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Cardiac-Gated Imaging Techniques

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Artificial intelligence-derived coronary artery calcium scoring saves time and achieves close to radiologist-level accuracy accuracy on routine ECG-gated CT.

The international journal of cardiovascular imaging Dec 16, 2024
Artificial Intelligence (AI) has been proposed to improve workflow for coronary artery calcium scoring (CACS), but simultaneous demonstration of improved efficiency, accuracy, and clinical stability have not been demonstrated. 148 sequential patients...
Middle Aged Severity of Illness Index Time Factors Electrocardiography Predictive Value of Tests Retrospective Studies Female Reproducibility of Results Aged Male Observer Variation Coronary Vessels Multidetector Computed Tomography Vascular Calcification Humans Computed Tomography Angiography Artificial Intelligence Cardiac-Gated Imaging Techniques Coronary Angiography Radiologists Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Workflow
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Evaluation of image quality on low contrast media with deep learning image reconstruction algorithm in prospective ECG-triggering coronary CT angiography.

The international journal of cardiovascular imaging May 9, 2024
To assess the impact of low-dose contrast media (CM) injection protocol with deep learning image reconstruction (DLIR) algorithm on image quality in coronary CT angiography (CCTA). In this prospective study, patients underwent CCTA were prospectively...
Humans Prospective Studies Female Reproducibility of Results Contrast Media Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Heart Rate Aged Male Middle Aged Deep Learning Electrocardiography Coronary Vessels Radiation Dosage Multidetector Computed Tomography Computed Tomography Angiography Cardiac-Gated Imaging Techniques
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Artificial intelligence in coronary artery calcium score: rationale, different approaches, and outcomes.

The international journal of cardiovascular imaging May 3, 2024
Almost 35 years after its introduction, coronary artery calcium score (CACS) not only survived technological advances but became one of the cornerstones of contemporary cardiovascular imaging. Its simplicity and quantitative nature established it as ...
Deep Learning Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Humans Cardiac-Gated Imaging Techniques Artificial Intelligence Coronary Vessels Prognosis Vascular Calcification Reproducibility of Results Computed Tomography Angiography Severity of Illness Index
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Gated cardiac CT in infants: What can we expect from deep learning image reconstruction algorithm?

Journal of cardiovascular computed tomography Mar 12, 2024
BACKGROUND: ECG-gated cardiac CT is now widely used in infants with congenital heart disease (CHD). Deep Learning Image Reconstruction (DLIR) could improve image quality while minimizing the radiation dose.
Cardiac-Gated Imaging Techniques Radiation Dosage Heart Defects, Congenital Phantoms, Imaging Computed Tomography Angiography Radiation Exposure Humans Reproducibility of Results Infant Deep Learning Electrocardiography Age Factors Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted
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Fully Automated Agatston Score Calculation From Electrocardiography-Gated Cardiac Computed Tomography Using Deep Learning and Multi-Organ Segmentation: A Validation Study.

Angiology Jan 2, 2024
To evaluate deep learning-based calcium segmentation and quantification on ECG-gated cardiac CT scans compared with manual evaluation. Automated calcium quantification was performed using a neural network based on mask regions with convolutional neur...
Cardiac-Gated Imaging Techniques Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Humans Coronary Artery Disease Female Male Neural Networks, Computer Retrospective Studies Tomography, X-Ray Computed Middle Aged Deep Learning Electrocardiography Predictive Value of Tests Reproducibility of Results Aged Vascular Calcification Computed Tomography Angiography
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Additional value of deep learning computed tomographic angiography-based fractional flow reserve in detecting coronary stenosis and predicting outcomes.

Acta radiologica (Stockholm, Sweden : 1987) Jan 1, 2022
BACKGROUND: Deep learning (DL) has achieved great success in medical imaging and could be utilized for the non-invasive calculation of fractional flow reserve (FFR) from coronary computed tomographic angiography (CCTA) (CT-FFR).
Humans Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial Cardiac-Gated Imaging Techniques Sensitivity and Specificity Retrospective Studies Male Female Middle Aged Aged Deep Learning Aged, 80 and over Predictive Value of Tests Adult
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Evaluation of a Deep Learning-Based Automated CT Coronary Artery Calcium Scoring Algorithm.

JACC. Cardiovascular imaging Feb 1, 2020
Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Automation Coronary Vessels Vascular Calcification Computed Tomography Angiography Cardiac-Gated Imaging Techniques Middle Aged Severity of Illness Index Diagnosis, Computer-Assisted Deep Learning Humans Electrocardiography Retrospective Studies Software Female Reproducibility of Results Aged Male
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Motion estimation and correction in cardiac CT angiography images using convolutional neural networks.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Sep 1, 2019
Cardiac motion artifacts frequently reduce the interpretability of coronary computed tomography angiography (CCTA) images and potentially lead to misinterpretations or preclude the diagnosis of coronary artery disease (CAD). In this paper, a novel mo...
Humans Motion Neural Networks, Computer Cardiac-Gated Imaging Techniques Artifacts Software Computed Tomography Angiography Imaging, Three-Dimensional Coronary Angiography Radiographic Image Interpretation, Computer-Assisted
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Motion artifact recognition and quantification in coronary CT angiography using convolutional neural networks.

Medical image analysis Feb 1, 2019
Excellent image quality is a primary prerequisite for diagnostic non-invasive coronary CT angiography. Artifacts due to cardiac motion may interfere with detection and diagnosis of coronary artery disease and render subsequent treatment decisions mor...
Motion Artifacts Computed Tomography Angiography Cardiac-Gated Imaging Techniques Humans Neural Networks, Computer Software Algorithms Coronary Angiography Supervised Machine Learning
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Real-time cardiovascular MR with spatio-temporal artifact suppression using deep learning-proof of concept in congenital heart disease.

Magnetic resonance in medicine Feb 1, 2019
PURPOSE: Real-time assessment of ventricular volumes requires high acceleration factors. Residual convolutional neural networks (CNN) have shown potential for removing artifacts caused by data undersampling. In this study, we investigated the ability...
Heart Image Interpretation, Computer-Assisted Artifacts Male Fourier Analysis Humans Respiration Middle Aged Breath Holding Heart Defects, Congenital Algorithms Deep Learning Magnetic Resonance Imaging, Cine Retrospective Studies Adolescent Cardiac-Gated Imaging Techniques Young Adult Image Processing, Computer-Assisted Adult
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