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Improving Right Ventricle Contouring in Cardiac MR Images Using Integrated Approach for Small Datasets
Deep learning methods are showing progressive development in the medical imaging field. The accuracy of segmentation is improving challengingly with...
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MRI Cardiac Images Segmentation and Anomaly Detection Using U-Net Convolutional Neural Networks
Healthcare industry is increasingly adopting artificial intelligence in analyzing laboratory and radiology outputs to provide optimal treatments for...
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TAUNet: a triple-attention-based multi-modality MRI fusion U-Net for cardiac pathology segmentation
Automated segmentation of cardiac pathology in MRI plays a significant role for diagnosis and treatment of some cardiac disease. In clinical...
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Integrated approach for fully automatic left ventricle segmentation using adaptive iteration based parametric model with deep learning in short axis cardiac MRI
The left ventricle dysfunction is the root cause for major cardiac arrests across globe. Heart functional indices such as End diastolic volume,...
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Cardiac arrhythmia detection using dual-tree wavelet transform and convolutional neural network
The non-stationary ECG signals are used as key tools in screening coronary diseases. ECG recording is collected from millions of cardiac cells and...
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In Silico Closed-Loop System for the Assessment of Cardiac Pacing Algorithms
In this work, we report on the application of a closed-loop system, composed of a 2D reaction-diffusion heart model and a pace-maker model, for...
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An attention-based dense network model for cardiac image segmentation using learning approaches
Although the outcomes of the DL techniques obtained are promising, performance is always limited to some extent due to a need for more sufficient...
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Synthetic extracellular matrices with function-encoding peptides
The communication of cells with their surroundings is mostly encoded in the epitopes of structural and signalling proteins present in the...
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Intelligent prediction of sudden cardiac death based on multi-domain feature fusion of heart rate variability signals
Background and objectiveSudden cardiac death (SCD) is one of the leading causes of death in cardiovascular diseases. Monitoring the state of the...
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Artificial Intelligence of Things for Early Detection of Cardiac Diseases
Cardiovascular disease (CVD) is now the primary cause for morbidity and mortality around the world; with the substantial improvements in prognosis...
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Cardiac Flow Visualization Techniques
Existing cardiac flow visualization techniques will be described, both in vivo and in vitro. At the end of the chapter it will be shown the procedure...
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Non-invasive parameters of autonomic function using beat-to-beat cardiovascular variations and arterial stiffness in hypertensive individuals: a systematic review
PurposeNon-invasive, beat-to-beat variations in physiological indices provide an opportunity for more accessible assessment of autonomic dysfunction....
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Non-invasive myocardial work index contributes to early identification of impaired left ventricular myocardial function in uremic patients with preserved left ventricular ejection fraction
BackgroundCardiac damage is the leading cause of death in uremic patients. This study aimed to evaluate the application of non-invasive myocardial...
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ECG Signal Denoising Techniques for Cardiac Pacemaker Systems
Electrocardiogram (ECG) signals are used to diagnose cardiovascular diseases. Various noises like power line interference, baseline wandering, motion...
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Automated Detection of Cardiac Arrhythmia Based on a Hybrid CNN-LSTM Network
Cardiac arrhythmia is an irregular sequence of electrical impulses which result in numerous shifts in heart rhythms. Such cardiac abnormalities can...
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Classification of Cardiac Signals with Automated R-Peak Detection Using Wavelet Transform Method
Heart rate is a vital sign that holds important information about cardiac signals. The measurement of heart rate is of particular interest since it...
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Assessment of Cardiac Autonomic Modulation Parameters in a Healthy Population
Heart rate variability (HRV), a physiological measure, can manifest changes in stress levels even when other physiological variables like blood...
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A Novel and Self Adapting Machine Learning Approach of ECG Signal Classification in Association with Cardiac Arrhythmia
An irregular heartbeat is referred to as cardiac arrhythmia. It’s a condition in which the pulse is either too slow or too quick. When electrical...
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Heart disease diagnosis using deep learning and cardiac color doppler ultrasound
Deep learning (DL) has various applications in different fields such as smart agriculture, smart cities, intelligent transportation system,...
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Replacing renal function using bioengineered tissues
Kidney transplantation is at present the only definitive treatment for patients with end-stage kidney disease that can improve the quality of life...
