AIMC Topic: Heart Ventricles
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AI-derived automated quantification of cardiac chambers and myocardium from non-contrast CT: Prediction of major adverse cardiovascular events in asymptomatic subjects.
Atherosclerosis
Dec 22, 2024
BACKGROUND AND AIMS: The significance of left ventricular mass and chamber volumes from non-contrast computed tomography (CT) for predicting major adverse cardiovascular events (MACE) has not been studied. Our objective was to evaluate the role of ar...
Predictive Value of Tests
Coronary Angiography
Radiographic Image Interpretation, Computer-Assisted
Vascular Calcification
Asymptomatic Diseases
Coronary Artery Disease
Heart Ventricles
Male
Middle Aged
Risk Assessment
Deep Learning
Tomography, X-Ray Computed
Female
Aged
Artificial Intelligence
Prognosis
Humans
Reliability of post-contrast deep learning-based highly accelerated cardiac cine MRI for the assessment of ventricular function.
Magnetic resonance imaging
Dec 19, 2024
OBJECTIVE: The total examination time can be reduced if high-quality two-dimensional (2D) cine images can be collected post-contrast to minimize non-scanning time prior to late gadolinium-enhanced imaging. This study aimed to assess the equivalency o...
Super-resolution left ventricular flow and pressure mapping by Navier-Stokes-informed neural networks.
Computers in biology and medicine
Dec 12, 2024
Intraventricular vector flow mapping (VFM) is an increasingly adopted echocardiographic technique that derives time-resolved two-dimensional flow maps in the left ventricle (LV) from color-Doppler sequences. Current VFM models rely on kinematic const...
Deep-DM: Deep-Driven Deformable Model for 3D Image Segmentation Using Limited Data.
IEEE journal of biomedical and health informatics
Dec 5, 2024
Objective - Medical image segmentation is essential for several clinical tasks, including diagnosis, surgical and treatment planning, and image-guided interventions. Deep Learning (DL) methods have become the state-of-the-art for several image segmen...
BEAS-Net: A Shape-Prior-Based Deep Convolutional Neural Network for Robust Left Ventricular Segmentation in 2-D Echocardiography.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 27, 2024
Left ventricle (LV) segmentation of 2-D echocardiography images is an essential step in the analysis of cardiac morphology and function and-more generally-diagnosis of cardiovascular diseases (CVD). Several deep learning (DL) algorithms have recently...
Physics-Guided Neural Networks for Intraventricular Vector Flow Mapping.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 27, 2024
Intraventricular vector flow mapping (iVFM) seeks to enhance and quantify color Doppler in cardiac imaging. In this study, we propose novel alternatives to the traditional iVFM optimization scheme using physics-informed neural networks (PINNs) and a ...
Spatiotemporal Deep Learning-Based Cine Loop Quality Filter for Handheld Point-of-Care Echocardiography.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 27, 2024
The reliability of automated image interpretation of point-of-care (POC) echocardiography scans depends on the quality of the acquired ultrasound data. This work reports on the development and validation of spatiotemporal deep learning models to asse...
A deep learning based method for left ventricular strain measurements: repeatability and accuracy compared to experienced echocardiographers.
BMC medical imaging
Nov 12, 2024
BACKGROUND: Speckle tracking echocardiography (STE) provides quantification of left ventricular (LV) deformation and is useful in the assessment of LV function. STE is increasingly being used clinically, and every effort to simplify and standardize S...
AI derived ECG global longitudinal strain compared to echocardiographic measurements.
Scientific reports
Nov 2, 2024
Left ventricular (LV) global longitudinal strain (LVGLS) is versatile; however, it is difficult to obtain. We evaluated the potential of an artificial intelligence (AI)-generated electrocardiography score for LVGLS estimation (ECG-GLS score) to diagn...
Accelerated cardiac cine with spatio-coil regularized deep learning reconstruction.
Magnetic resonance in medicine
Oct 21, 2024
PURPOSE: To develop an iterative deep learning (DL) reconstruction with spatio-coil regularization and multichannel k-space data consistency for accelerated cine imaging.
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