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Myocardium

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Machine Learning-Based Prediction of Myocardial Recovery in Patients With Left Ventricular Assist Device Support.

Circulation. Heart failure
BACKGROUND: Prospective studies demonstrate that aggressive pharmacological therapy combined with pump speed optimization may result in myocardial recovery in larger numbers of patients supported with left ventricular assist device (LVAD). This study...

A deep learning approach to identify and segment alpha-smooth muscle actin stress fiber positive cells.

Scientific reports
Cardiac fibrosis is a pathological process characterized by excessive tissue deposition, matrix remodeling, and tissue stiffening, which eventually leads to organ failure. On a cellular level, the development of fibrosis is associated with the activa...

Towards Intraoperative Quantification of Atrial Fibrosis Using Light-Scattering Spectroscopy and Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Light-scattering spectroscopy (LSS) is an established optical approach for characterization of biological tissues. Here, we investigated the capabilities of LSS and convolutional neural networks (CNNs) to quantitatively characterize the composition a...

Classifying Microscopic Acute and Old Myocardial Infarction Using Convolutional Neural Networks.

The American journal of forensic medicine and pathology
Convolutional neural network (CNN) has advanced in recent years and translated from research into medical practice, most notably in clinical radiology and histopathology. Research on CNNs in forensic/postmortem pathology is almost exclusive to postmo...

Detecting myocardial scar using electrocardiogram data and deep neural networks.

Biological chemistry
Ischaemic heart disease is among the most frequent causes of death. Early detection of myocardial pathologies can increase the benefit of therapy and reduce the number of lethal cases. Presence of myocardial scar is an indicator for developing ischae...

Improved Quantification of Myocardium Scar in Late Gadolinium Enhancement Images: Deep Learning Based Image Fusion Approach.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Quantification of myocardium scarring in late gadolinium enhanced (LGE) cardiac magnetic resonance imaging can be challenging due to low scar-to-background contrast and low image quality. To resolve ambiguous LGE regions, experienced read...

Decoding empagliflozin's molecular mechanism of action in heart failure with preserved ejection fraction using artificial intelligence.

Scientific reports
The use of sodium-glucose co-transporter 2 inhibitors to treat heart failure with preserved ejection fraction (HFpEF) is under investigation in ongoing clinical trials, but the exact mechanism of action is unclear. Here we aimed to use artificial int...

A deep learning approach with temporal consistency for automatic myocardial segmentation of quantitative myocardial contrast echocardiography.

The international journal of cardiovascular imaging
Quantitative myocardial contrast echocardiography (MCE) has been proved to be valuable in detecting myocardial ischemia. During quantitative MCE analysis, myocardial segmentation is a critical step in determining accurate region of interests (ROIs). ...

Improvement of late gadolinium enhancement image quality using a deep learning-based reconstruction algorithm and its influence on myocardial scar quantification.

European radiology
OBJECTIVES: The aim of this study was to assess the effect of a deep learning (DL)-based reconstruction algorithm on late gadolinium enhancement (LGE) image quality and to evaluate its influence on scar quantification.