179 citations · 297 across the 11 of their papers we have counts for
5 papers · 1 filter
NeCA: 3D Coronary Artery Tree Reconstruction from Two 2D Projections via Neural Implicit Representation
Yiying Wang, Abhirup Banerjee, Vicente Grau
Cardiovascular diseases (CVDs) are the most common health threats worldwide. 2D X-ray invasive coronary angiography (ICA) remains the most widely adopted imaging modality for CVD a…
DeepCA: Deep Learning-based 3D Coronary Artery Tree Reconstruction from Two 2D Non-simultaneous X-ray Angiography Projections
Yiying Wang, Abhirup Banerjee, Robin P. Choudhury +1
Cardiovascular diseases (CVDs) are the most common cause of death worldwide. Invasive x-ray coronary angiography (ICA) is one of the most important imaging modalities for the diagn…
Modeling 3D cardiac contraction and relaxation with point cloud deformation networks
Marcel Beetz, Abhirup Banerjee, Vicente Grau
Global single-valued biomarkers of cardiac function typically used in clinical practice, such as ejection fraction, provide limited insight on the true 3D cardiac deformation proce…
Multi-class point cloud completion networks for 3D cardiac anatomy reconstruction from cine magnetic resonance images
Marcel Beetz, Abhirup Banerjee, Julius Ossenberg-Engels +1
Cine magnetic resonance imaging (MRI) is the current gold standard for the assessment of cardiac anatomy and function. However, it typically only acquires a set of two-dimensional…
DenResCov-19: A deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays
Michail Mamalakis, Andrew J. Swift, Bart Vorselaars +6
The global pandemic of COVID-19 is continuing to have a significant effect on the well-being of global population, increasing the demand for rapid testing, diagnosis, and treatment…