[HTML][HTML] Multi-class point cloud completion networks for 3D cardiac anatomy reconstruction from cine magnetic resonance images
M Beetz, A Banerjee, J Ossenberg-Engels… - Medical Image Analysis, 2023 - Elsevier
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 …
cardiac anatomy and function. However, it typically only acquires a set of two-dimensional …
Digital twinning of cardiac electrophysiology models from the surface ECG: a geodesic backpropagation approach
The eikonal equation has become an indispensable tool for modeling cardiac electrical
activation accurately and efficiently. In principle, by matching clinically recorded and eikonal …
activation accurately and efficiently. In principle, by matching clinically recorded and eikonal …
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 …
A conditional flow variational autoencoder for controllable synthesis of virtual populations of anatomy
The generation of virtual populations (VPs) of anatomy is essential for conducting in silico
trials of medical devices. Typically, the generated VP should capture sufficient variability …
trials of medical devices. Typically, the generated VP should capture sufficient variability …
Point2Mesh-Net: Combining point cloud and mesh-based deep learning for cardiac shape reconstruction
Cine magnetic resonance imaging (MRI) is the gold standard modality for the assessment of
cardiac anatomy and function. However, a standard cine acquisition typically consists of only …
cardiac anatomy and function. However, a standard cine acquisition typically consists of only …
3D shape-based myocardial infarction prediction using point cloud classification networks
Myocardial infarction (MI) is one of the most prevalent cardiovascular diseases with
associated clinical decision-making typically based on single-valued imaging biomarkers …
associated clinical decision-making typically based on single-valued imaging biomarkers …
Solving the Inverse Problem of Electrocardiography for Cardiac Digital Twins: A Survey
Cardiac digital twins are personalized virtual representations used to understand complex
heart mechanisms. Solving the ECG inverse problem is crucial for accurate virtual heart …
heart mechanisms. Solving the ECG inverse problem is crucial for accurate virtual heart …
Reconstructing 3D cardiac anatomies from misaligned multi-view magnetic resonance images with mesh deformation U-nets
Abstract High-quality three-dimensional (3D) representations of cardiac anatomy and
function are crucial for improving cardiac disease diagnosis beyond strictly volume-based …
function are crucial for improving cardiac disease diagnosis beyond strictly volume-based …
Influence of myocardial infarction on QRS properties: A simulation study
The interplay between structural and electrical changes in the heart after myocardial
infarction (MI) plays a key role in the initiation and maintenance of arrhythmia. The …
infarction (MI) plays a key role in the initiation and maintenance of arrhythmia. The …
Large Language Model-informed ECG Dual Attention Network for Heart Failure Risk Prediction
Heart failure (HF) poses a significant public health challenge due to its rising global mortality
rate. Addressing this issue through early diagnosis and prevention could significantly reduce …
rate. Addressing this issue through early diagnosis and prevention could significantly reduce …