AI Medical Compendium Journal:
Journal of computer assisted tomography

Showing 51 to 55 of 55 articles

Possibility of Deep Learning in Medical Imaging Focusing Improvement of Computed Tomography Image Quality.

Journal of computer assisted tomography Jan 1, 2020
Deep learning (DL), part of a broader family of machine learning methods, is based on learning data representations rather than task-specific algorithms. Deep learning can be used to improve the image quality of clinical scans with image noise reduct...
Humans Radiographic Image Interpretation, Computer-Assisted Quality Improvement Signal-To-Noise Ratio Tomography, X-Ray Computed Deep Learning
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Impact of Knowledge-Based Iterative Model Reconstruction on Image Quality and Hemodynamic Parameters in Dynamic Myocardial Computed Tomography Perfusion Using Low-Tube-Voltage Scan: A Feasibility Study.

Journal of computer assisted tomography Jan 1, 2019
OBJECTIVE: Knowledge-based iterative model reconstruction (IMR) yields diagnostically acceptable image quality in low-dose static computed tomography (CT). We aimed to evaluate the feasibility of IMR in dynamic myocardial computed tomography perfusio...
Humans Algorithms Aged Male Middle Aged Retrospective Studies Female Iopamidol Computed Tomography Angiography Cardiac-Gated Imaging Techniques Exercise Test Coronary Angiography Coronary Artery Disease Radiographic Image Interpretation, Computer-Assisted Hemodynamics Knowledge Bases Contrast Media Multidetector Computed Tomography Feasibility Studies
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Support Vector Machines Model of Computed Tomography for Assessing Lymph Node Metastasis in Esophageal Cancer with Neoadjuvant Chemotherapy.

Journal of computer assisted tomography Jan 1, 2017
OBJECTIVE: The aim of this study was to diagnose lymph node metastasis of esophageal cancer by support vector machines model based on computed tomography.
Lymphatic Metastasis Esophageal Neoplasms Middle Aged Image Processing, Computer-Assisted Neoadjuvant Therapy Support Vector Machine Lymph Nodes Adult Male Female Aged Retrospective Studies Tomography, X-Ray Computed Humans
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Comparison of Knowledge-based Iterative Model Reconstruction and Hybrid Reconstruction Techniques for Liver CT Evaluation of Hypervascular Hepatocellular Carcinoma.

Journal of computer assisted tomography Jan 1, 2016
OBJECTIVE: The purpose of this work was to evaluate the image quality, lesion conspicuity, and dose reduction provided by knowledge-based iterative model reconstruction (IMR) in computed tomography (CT) of the liver compared with hybrid iterative rec...
Middle Aged Liver Neoplasms Liver Humans Radiographic Image Interpretation, Computer-Assisted Machine Learning Carcinoma, Hepatocellular Sensitivity and Specificity Multidetector Computed Tomography Aged Male Neovascularization, Pathologic Republic of Korea Radiographic Image Enhancement Adult Algorithms Female Pattern Recognition, Automated Models, Biological Computer Simulation Reproducibility of Results Knowledge Bases
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Histogram-Based Discrimination of Intravenous Contrast in Abdominopelvic Computed Tomography.

Journal of computer assisted tomography Jan 1, 2016
OBJECTIVE: The aim of this study was to evaluate the accuracy of fully automated machine learning methods for detecting intravenous contrast in computed tomography (CT) studies of the abdomen and pelvis.
Radiographic Image Enhancement Reproducibility of Results Algorithms Radiography, Abdominal Humans Logistic Models Pelvis Tomography, X-Ray Computed Artificial Intelligence Administration, Intravenous Contrast Media
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