Deep Learning Framework for Real-Time Estimation of in-silico Thrombotic Risk Indices in the Left Atrial Appendage
Patient-specific computational fluid dynamics (CFD) simulations can provide invaluable
insight into the interaction of left atrial appendage (LAA) morphology, hemodynamics, and …
insight into the interaction of left atrial appendage (LAA) morphology, hemodynamics, and …
Interpretable cardiac anatomy modeling using variational mesh autoencoders
M Beetz, J Corral Acero, A Banerjee, I Eitel… - Frontiers in …, 2022 - frontiersin.org
Cardiac anatomy and function vary considerably across the human population with
important implications for clinical diagnosis and treatment planning. Consequently, many …
important implications for clinical diagnosis and treatment planning. Consequently, many …
[HTML][HTML] A Review of Personalised Cardiac Computational Modelling Using Electroanatomical Mapping Data
Computational models of cardiac electrophysiology have gradually matured during the past
few decades and are now being personalised to provide patient-specific therapy guidance …
few decades and are now being personalised to provide patient-specific therapy guidance …
Towards enabling cardiac digital twins of myocardial infarction using deep computational models for inverse inference
Cardiac digital twins (CDTs) have the potential to offer individualized evaluation of cardiac
function in a non-invasive manner, making them a promising approach for personalized …
function in a non-invasive manner, making them a promising approach for personalized …
Deep computational model for the inference of ventricular activation properties
Patient-specific cardiac computational models are essential for the efficient realization of
precision medicine and in-silico clinical trials using digital twins. Cardiac digital twins can …
precision medicine and in-silico clinical trials using digital twins. Cardiac digital twins can …
Mesh convolutional neural networks for wall shear stress estimation in 3D artery models
Computational fluid dynamics (CFD) is a valuable tool for personalised, non-invasive
evaluation of hemodynamics in arteries, but its complexity and time-consuming nature …
evaluation of hemodynamics in arteries, but its complexity and time-consuming nature …
Mesh U-Nets for 3D cardiac deformation modeling
During a cardiac cycle, the heart anatomy undergoes a series of complex 3D deformations,
which can be analyzed to diagnose various cardiovascular pathologies including …
which can be analyzed to diagnose various cardiovascular pathologies including …
Extrapolation of ventricular activation times from sparse electroanatomical data using graph convolutional neural networks
Electroanatomic mapping is the gold standard for the assessment of ventricular tachycardia.
Acquiring high resolution electroanatomic maps is technically challenging and may require …
Acquiring high resolution electroanatomic maps is technically challenging and may require …
Post-infarction risk prediction with mesh classification networks
Post-myocardial infarction (MI) patients are at risk of major adverse cardiac events (MACE),
with risk stratification primarily based on global image-based biomarkers, such as ejection …
with risk stratification primarily based on global image-based biomarkers, such as ejection …