Generative Modelling of the Ageing Heart with Cross-Sectional Imaging and Clinical Data
Learning correspondences of cardiac motion using biomechanics-informed modeling
Multi-modal Latent-space Self-alignment for Super-resolution Cardiac MR Segmentation
Towards real-time optimization of left atrial appendage occlusion device placement through physics-informed neural networks
Haemodynamic changes in the fetal circulation after connection to an artificial placenta: a computational modelling study
Personalized Fast Electrophysiology Simulations to Evaluate Arrhythmogenicity of Ventricular Slow Conduction Channels
Self-supervised motion descriptor for cardiac phase detection in 4D CMR based on discrete vector field estimations
Going Off-Grid: Continuous Implicit Neural Representations for 3D Vascular Modeling
Comparison of Semi- and Un-supervised Domain Adaptation Methods for Whole-Heart Segmentation
Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance Imaging
An Atlas-Based Analysis of Biventricular Mechanics in Tetralogy of Fallot
Review of data types and model dimensionality for cardiac DTI SMS-related artefact removal
Improving Echocardiography Segmentation by Polar Transformation
Spatiotemporal Cardiac Statistical Shape Modeling: A Data-Driven Approach
Interpretable Prediction of Post-Infarct Ventricular Arrhythmia using Graph Convolutional Network
Unsupervised Echocardiography Registration through Patch-based MLPs and Transformers
Sensitivity analysis of left atrial wall modeling approaches and inlet/outlet boundary conditions in fluid simulations to predict thrombus formation
APHYN-EP: Physics-based deep learning framework to learn and forecast cardiac electrophysiology dynamics
Unsupervised machine-learning exploration of morphological and haemodynamic indices to predict thrombus formation at the left atrial appendage
Geometrical deep learning for the estimation of residence time in the left atria
Explainable Electrocardiogram Analysis with Wave Decomposition: Application to Myocardial Infarction Detection
A systematic study of race and sex bias in CNN-based cardiac MR segmentation
Mesh U-Nets for 3D Cardiac Deformation Modeling
Skeletal model-based analysis of the tricuspid valve in hypoplastic left heart syndrome
Simplifying Disease Staging Models into a Single Anatomical Axis A Case Study of Aortic Coarctation In-utero
Point2Mesh-Net: Combining Point Cloud and Mesh-Based Deep Learning for Cardiac Shape Reconstruction
Post-Infarction Risk Prediction with Mesh Classification Networks
Statistical Shape Modeling of Biventricular Anatomy with Shared Boundaries
Computerized Analysis of the Human Heart to Guide Targeted Treatment of Atrial Fibrillation
3D Mitral Valve Surface Reconstruction from 3D TEE via Graph Neural Networks
Efficient MRI Reconstruction with Reinforcement Learning for Automatic Acquisition Stopping
Unsupervised Cardiac Segmentation Utilizing Synthesized Images from Anatomical Labels
PAT-CNN: Automatic Segmentation and Quantification of Pericardial Adipose Tissue from T2-Weighted Cardiac Magnetic Resonance Images
Deep Computational Model for the Inference of Ventricular Activation Properties
Semi-Supervised Domain Generalization for Cardiac Magnetic Resonance Image Segmentation with High Quality Pseudo Labels
Cardiac Segmentation using Transfer Learning under Respiratory Motion Artifacts
Deep Learning Based Classification and Segmentation for Cardiac Magnetic Resonance Imaging with Respiratory Motion Artifacts
Multi-task Swin Transformer for Motion Artifacts Classification and Cardiac Magnetic Resonance Image Segmentation
Automatic Quality Assessment of Cardiac MR Images with Motion Artefacts using Multi-task Learning and K-Space Motion Artefact Augmentation
Motion-related Artefact Classification Using Patch-based Ensemble and Transfer Learning in Cardiac MRI
Automatic Image Quality Assessment and Cardiac Segmentation Based on CMR Images
Detecting respiratory motion artefacts for cardiovascular MRIs to ensure high-quality segmentation
3D MRI cardiac segmentation under respiratory motion artifacts
Cardiac MR Image Segmentation and Quality Control in the Presence of Respiratory Motion Artifact using Simulated Data
Combination Special Data Augmentation and Sampling Inspection Network for Cardiac Magnetic Resonance Imaging Quality Classification
Automatic Cardiac Magnetic Resonance Respiratory Motions Assessment and Segmentation
Robust Cardiac MRI Segmentation with Data-Centric Models to Improve Performance via Intensive Pre-training and Augmentation
A deep learning-based fully automatic framework for motion-existing cine image quality control and quantitative analysis.