AIMC Topic: Ventricular Function, Left
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Myocardial scar and left ventricular ejection fraction classification for electrocardiography image using multi-task deep learning.
Scientific reports
Mar 29, 2024
Myocardial scar (MS) and left ventricular ejection fraction (LVEF) are vital cardiovascular parameters, conventionally determined using cardiac magnetic resonance (CMR). However, given the high cost and limited availability of CMR in resource-constra...
Deep Learning-Derived Myocardial Strain.
JACC. Cardiovascular imaging
Mar 27, 2024
BACKGROUND: Echocardiographic strain measurements require extensive operator experience and have significant intervendor variability. Creating an automated, open-source, vendor-agnostic method to retrospectively measure global longitudinal strain (GL...
Assessment of deep learning segmentation for real-time free-breathing cardiac magnetic resonance imaging at rest and under exercise stress.
Scientific reports
Feb 14, 2024
In recent years, a variety of deep learning networks for cardiac MRI (CMR) segmentation have been developed and analyzed. However, nearly all of them are focused on cine CMR under breathold. In this work, accuracy of deep learning methods is assessed...
Pragmatic Evaluation of a Deep-Learning Algorithm to Automate Ejection Fraction on Hand-Held, Point-of-Care Echocardiography in a Cardiac Surgical Operating Room.
Journal of cardiothoracic and vascular anesthesia
Jan 11, 2024
OBJECTIVE: To test the correlation of ejection fraction (EF) estimated by a deep-learning-based, automated algorithm (Auto EF) versus an EF estimated by Simpson's method.
Deep learning based automated left ventricle segmentation and flow quantification in 4D flow cardiac MRI.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Jan 10, 2024
BACKGROUND: 4D flow MRI enables assessment of cardiac function and intra-cardiac blood flow dynamics from a single acquisition. However, due to the poor contrast between the chambers and surrounding tissue, quantitative analysis relies on the segment...
Automation
Blood Flow Velocity
Coronary Circulation
Myocardial Perfusion Imaging
Magnetic Resonance Imaging, Cine
Deep Learning
Predictive Value of Tests
Humans
Heart Ventricles
Databases, Factual
Image Interpretation, Computer-Assisted
Female
Male
Reproducibility of Results
Ventricular Function, Left
Middle Aged
Utilizing Artificial Intelligence-Based Deformable Registration for Global and Layer-Specific Cardiac MRI Strain Analysis in Healthy Children and Young Adults.
Academic radiology
Jan 4, 2024
RATIONALE AND OBJECTIVES: The absence of published reference values for multilayer-specific strain measurement using cardiac magnetic resonance (CMR) in young healthy individuals limits its use. This study aimed to establish normal global and layer-s...
Empowering Medical Students: Harnessing Artificial Intelligence for Precision Point-of-Care Echocardiography Assessment of Left Ventricular Ejection Fraction.
International journal of clinical practice
Nov 29, 2023
INTRODUCTION: Point-of-care ultrasound (POCUS) use is now universal among nonexperts. Artificial intelligence (AI) is currently employed by nonexperts in various imaging modalities to assist in diagnosis and decision making.
High-resolution spiral real-time cardiac cine imaging with deep learning-based rapid image reconstruction and quantification.
NMR in biomedicine
Nov 5, 2023
The objective of the current study was to develop and evaluate a DEep learning-based rapid Spiral Image REconstruction (DESIRE) and deep learning (DL)-based segmentation approach to quantify the left ventricular ejection fraction (LVEF) for high-reso...
Electrocardiogram-based deep learning model to screen peripartum cardiomyopathy.
American journal of obstetrics & gynecology MFM
Oct 30, 2023
BACKGROUND: Peripartum cardiomyopathy, one of the most fatal conditions during delivery, results in heart failure secondary to left ventricular systolic dysfunction. Left ventricular dysfunction can result in abnormalities in electrocardiography. How...
Heterogeneous treatment effects of coronary artery bypass grafting in ischemic cardiomyopathy: A machine learning causal forest analysis.
The Journal of thoracic and cardiovascular surgery
Sep 15, 2023
OBJECTIVES: We aim to evaluate the heterogeneous treatment effects of coronary artery bypass grafting in patients with ischemic cardiomyopathy and to identify a group of patients to have greater benefits from coronary artery bypass grafting compared ...
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