State-of-the-art deep learning in cardiovascular image analysis
Cardiovascular imaging is going to change substantially in the next decade, fueled by the
deep learning revolution. For medical professionals, it is important to keep track of these …
deep learning revolution. For medical professionals, it is important to keep track of these …
[HTML][HTML] Risk prediction of cardiovascular events by exploration of molecular data with explainable artificial intelligence
Cardiovascular diseases (CVD) annually take almost 18 million lives worldwide. Most lethal
events occur months or years after the initial presentation. Indeed, many patients experience …
events occur months or years after the initial presentation. Indeed, many patients experience …
Standardized assessment of automatic segmentation of white matter hyperintensities and results of the WMH segmentation challenge
Quantification of cerebral white matter hyperintensities (WMH) of presumed vascular origin
is of key importance in many neurological research studies. Currently, measurements are …
is of key importance in many neurological research studies. Currently, measurements are …
A recurrent CNN for automatic detection and classification of coronary artery plaque and stenosis in coronary CT angiography
M Zreik, RW Van Hamersvelt… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Various types of atherosclerotic plaque and varying grades of stenosis could lead to different
management of patients with a coronary artery disease. Therefore, it is crucial to detect and …
management of patients with a coronary artery disease. Therefore, it is crucial to detect and …
Automatic coronary artery calcium scoring in cardiac CT angiography using paired convolutional neural networks
The amount of coronary artery calcification (CAC) is a strong and independent predictor of
cardiovascular events. CAC is clinically quantified in cardiac calcium scoring CT (CSCT), but …
cardiovascular events. CAC is clinically quantified in cardiac calcium scoring CT (CSCT), but …
Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier
Coronary artery centerline extraction in cardiac CT angiography (CCTA) images is a
prerequisite for evaluation of stenoses and atherosclerotic plaque. In this work, we propose …
prerequisite for evaluation of stenoses and atherosclerotic plaque. In this work, we propose …
[HTML][HTML] Position paper of the EACVI and EANM on artificial intelligence applications in multimodality cardiovascular imaging using SPECT/CT, PET/CT, and cardiac …
In daily clinical practice, clinicians integrate available data to ascertain the diagnostic and
prognostic probability of a disease or clinical outcome for their patients. For patients with …
prognostic probability of a disease or clinical outcome for their patients. For patients with …
A deep-learning approach for direct whole-heart mesh reconstruction
Automated construction of surface geometries of cardiac structures from volumetric medical
images is important for a number of clinical applications. While deep-learning-based …
images is important for a number of clinical applications. While deep-learning-based …
Direct automatic coronary calcium scoring in cardiac and chest CT
Cardiovascular disease (CVD) is the global leading cause of death. A strong risk factor for
CVD events is the amount of coronary artery calcium (CAC). To meet the demands of the …
CVD events is the amount of coronary artery calcium (CAC). To meet the demands of the …
Cardiac imaging: working towards fully-automated machine analysis & interpretation
Introduction: Non-invasive imaging plays a critical role in managing patients with
cardiovascular disease. Although subjective visual interpretation remains the clinical …
cardiovascular disease. Although subjective visual interpretation remains the clinical …