AIMC Topic: Magnetic Resonance Imaging, Cine

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High-Resolution Maps of Left Atrial Displacements and Strains Estimated With 3D Cine MRI Using Online Learning Neural Networks.

IEEE transactions on medical imaging May 2, 2025
The functional analysis of the left atrium (LA) is important for evaluating cardiac health and understanding diseases like atrial fibrillation. Cine MRI is ideally placed for the detailed 3D characterization of LA motion and deformation but is lackin...
Magnetic Resonance Imaging, Cine Imaging, Three-Dimensional Heart Atria Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Female Aged Adult Male Middle Aged
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Deep learning based automated left atrial segmentation and flow quantification of real time phase contrast MRI in patients with atrial fibrillation.

The international journal of cardiovascular imaging Apr 29, 2025
Real time 2D phase contrast (RTPC) MRI is useful for flow quantification in atrial fibrillation (AF) patients, but data analysis requires time-consuming anatomical contouring for many cardiac time frames. Our goal was to develop a convolutional neura...
Reproducibility of Results Aged Male Middle Aged Humans Female Atrial Fibrillation Heart Atria Heart Rate Image Interpretation, Computer-Assisted Deep Learning Time Factors Magnetic Resonance Imaging Predictive Value of Tests Atrial Function, Left Observer Variation Magnetic Resonance Imaging, Cine Automation Blood Flow Velocity
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Artificial intelligence-assisted left ventricular global longitudinal strain assessment in patients with acute myocardial infarction: a RESUS-AMI trial sub-analysis.

The international journal of cardiovascular imaging Apr 29, 2025
PURPOSE: The aim of this sub-analysis of the RESUS-AMI trial was to evaluate the correlation of artificial intelligence (AI)-assisted echocardiographic global longitudinal strain (GLS) assessments with infarct size, left ventricular ejection fraction...
Image Interpretation, Computer-Assisted Observer Variation Magnetic Resonance Imaging, Cine Myocardial Contraction Treatment Outcome Predictive Value of Tests ST Elevation Myocardial Infarction Female Percutaneous Coronary Intervention Reproducibility of Results Aged Male Global Longitudinal Strain Ventricular Function, Left Stroke Volume Humans Echocardiography Artificial Intelligence Middle Aged
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HALSR-Net: Improving CNN Segmentation of Cardiac Left Ventricle MRI with Hybrid Attention and Latent Space Reconstruction.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Apr 12, 2025
Accurate cardiac MRI segmentation is vital for detailed cardiac analysis, yet the manual process is labor-intensive and prone to variability. Despite advancements in MRI technology, there remains a significant need for automated methods that can reli...
Image Processing, Computer-Assisted Humans Heart Ventricles Image Interpretation, Computer-Assisted Neural Networks, Computer Magnetic Resonance Imaging, Cine Reproducibility of Results
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Machine Learning Identification of Patient Phenoclusters in Aortic Regurgitation.

JACC. Cardiovascular imaging Mar 26, 2025
BACKGROUND: Current treatment paradigms assume aortic regurgitation (AR) patients to be a homogenous population, but varied courses of disease progression and outcomes are observed clinically.
Risk Factors Aged Adult Male Ventricular Function, Left Middle Aged Risk Assessment Disease Progression Prognosis Retrospective Studies Female Magnetic Resonance Imaging, Cine Reproducibility of Results Machine Learning Humans Decision Support Techniques Unsupervised Machine Learning Severity of Illness Index Phenotype Predictive Value of Tests Time Factors Sex Factors United States Aortic Valve Insufficiency Aortic Valve
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Texture-based probability mapping for automatic assessment of myocardial injury in late gadolinium enhancement images after revascularized STEMI.

International journal of cardiology Mar 2, 2025
BACKGROUND: Late Gadolinium-enhancement in cardiac magnetic resonance imaging (LGE-CMR) is the gold standard for assessing myocardial infarction (MI) size. Texture-based probability mapping (TPM) is a novel machine learning-based analysis of LGE imag...
Proof of Concept Study Magnetic Resonance Imaging, Cine Aged Male Middle Aged Follow-Up Studies Contrast Media ST Elevation Myocardial Infarction Percutaneous Coronary Intervention Gadolinium Humans Prospective Studies Female
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Computationally Efficient Implicit Training Strategy for Unrolled Networks (IMUNNE): A Preliminary Analysis Using Accelerated Real-Time Cardiac Cine MRI.

IEEE transactions on bio-medical engineering Jan 15, 2025
OBJECTIVE: Highly-undersampled, dynamic MRI reconstruction, particularly in multi-coil scenarios, is a challenging inverse problem. Unrolled networks achieve state-of-the-art performance in MRI reconstruction but suffer from long training times and e...
Image Processing, Computer-Assisted Humans Heart Neural Networks, Computer Magnetic Resonance Imaging, Cine Algorithms Deep Learning
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Artificial intelligence for left ventricular hypertrophy detection and differentiation on echocardiography, cardiac magnetic resonance and cardiac computed tomography: A systematic review.

International journal of cardiology Jan 10, 2025
AIMS: Left ventricular hypertrophy (LVH) is a common clinical finding associated with adverse cardiovascular outcomes. Once LVH is diagnosed, defining its cause has crucial clinical implications. Artificial intelligence (AI) may allow significant pro...
Humans Diagnosis, Differential Artificial Intelligence Hypertrophy, Left Ventricular Tomography, X-Ray Computed Magnetic Resonance Imaging, Cine Echocardiography
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Prediction of real-time cine-MR images during MRI-guided radiotherapy of liver cancer using a GAN-ConvLSTM network.

Medical physics Jan 4, 2025
BACKGROUND: Respiratory motion during radiotherapy (RT) may reduce the therapeutic effect and increase the dose received by organs at risk. This can be addressed by real-time tracking, where respiration motion prediction is currently required to comp...
Image Processing, Computer-Assisted Respiration Radiotherapy, Image-Guided Magnetic Resonance Imaging, Cine Neural Networks, Computer Humans Deep Learning Time Factors Liver Neoplasms
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Attention incorporated network for sharing low-rank, image and k-space information during MR image reconstruction to achieve single breath-hold cardiac Cine imaging.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Dec 28, 2024
Cardiac Cine Magnetic Resonance Imaging (MRI) provides an accurate assessment of heart morphology and function in clinical practice. However, MRI requires long acquisition times, with recent deep learning-based methods showing great promise to accele...
Humans Heart Deep Learning Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Breath Holding Magnetic Resonance Imaging, Cine
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