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Deep learning for cardiac image segmentation: a review
Deep learning has become the most widely used approach for cardiac image segmentation
in recent years. In this paper, we provide a review of over 100 cardiac image segmentation …
in recent years. In this paper, we provide a review of over 100 cardiac image segmentation …
A review of heart chamber segmentation for structural and functional analysis using cardiac magnetic resonance imaging
Cardiovascular magnetic resonance (CMR) has become a key imaging modality in clinical
cardiology practice due to its unique capabilities for non-invasive imaging of the cardiac …
cardiology practice due to its unique capabilities for non-invasive imaging of the cardiac …
Fully convolutional multi-scale residual DenseNets for cardiac segmentation and automated cardiac diagnosis using ensemble of classifiers
Deep fully convolutional neural network (FCN) based architectures have shown great
potential in medical image segmentation. However, such architectures usually have millions …
potential in medical image segmentation. However, such architectures usually have millions …
A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI
Segmentation of the left ventricle (LV) from cardiac magnetic resonance imaging (MRI)
datasets is an essential step for calculation of clinical indices such as ventricular volume and …
datasets is an essential step for calculation of clinical indices such as ventricular volume and …
A fully convolutional neural network for cardiac segmentation in short-axis MRI
Automated cardiac segmentation from magnetic resonance imaging datasets is an essential
step in the timely diagnosis and management of cardiac pathologies. We propose to tackle …
step in the timely diagnosis and management of cardiac pathologies. We propose to tackle …
Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis
In patients with coronary artery stenoses of intermediate severity, the functional significance
needs to be determined. Fractional flow reserve (FFR) measurement, performed during …
needs to be determined. Fractional flow reserve (FFR) measurement, performed during …
Adversarial image synthesis for unpaired multi-modal cardiac data
This paper demonstrates the potential for synthesis of medical images in one modality (eg
MR) from images in another (eg CT) using a CycleGAN [24] architecture. The synthesis can …
MR) from images in another (eg CT) using a CycleGAN [24] architecture. The synthesis can …
Convolutional neural network regression for short-axis left ventricle segmentation in cardiac cine MR sequences
Automated left ventricular (LV) segmentation is crucial for efficient quantification of cardiac
function and morphology to aid subsequent management of cardiac pathologies. In this …
function and morphology to aid subsequent management of cardiac pathologies. In this …
[HTML][HTML] Multi-modality cardiac image computing: A survey
Multi-modality cardiac imaging plays a key role in the management of patients with
cardiovascular diseases. It allows a combination of complementary anatomical …
cardiovascular diseases. It allows a combination of complementary anatomical …
Automated localization and segmentation techniques for B-mode ultrasound images: A review
B-mode ultrasound imaging is used extensively in medicine. Hence, there is a need to have
efficient segmentation tools to aid in computer-aided diagnosis, image-guided interventions …
efficient segmentation tools to aid in computer-aided diagnosis, image-guided interventions …