.

Journal of computer assisted tomography Aug 3, 2023
PURPOSE: This study aimed to predict contrast effects in cardiac computed tomography (CT) from CT localizer radiographs using a deep learning (DL) model and to compare the prediction performance of the DL model with that of conventional models based ...
Iodine Contrast Media Humans Feasibility Studies Male Body Weight Retrospective Studies Middle Aged Tomography, X-Ray Computed Deep Learning Female Aged Aged, 80 and over
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