AIMC Topic: Magnetic Resonance Imaging, Cine

Clear Filters Showing 31 to 40 of 175 articles

Tricuspid valve flow measurement using a deep learning framework for automated valve-tracking 2D phase contrast.

Magnetic resonance in medicine May 31, 2024
PURPOSE: Tricuspid valve flow velocities are challenging to measure with cardiovascular MR, as the rapidly moving valvular plane prohibits direct flow evaluation, but they are vitally important to diastolic function evaluation. We developed an automa...
Systole Blood Flow Velocity Diastole Magnetic Resonance Imaging, Cine Tricuspid Valve Stroke Volume Middle Aged Deep Learning Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Female Reproducibility of Results Adult Male Humans Algorithms
View on PubMed DOI

Training deep learning based dynamic MR image reconstruction using open-source natural videos.

Scientific reports May 23, 2024
To develop and assess a deep learning (DL) pipeline to learn dynamic MR image reconstruction from publicly available natural videos (Inter4K). Learning was performed for a range of DL architectures (VarNet, 3D UNet, FastDVDNet) and corresponding samp...
Video Recording Magnetic Resonance Imaging, Cine Humans Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Heart
View on PubMed DOI

Cardiac function in a large animal model of myocardial infarction at 7 T: deep learning based automatic segmentation increases reproducibility.

Scientific reports May 14, 2024
Cardiac magnetic resonance (CMR) imaging allows precise non-invasive quantification of cardiac function. It requires reliable image segmentation for myocardial tissue. Clinically used software usually offers automatic approaches for this step. These ...
Animals Stroke Volume Swine Deep Learning Image Processing, Computer-Assisted Humans Reproducibility of Results Magnetic Resonance Imaging Disease Models, Animal Heart Myocardial Infarction Magnetic Resonance Imaging, Cine
View on PubMed DOI

The use of artificial intelligence for predicting postinfarction myocardial viability in echocardiographic images.

Cardiology journal May 14, 2024
BACKGROUND: Evaluation of standard echocardiographic examination with artificial intelligence may help in the diagnosis of myocardial viability and function recovery after acute coronary syndrome.
Reproducibility of Results Humans Follow-Up Studies Acute Coronary Syndrome Aged Predictive Value of Tests Neural Networks, Computer Echocardiography, Stress Male Artificial Intelligence Myocardium Middle Aged Magnetic Resonance Imaging, Cine Female Percutaneous Coronary Intervention Time Factors Tissue Survival Myocardial Infarction
View on PubMed DOI

Screening and diagnosis of cardiovascular disease using artificial intelligence-enabled cardiac magnetic resonance imaging.

Nature medicine May 13, 2024
Cardiac magnetic resonance imaging (CMR) is the gold standard for cardiac function assessment and plays a crucial role in diagnosing cardiovascular disease (CVD). However, its widespread application has been limited by the heavy resource burden of CM...
Humans Artificial Intelligence Female Aged Adult Magnetic Resonance Imaging Magnetic Resonance Imaging, Cine Male Cardiovascular Diseases Middle Aged Mass Screening
View on PubMed DOI

Machine Learning Quantification of Pulmonary Regurgitation Fraction from Echocardiography.

Pediatric cardiology May 10, 2024
Assessment of pulmonary regurgitation (PR) guides treatment for patients with congenital heart disease. Quantitative assessment of PR fraction (PRF) by echocardiography is limited. Cardiac MRI (cMRI) is the reference-standard for PRF quantification. ...
ROC Curve Retrospective Studies Heart Defects, Congenital Magnetic Resonance Imaging, Cine Female Humans Pulmonary Valve Insufficiency Young Adult Machine Learning Echocardiography Adult Algorithms Infant Male Adolescent Child, Preschool Child
View on PubMed DOI

Integration of Cine-cardiac Magnetic Resonance Radiomics and Machine Learning for Differentiating Ischemic and Dilated Cardiomyopathy.

Academic radiology May 3, 2024
RATIONALE AND OBJECTIVES: This study aims to evaluate the capability of machine learning algorithms in utilizing radiomic features extracted from cine-cardiac magnetic resonance (CMR) sequences for differentiating between ischemic cardiomyopathy (ICM...
Humans Machine Learning Algorithms Retrospective Studies Female Diagnosis, Differential Image Interpretation, Computer-Assisted Myocardial Ischemia Magnetic Resonance Imaging, Cine Cardiomyopathy, Dilated Aged Adult Radiomics Male Middle Aged
View on PubMed DOI

DEep LearnIng-based QuaNtification of epicardial adipose tissue predicts MACE in patients undergoing stress CMR.

Atherosclerosis Apr 18, 2024
BACKGROUND AND AIMS: This study investigated the additional prognostic value of epicardial adipose tissue (EAT) volume for major adverse cardiovascular events (MACE) in patients undergoing stress cardiac magnetic resonance (CMR) imaging.
Middle Aged Risk Assessment Deep Learning Magnetic Resonance Imaging Adipose Tissue Humans Predictive Value of Tests Coronary Artery Disease Risk Factors Myocardial Infarction Aged Epicardial Adipose Tissue Pericardium Prognosis Male Magnetic Resonance Imaging, Cine Retrospective Studies Ventricular Function, Left Female Stroke Volume Reproducibility of Results
View on PubMed DOI

Radiomics-based detection of acute myocardial infarction on noncontrast enhanced midventricular short-axis cine CMR images.

The international journal of cardiovascular imaging Apr 17, 2024
Cardiac magnetic resonance cine images are primarily used to evaluate functional consequences, whereas limited information is extracted from the noncontrast pixel-wise myocardial signal intensity pattern. In this study we want to assess whether chara...
Ventricular Function, Left Middle Aged Case-Control Studies Support Vector Machine Predictive Value of Tests Reproducibility of Results Aged Adult Myocardial Infarction Radiomics Image Interpretation, Computer-Assisted Humans Male Magnetic Resonance Imaging, Cine Retrospective Studies Female
View on PubMed DOI

Diastolic function assessment with four-dimensional flow cardiovascular magnetic resonance using automatic deep learning E/A ratio analysis.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Mar 30, 2024
BACKGROUND: Diastolic left ventricular (LV) dysfunction is a powerful contributor to the symptoms and prognosis of patients with heart failure. In patients with depressed LV systolic function, the E/A ratio, the ratio between the peak early (E) and t...
Ventricular Function, Left Middle Aged Deep Learning Chronic Disease Humans Predictive Value of Tests Echocardiography, Doppler Female Blood Flow Velocity Reproducibility of Results Mitral Valve Diastole Aged Ventricular Dysfunction, Left Magnetic Resonance Imaging, Cine Male Image Interpretation, Computer-Assisted Automation Myocardial Ischemia
View on PubMed DOI
Popular Topics
Recent Journals