AIMC Topic: Magnetic Resonance Imaging, Cine

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Automated biventricular quantification in patients with repaired tetralogy of Fallot using a three-dimensional deep learning segmentation model.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Sep 11, 2024
BACKGROUND: Deep learning is the state-of-the-art approach for automated segmentation of the left ventricle (LV) and right ventricle (RV) in cardiovascular magnetic resonance (CMR) images. However, these models have been mostly trained and validated ...
Tetralogy of Fallot Deep Learning Reproducibility of Results Humans Magnetic Resonance Imaging, Cine Adolescent Databases, Factual Young Adult Ventricular Function, Right Child Predictive Value of Tests Retrospective Studies Adult Cardiac Surgical Procedures Female Imaging, Three-Dimensional Male Heart Ventricles Treatment Outcome Ventricular Function, Left Image Interpretation, Computer-Assisted Automation
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Predicting Late Gadolinium Enhancement of Acute Myocardial Infarction in Contrast-Free Cardiac Cine MRI Using Deep Generative Learning.

Circulation. Cardiovascular imaging Sep 10, 2024
BACKGROUND: Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) is a standard technique for diagnosing myocardial infarction (MI), which, however, poses risks due to gadolinium contrast usage. Techniques enabling MI assessment based on...
Humans Retrospective Studies Female Reproducibility of Results Aged Myocardium Myocardial Infarction Image Interpretation, Computer-Assisted Gadolinium Magnetic Resonance Imaging, Cine Male Middle Aged Deep Learning Contrast Media Predictive Value of Tests
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Accelerated chemical shift encoded cardiovascular magnetic resonance imaging with use of a resolution enhancement network.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Sep 5, 2024
BACKGROUND: Cardiovascular magnetic resonance (CMR) chemical shift encoding (CSE) enables myocardial fat imaging. We sought to develop a deep learning network (fast chemical shift encoding [FastCSE]) to accelerate CSE.
Retrospective Studies Adiposity Female Magnetic Resonance Imaging, Cine Reproducibility of Results Adipose Tissue Aged Adult Humans Predictive Value of Tests Male Young Adult Prospective Studies Myocardium Middle Aged Heart Diseases Case-Control Studies Image Interpretation, Computer-Assisted Deep Learning
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Deep learning approaches for the detection of scar presence from cine cardiac magnetic resonance adding derived parametric images.

Medical & biological engineering & computing Aug 6, 2024
This work proposes a convolutional neural network (CNN) that utilizes different combinations of parametric images computed from cine cardiac magnetic resonance (CMR) images, to classify each slice for possible myocardial scar tissue presence. The CNN...
Deep Learning ROC Curve Cicatrix Image Interpretation, Computer-Assisted Magnetic Resonance Imaging, Cine Humans Neural Networks, Computer Female Aged Male Middle Aged
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Clinical utility of a rapid two-dimensional balanced steady-state free precession sequence with deep learning reconstruction.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Jul 28, 2024
BACKGROUND: Cardiovascular magnetic resonance (CMR) cine imaging is still limited by long acquisition times. This study evaluated the clinical utility of an accelerated two-dimensional (2D) cine sequence with deep learning reconstruction (Sonic DL) t...
Ventricular Function, Left Stroke Volume Middle Aged Deep Learning Time Factors Ventricular Function, Right Female Predictive Value of Tests Reproducibility of Results Heart Ventricles Humans Aged Image Interpretation, Computer-Assisted Prospective Studies Adult Observer Variation Male Magnetic Resonance Imaging, Cine
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Accelerated cardiac magnetic resonance imaging using deep learning for volumetric assessment in children.

Pediatric radiology Jul 17, 2024
BACKGROUND: Ventricular volumetry using a short-axis stack of two-dimensional (D) cine balanced steady-state free precession (bSSFP) sequences is crucial in any cardiac magnetic resonance imaging (MRI) examination. This task becomes particularly chal...
Child Male Heart Ventricles Infant Image Interpretation, Computer-Assisted Deep Learning Magnetic Resonance Imaging, Cine Humans Adolescent Retrospective Studies Child, Preschool Female
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Identifying high-risk Fontan phenotypes using K-means clustering of cardiac magnetic resonance-based dyssynchrony metrics.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Jul 14, 2024
BACKGROUND: Individuals with a Fontan circulation encompass a heterogeneous group with adverse outcomes linked to ventricular dilation, dysfunction, and dyssynchrony. The purpose of this study was to assess if unsupervised machine learning cluster an...
Magnetic Resonance Imaging, Cine Myocardial Contraction Image Interpretation, Computer-Assisted Heart Transplantation Fontan Procedure Heart Defects, Congenital Ventricular Function, Left Risk Assessment Adolescent Time Factors Child Treatment Outcome Cluster Analysis Unsupervised Machine Learning Predictive Value of Tests Ventricular Dysfunction, Left Risk Factors Young Adult Humans Adult Phenotype Biomechanical Phenomena Retrospective Studies Male Female
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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...
Diastole Magnetic Resonance Imaging, Cine Tricuspid Valve Reproducibility of Results Adult Male Stroke Volume Middle Aged Deep Learning Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Systole Blood Flow Velocity Humans Algorithms Female
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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...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Heart Video Recording Magnetic Resonance Imaging, Cine Humans Deep Learning
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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 ...
Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Disease Models, Animal Heart Humans Reproducibility of Results Animals Stroke Volume Swine Myocardial Infarction Magnetic Resonance Imaging, Cine
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