AIMC Topic: Heart Atria
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An artificial intelligence-enabled electrocardiogram algorithm for the prediction of left atrial low-voltage areas in persistent atrial fibrillation.
Journal of cardiovascular electrophysiology
Jul 25, 2024
OBJECTIVES: We aimed to construct an artificial intelligence-enabled electrocardiogram (ECG) algorithm that can accurately predict the presence of left atrial low-voltage areas (LVAs) in patients with persistent atrial fibrillation.
Machine Learning of Cardiac Anatomy and the Risk of New-Onset Atrial Fibrillation After TAVR.
JACC. Clinical electrophysiology
Jun 5, 2024
BACKGROUND: New-onset atrial fibrillation (NOAF) occurs in 5% to 15% of patients who undergo transfemoral transcatheter aortic valve replacement (TAVR). Cardiac imaging has been underutilized to predict NOAF following TAVR.
Deep learning of left atrial structure and function provides link to atrial fibrillation risk.
Nature communications
May 21, 2024
Increased left atrial volume and decreased left atrial function have long been associated with atrial fibrillation. The availability of large-scale cardiac magnetic resonance imaging data paired with genetic data provides a unique opportunity to asse...
Mutual learning with reliable pseudo label for semi-supervised medical image segmentation.
Medical image analysis
Feb 21, 2024
Semi-supervised learning has garnered significant interest as a method to alleviate the burden of data annotation. Recently, semi-supervised medical image segmentation has garnered significant interest that can alleviate the burden of densely annotat...
Deep learning-based workflow for automatic extraction of atria and epicardial adipose tissue on cardiac computed tomography in atrial fibrillation.
Journal of the Chinese Medical Association : JCMA
Feb 21, 2024
BACKGROUND: Preoperative estimation of the volume of the left atrium (LA) and epicardial adipose tissue (EAT) on computed tomography (CT) images is associated with an increased risk of atrial fibrillation (AF) recurrence. We aimed to design a deep le...
Collaborative Learning for Annotation-Efficient Volumetric MR Image Segmentation.
Journal of magnetic resonance imaging : JMRI
Dec 29, 2023
BACKGROUND: Deep learning has presented great potential in accurate MR image segmentation when enough labeled data are provided for network optimization. However, manually annotating three-dimensional (3D) MR images is tedious and time-consuming, req...
Novel application of convolutional neural networks for artificial intelligence-enabled modified moving average analysis of P-, R-, and T-wave alternans for detection of risk for atrial and ventricular arrhythmias.
Journal of electrocardiology
Dec 26, 2023
BACKGROUND: T-wave alternans (TWA) analysis was shown in >14,000 individuals studied worldwide over the past two decades to be a useful tool to assess risk for cardiovascular mortality and sudden arrhythmic death. TWA analysis by the modified moving ...
Super-resolution deep learning reconstruction at coronary computed tomography angiography to evaluate the coronary arteries and in-stent lumen: an initial experience.
BMC medical imaging
Oct 30, 2023
A super-resolution deep learning reconstruction (SR-DLR) algorithm trained using data acquired on the ultrahigh spatial resolution computed tomography (UHRCT) has the potential to provide better image quality of coronary arteries on the whole-heart, ...
A multifunctional soft robot for cardiac interventions.
Science advances
Oct 25, 2023
In minimally invasive endovascular procedures, surgeons rely on catheters with low dexterity and high aspect ratios to reach an anatomical target. However, the environment inside the beating heart presents a combination of challenges unique to few an...
Automated 2-D and 3-D Left Atrial Volume Measurements Using Deep Learning.
Ultrasound in medicine & biology
Oct 8, 2023
OBJECTIVE: Echocardiography, a critical tool for assessing left atrial (LA) volume, often relies on manual or semi-automated measurements. This study introduces a fully automated, real-time method for measuring LA volume in both 2-D and 3-D imaging, ...
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