Statistical Atlases and Computational Models of the Heart. Workshop, CMRxRecon and MBAS Challenge Papers.

.- Single-source Domain Generalization for Coronary Vessels Segmentation in X-ray Angiography. 

.- Constraint-Based Model in Multimodal Learning to Improve Ventricular Arrhythmia Prediction. 

.- Automated estimation of cardiac stroke volumes from computed tomography. 

.- Peridevice leaks following left atrial appendage occlusion - analysis with morphology descriptive centerlines and explainable graph attention network. 

.- Improved 3D Whole Heart Geometry from Sparse CMR Slices. 

.- CavityBASNet: Cavity-focused Biatrial Automatic Segmentation on LGE MRI with augmented input channel and left-right myocardium splitting. 

.- A novel MRI-based electrophysiological computational model of progressive doxorubicin-induced fibrosis in the left ventricle. 

.- Quantitative comparison of blood flow patterns from in silico simulations and 4D flow data before and after left atrial occlusion. 

.- Panoramic anatomical context in 3D intracardiac echocardiography (ICE) with 3D registration and geometry-based image fusion. 

.- Physics-Informed Neural Networks can accurately model cardiac electrophysiology in 3D geometries and fibrillatory conditions. 

.- Beyond the standards: Fully-Automated Aortic Annulus Segmentation on Contrast-free Magnetic Resonance Imaging using a Computational Aorta Unwrapping Method. 

.- Coronary Artery Calcium Scoring from Non-Contrast Cardiac CT Using Deep Learning With External Validation. 

.- Effective approach based on student-teacher self-supervised deep learning for Multi-class Bi-Atrial Segmentation Challenge. 

.- Sampling-Pattern-Agnostic MRI Reconstruction through Adaptive Consistency Enforcement with Diffusion Model. 

.- HyperCMR: Enhanced Multi-Contrast CMR Reconstruction with Eagle Loss. 

.- A Multi-Contrast Cardiac MRI Reconstruction Method Using an Advanced Unrolled Network Architecture. 

.- Implicit Neural Representations for Registration of Left Ventricle Myocardium During a Cardiac Cycle. 

.- Deep Multi-contrast Cardiac MRI Reconstruction via vSHARP with Auxil iary Refinement Network. 

.- Multi-Model Ensemble Approach for Accurate Bi-Atrial Segmentation in LGE-MRI of Atrial Fibrillation Patients. 

.- Two-Stage nnU-Net for Automatic Multi-class Bi-Atrial Segmentation from LGE-MRIs. 

.- An Ensemble of 3D Residual Encoder UNet Models for Solving Multi-Class Bi-Atrial Segmentation Challenge. 

.- Evaluating Convolution, Attention, and Mamba Based U-Net Models for Multi-Class Bi-Atrial Segmentation from LGE-MRI. 

.- On the Foundation Model for Cardiac MRI Reconstruction. 

.- Multi-Loss 3D Segmentation for Enhanced Bi-Atrial Segmentation. 

.- Classification of Mitral Regurgitation from Cardiac Cine MRI using Clinically-Interpretable Morphological Features. 

.- Gaussian Process Emulators for Few-Shot Segmentation in Cardiac MRI. 

.- Global Control for Local SO(3)-Equivariant Scale-Invariant Vessel Segmentation. 

.- A self-distillation bi-atrial segmentation network for Cardiac MRI. 

.- Adaptive Unrolling Applied to the CMRxRecon2024 Callenge. 

.- Reducing the number of leads for ECG Imaging with Graph Neural Networks and meaningful latent space. 

.- Rotor Core Projection Ablation (RCPA): Novel Computational Approach to Catheter Ablation Therapy for Atrial Fibrillation. 

.- Automated pipeline for regional epicardial adipose tissue distribution analysis in the left atrium. 

.- Low-Rank Conjugate Gradient-Net for Accelerated Cardiac MR Imaging. 

.- SBAW-Net: Segmentation of Bi-Atria and Wall Network - Offering Valuable Insights into Challenge Data. 

.- ResNet-based Convolutional Framework for Segmenting Left Atrial Scars and Cavities. 

.- EAT-Mamba: Epicardial Adipose Tissue Segmentation from Multi-modal Dixon MRI. 

.- Neural Fields for Continuous Periodic Motion Estimation in 4D Cardiovascular Imaging. 

.- Exploring CNN and Transformer Architectures for Multi-class Bi-Atrial Segmentation from Late Gadolinium-Enhanced MRI. 

.- EigenBoundaries for the temporally regularized segmentation of echocardiographic images. 

.- Dynamic Cardiac MRI Reconstruction via Separate Optimization of K-space and Hybrid-domian Spatial-temporal Feature Fusion. 

.- an Interpretable Learning of Risk Explain Ventricular Arrhythmia Mechanism. 

.- 3D Left Ventricular Reconstruction from 2D Echocardiograms for Reliable Volume Estimation. 

.- Comparing Left Atrial Spontaneous Echo Contrast Intensity with Gaussian Process Emulator Predictions. 

.- UPCMR: A Universal Prompt-guided Model for Random Sampling Cardiac MRI Reconstruction. 

.- An All-in-one Approach for Accelerated Cardiac MRI Reconstruction. 

.- Improving the Scan-rescan Precision of AI-based CMR Biomarker Estimation.