AI Medical Compendium Journal:
Journal of computer assisted tomography

Showing 41 to 50 of 55 articles

Assessment of Image Quality of Coronary Computed Tomography Angiography in Obese Patients by Comparing Deep Learning Image Reconstruction With Adaptive Statistical Iterative Reconstruction Veo.

Journal of computer assisted tomography May 13, 2025
OBJECTIVE: The aim of the study was to evaluate the image quality of coronary computed tomography (CT) angiography (CCTA) in obese patients by using deep learning image reconstruction (DLIR) in comparison with adaptive statistical iterative reconstru...
Female Humans Aged Prospective Studies Adult Male Middle Aged Deep Learning Obesity Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Vessels Radiation Dosage Computed Tomography Angiography
View on PubMed DOI

In Vitro Study of the Precision and Accuracy of Measurement of the Vascular Inner Diameter on Computed Tomography Angiography Using Deep Learning Image Reconstruction: Comparison With Filtered Back Projection and Iterative Reconstruction.

Journal of computer assisted tomography May 13, 2025
OBJECTIVE: This study aimed to compare the performance of deep learning image reconstruction (DLIR) with that of standard filtered back projection (FBP) and adaptive statistical iterative reconstruction V (ASiR-V) for measurement of the vascular diam...
Computed Tomography Angiography Models, Cardiovascular Algorithms Deep Learning Radiographic Image Interpretation, Computer-Assisted Phantoms, Imaging
View on PubMed DOI

Artificial Intelligence in Diagnostic Radiology: Where Do We Stand, Challenges, and Opportunities.

Journal of computer assisted tomography May 13, 2025
Artificial intelligence (AI) is the most revolutionizing development in the health care industry in the current decade, with diagnostic imaging having the greatest share in such development. Machine learning and deep learning (DL) are subclasses of A...
Humans Neural Networks, Computer Neoplasms Radiographic Image Interpretation, Computer-Assisted Workflow Quality Control Artificial Intelligence Machine Learning Algorithms Tomography, X-Ray Computed
View on PubMed DOI

AI-Based Quantitative CT Analysis of Temporal Changes According to Disease Severity in COVID-19 Pneumonia.

Journal of computer assisted tomography May 13, 2025
OBJECTIVE: To quantitatively evaluate computed tomography (CT) parameters of coronavirus disease 2019 (COVID-19) pneumonia an artificial intelligence (AI)-based software in different clinical severity groups during the disease course.
Middle Aged Lung Severity of Illness Index Adolescent Young Adult Adult Sensitivity and Specificity Male Evaluation Studies as Topic Radiographic Image Interpretation, Computer-Assisted Time COVID-19 Retrospective Studies Tomography, X-Ray Computed Female Reproducibility of Results SARS-CoV-2 Aged Aged, 80 and over Humans Artificial Intelligence
View on PubMed DOI

Evaluating a Convolutional Neural Network Noise Reduction Method When Applied to CT Images Reconstructed Differently Than Training Data.

Journal of computer assisted tomography May 13, 2025
OBJECTIVE: The aim of this study was to evaluate a narrowly trained convolutional neural network (CNN) denoising algorithm when applied to images reconstructed differently than training data set.
Signal-To-Noise Ratio Algorithms Tomography, X-Ray Computed Humans Deep Learning Neural Networks, Computer Image Processing, Computer-Assisted
View on PubMed DOI

Machine Learning and Deep Learning in Oncologic Imaging: Potential Hurdles, Opportunities for Improvement, and Solutions-Abdominal Imagers' Perspective.

Journal of computer assisted tomography May 13, 2025
The applications of machine learning in clinical radiology practice and in particular oncologic imaging practice are steadily evolving. However, there are several potential hurdles for widespread implementation of machine learning in oncologic imagin...
Machine Learning Abdomen Diagnostic Imaging Image Interpretation, Computer-Assisted Humans Abdominal Neoplasms
View on PubMed DOI

Radiomics-Based Machine Learning Classification for Glioma Grading Using Diffusion- and Perfusion-Weighted Magnetic Resonance Imaging.

Journal of computer assisted tomography May 13, 2025
OBJECTIVE: The aim of this study was to evaluate various radiomics-based machine learning classification models using the apparent diffusion coefficient (ADC) and cerebral blood flow (CBF) maps for differentiating between low-grade gliomas (LGGs) and...
Humans Machine Learning Brain Retrospective Studies Female Adult Image Interpretation, Computer-Assisted Brain Neoplasms Male Magnetic Resonance Angiography Middle Aged Diffusion Magnetic Resonance Imaging Glioma Neoplasm Grading
View on PubMed DOI

Initial Experience With Low-Dose 18F-Fluorodeoxyglucose Positron Emission Tomography/Magnetic Resonance Imaging With Deep Learning Enhancement.

Journal of computer assisted tomography May 13, 2025
OBJECTIVE: To demonstrate the utility of deep learning enhancement (DLE) to achieve diagnostic quality low-dose positron emission tomography (PET)/magnetic resonance (MR) imaging.
Image Interpretation, Computer-Assisted Fluorodeoxyglucose F18 Multimodal Imaging Radiopharmaceuticals Positron-Emission Tomography Female Aged Young Adult Adult Male Middle Aged Deep Learning Magnetic Resonance Imaging Humans
View on PubMed DOI

Use of a Dual Artificial Intelligence Platform to Detect Unreported Lung Nodules.

Journal of computer assisted tomography May 13, 2025
OBJECTIVE: To investigate the performance of Dual-AI Deep Learning Platform in detecting unreported pulmonary nodules that are 6 mm or greater, comprising computer-vision (CV) algorithm to detect pulmonary nodules, with positive results filtered by n...
Radiographic Image Interpretation, Computer-Assisted Female Aged Deep Learning Aged, 80 and over Adult Humans Adolescent Young Adult Male Artificial Intelligence Multiple Pulmonary Nodules Algorithms Middle Aged Natural Language Processing Retrospective Studies Lung Tomography, X-Ray Computed
View on PubMed DOI

Diagnostic Performance of the Support Vector Machine Model for Breast Cancer on Ring-Shaped Dedicated Breast Positron Emission Tomography Images.

Journal of computer assisted tomography Jan 1, 2020
OBJECTIVE: The aim of this study was to evaluate the diagnostic ability of support vector machine (SVM) for early breast cancer (BC) using dedicated breast positron emission tomography (dbPET).
Middle Aged Support Vector Machine Breast Aged Positron-Emission Tomography Humans Aged, 80 and over Image Interpretation, Computer-Assisted Retrospective Studies Adult Fluorodeoxyglucose F18 Female Breast Neoplasms
View on PubMed DOI
Popular Topics
Popular Journals