Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review
In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of
mortality globally. At early stages, CVDs appear with minor symptoms and progressively get …
mortality globally. At early stages, CVDs appear with minor symptoms and progressively get …
Respiratory motion correction for free-breathing 3D abdominal MRI using CNN-based image registration: a feasibility study
Objective: Free-breathing abdomen imaging requires non-rigid motion registration of
unavoidable respiratory motion in three-dimensional undersampled data sets. In this work …
unavoidable respiratory motion in three-dimensional undersampled data sets. In this work …
Generalization of feature embeddings transferred from different video anomaly detection domains
Detecting anomalous activity in video surveillance often suffers from limited availability of
training data. Transfer learning may close this gap, allowing to use existing annotated data …
training data. Transfer learning may close this gap, allowing to use existing annotated data …
A multi-level convolutional LSTM model for the segmentation of left ventricle myocardium in infarcted porcine cine MR images
Automatic segmentation of left ventricle (LV) myocardium in cardiac short-axis cine MR
images acquired on subjects with myocardial infarction is a challenging task, mainly …
images acquired on subjects with myocardial infarction is a challenging task, mainly …
Improving privacy-preserving multi-faceted long short-term memory for accurate evaluation of encrypted time-series MRI images in heart disease
In therapeutic diagnostics, early diagnosis and monitoring of heart disease is dependent on
fast time-series MRI data processing. Robust encryption techniques are necessary to …
fast time-series MRI data processing. Robust encryption techniques are necessary to …
Development of magnetic resonance image de-noising methodologies: a comprehensive overview of the state-of-the-art
Denoising of various radiological images is crucial, as a minute loss of a detail result in
colossal failure. While numerous frequency domain and spatial denoising approaches are …
colossal failure. While numerous frequency domain and spatial denoising approaches are …
Automatic left ventricle segmentation from cardiac magnetic resonance images using a capsule network
PURPOSE: Segmentation of magnetic resonance images (MRI) of the left ventricle (LV)
plays a key role in quantifying the volumetric functions of the heart, such as the area …
plays a key role in quantifying the volumetric functions of the heart, such as the area …
Transfer learning for the fully automatic segmentation of left ventricle myocardium in porcine cardiac cine MR images
A fully automatic approach for the segmentation of the left ventricle (LV) myocardium in
porcine cardiac cine MRI images is proposed based on deep convolutional neural networks …
porcine cardiac cine MRI images is proposed based on deep convolutional neural networks …
Multislice left ventricular ejection fraction prediction from cardiac MRIs without segmentation using shared SptDenNet
We propose a spatiotemporal model for cardiac magnetic resonance images (MRI) named
SptDenNet. The proposed model is based on DenseNet and extracts spatial and temporal …
SptDenNet. The proposed model is based on DenseNet and extracts spatial and temporal …
Multi-level convolutional LSTM model for the segmentation of MR images
Approaches for the automatic segmentation of magnetic resonance (MR) images. Machine
learning models segment images to identify image features in consecutive frames at …
learning models segment images to identify image features in consecutive frames at …