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

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.- 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 T