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Deep Learning Algorithm for Classifying Dilated Cardiomyopathy and Hypertrophic Cardiomyopathy in Transport Workers
Automatic classification of the different types of cardiomyopathies is desirable, but has been done less with a convolutional neural network (CNN)....
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Pixel-Correlation-Based Scar Screening in Hypertrophic Myocardium
The screening of myocardial scars in patients with hypertrophic cardiomyopathy(HCM) using cine magnetic resonance images(Cine-MRI) is critical in...
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FusionNet: A Frame Interpolation Network for 4D Heart Models
Cardiac magnetic resonance (CMR) imaging is widely used to visualise cardiac motion and diagnose heart disease. However, standard CMR imaging...
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An Exploratory Assessment of Focused Septal Growth in Hypertrophic Cardiomyopathy
Growth and Remodelling (G&R) processes are typical responses to changes in the heart’s loading conditions. The most frequent types of growth in the...
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Automated Quality-Controlled Left Heart Segmentation from 2D Echocardiography
Segmentation of 2D echocardiography (2DE) images is an important prerequisite for quantifying cardiac function. Although deep learning can automate...
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Implementing Machine Vision Process to Analyze Echocardiography for Heart Health Monitoring
Machine vision analysis of echocardiography images (echo) has vital recent advances. Echocardiography images are ultrasound scans that present the...
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Learning-based techniques for heart disease prediction: a survey of models and performance metrics
Heart disease (HD) is a major threat to human health, and the medical field generates vast amounts of data that doctors struggle to effectively...
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What can machines learn about heart failure? A systematic literature review
This paper presents a systematic literature review with respect to application of data science and machine learning (ML) to heart failure (HF)...
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AI and The Cardiologist-When Mind, Heart and Machine Unite
Artificial Intelligence (AI) and Deep Learning have made much headway in the consumer and advertising sector, not only affecting how and what people...
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Comparison of Different Parallel Transport Methods for the Study of Deformations in 3D Cardiac Data
Comparing the deformations of different beating hearts is a challenging operation. As in clinics the impaired condition is often recognized upon...
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Identification of systolic and diastolic heart failure progression with Krawtchouk moment feature-aided Harris hawks optimized support vector machine
The systolic and diastolic heart failure (HF) subjects are typically categorized based on clinical indices only. The relationship between different...
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Visual recognition of cardiac pathology based on 3D parametric model reconstruction
Visual recognition of cardiac images is important for cardiac pathology diagnosis and treatment. Due to the limited availability of annotated...
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Personal-by-Design: A 3D Electromechanical Model of the Heart Tailored for Personalisation
In this work we present a coupled electromechanical model of the heart for patient-specific simulations, and in particular cardiac resynchronisation...
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A Survey on Image-Based Cardiac Diagnosis Prediction Using Machine Learning and Deep Learning Techniques
Cardiac imaging is crucial in the diagnosis of cardiovascular disease. Cardiovascular disease is the umbrella term for the majority of heart...
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Pathology Synthesis of 3D Consistent Cardiac MR Images Using 2D VAEs and GANs
We propose a method for synthesizing cardiac MR images with plausible heart shapes and realistic appearances for the purpose of generating labeled...
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Ultrastructure Analysis of Cardiomyocytes and Their Nuclei
Cardiomyocytes are elongated and densely packed in the mammalian heart and connected end on end to achieve a functional syncytium. Qualitative...
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Automated Segmentation of the Right Ventricle from Magnetic Resonance Imaging Using Deep Convolutional Neural Networks
Although the left ventricle (LV) is commonly assessed in current clinical practice, the assessment of the right ventricle (RV) also plays an...
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Comparison of CNN Fusion Strategies for Left Ventricle Segmentation from Multi-modal MRI
Delayed enhancement magnetic resonance imaging (DE-MRI) is the gold standard to evaluate the state of the heart after myocardial infarction (MI). To...
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Artificial intelligence-based myocardial infarction diagnosis: a comprehensive review of modern techniques
Myocardial infarction (MI), commonly known as a heart attack, is a serious medical condition that can lead to congestive heart failure and even...
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A Multi-view Crossover Attention U-Net Cascade with Fourier Domain Adaptation for Multi-domain Cardiac MRI Segmentation
Cardiac image segmentation is a crucial step in clinical practice as it allows for the assessment of cardiac morphology and the quantification of...