A bi-ventricular cardiac atlas built from 1000+ high resolution MR images of healthy subjects and an analysis of shape and motion

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Learning a Probabilistic Model for Diffeomorphic Registration

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Machine Learning of Three-dimensional Right Ventricular Motion Enables Outcome Prediction in Pulmonary Hypertension: A Cardiac MR Imaging Study

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Genetic and functional insights into the fractal structure of the heart

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Toward a Common Coordinate Framework for the Human Body

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Statistical Shape Modeling of the Left Ventricle: Myocardial Infarct Classification Challenge

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Right ventricular shape and function: cardiovascular magnetic resonance reference morphology and biventricular risk factor morphometrics in UK Biobank

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Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling

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Stratified Decision Forests for Accurate Anatomical Landmark Localization in Cardiac Images

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A completely automated pipeline for 3D reconstruction of human heart from 2D cine magnetic resonance slices

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Super-Resolution of Cardiac MR Cine Imaging using Conditional GANs and Unsupervised Transfer Learning

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A bi-atrial statistical shape model for large-scale in silico studies of human atria: Model development and application to ECG simulations

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Polygonal surface processing and mesh generation tools for the numerical simulation of the cardiac function

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Radiomics Signatures of Cardiovascular Risk Factors in Cardiac MRI: Results From the UK Biobank

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Myocardial Radiomics in Cardiac MRI

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A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI

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Model-Based Generation of Large Databases of Cardiac Images: Synthesis of Pathological Cine MR Sequences From Real Healthy Cases

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Semi-supervised generative adversarial networks for the segmentation of the left ventricle in pediatric MRI

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Uncertainty quantification and sensitivity analysis of left ventricular function during the full cardiac cycle

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Comparison of novel ventricular pacing strategies using an electro-mechanical simulation platform

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Automated Detection of Motion Artefacts in MR Imaging Using Decision Forests

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Independent Left Ventricular Morphometric Atlases Show Consistent Relationships with Cardiovascular Risk Factors: A UK Biobank Study

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Atlas-ISTN: Joint segmentation, registration and atlas construction with image-and-spatial transformer networks

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Multi-Domain Variational Autoencoders for Combined Modeling of MRI-Based Biventricular Anatomy and ECG-Based Cardiac Electrophysiology

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A framework for combining a motion atlas with non-motion information to learn clinically useful biomarkers: Application to cardiac resynchronisation therapy response prediction

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Regional Multi-View Learning for Cardiac Motion Analysis: Application to Identification of Dilated Cardiomyopathy Patients

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Cobiveco: Consistent biventricular coordinates for precise and intuitive description of position in the heart – with MATLAB implementation

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Surface Mesh Reconstruction from Cardiac MRI Contours

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Artificial Intelligence in Cardiac Imaging With Statistical Atlases of Cardiac Anatomy

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Three-dimensional cardiovascular imaging-genetics: a mass univariate framework

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Multi-class point cloud completion networks for 3D cardiac anatomy reconstruction from cine magnetic resonance images

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Uncertainty in cardiac myofiber orientation and stiffnesses dominate the variability of left ventricle deformation response

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Fractal Analysis of Right Ventricular Trabeculae in Pulmonary Hypertension

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Relationship between body composition and left ventricular geometry using three dimensional cardiovascular magnetic resonance

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DeepMesh: Mesh-Based Cardiac Motion Tracking Using Deep Learning

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A multimodal spatiotemporal cardiac motion atlas from MR and ultrasound data

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Interpretable cardiac anatomy modeling using variational mesh autoencoders

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A deep learning approach for fully automated cardiac shape modeling in tetralogy of Fallot

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Survey of methods and principles in three-dimensional reconstruction from two-dimensional medical images

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Variational autoencoders for 3D data processing

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CT-Based Analysis of Left Ventricular Hemodynamics Using Statistical Shape Modeling and Computational Fluid Dynamics

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Machine Learning Approaches for Myocardial Motion and Deformation Analysis

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Computer Modeling of the Heart for ECG Interpretation—A Review

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Artificial Intelligence for Cardiac Imaging-Genetics Research

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Biventricular Surface Reconstruction From Cine Mri Contours Using Point Completion Networks

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Rapid inference of personalised left-ventricular meshes by deformation-based differentiable mesh voxelization

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3D High-Resolution Cardiac Segmentation Reconstruction From 2D Views Using Conditional Variational Autoencoders

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Fully Automated Segmentation-Based Respiratory Motion Correction of Multiplanar Cardiac Magnetic Resonance Images for Large-Scale Datasets

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Sex-Dependent QRS Guidelines for Cardiac Resynchronization Therapy Using Computer Model Predictions

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Generating Subpopulation-Specific Biventricular Anatomy Models Using Conditional Point Cloud Variational Autoencoders

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Metabolic pathways associated with right ventricular adaptation to pulmonary hypertension: 3D analysis of cardiac magnetic resonance imaging

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Effects of left ventricle wall thickness uncertainties on cardiac mechanics

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Investigating the Effects of Demographics on Shoulder Morphology and Density Using Statistical Shape and Density Modeling

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Atlas Based Computational Analysis of Heart Shape and Function in Congenital Heart Disease

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Simulator-generated training datasets as an alternative to using patient data for machine learning: An example in myocardial segmentation with MRI

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A personalized time-resolved 3D mesh generative model for unveiling normal heart dynamics

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A statistical shape model of the left ventricle from real-time 3D echocardiography and its application to myocardial segmentation of cardiac magnetic resonance images

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Cardiac left ventricular volumes prediction method based on atlas location and deep learning

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Ventricle Surface Reconstruction from Cardiac MR Slices Using Deep Learning

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Statistical Shape Models of the Heart: Applications to Cardiac Imaging

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Non-invasive localization of the ventricular excitation origin without patient-specific geometries using deep learning

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Reconstruction and completion of high-resolution 3D cardiac shapes using anisotropic CMRI segmentations and continuous implicit neural representations

Sander, J., de Vos, B. D., Bruns, S., Planken, R. N., Viergever, M. A., Leiner, T., & Išgum, I. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.107266 · Cited by 16

Motion correction and super-resolution for multi-slice cardiac magnetic resonance imaging via an end-to-end deep learning approach

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Advances in Genomic Discovery and Implications for Personalized Prevention and Medicine: Estonia as Example

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A probabilistic deep motion model for unsupervised cardiac shape anomaly assessment

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Deep learning in 3D cardiac reconstruction: a systematic review of methodologies and dataset

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Sex and regional differences in myocardial plasticity in aortic stenosis are revealed by 3D model machine learning

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Point2Mesh-Net: Combining Point Cloud and Mesh-Based Deep Learning for Cardiac Shape Reconstruction

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MRXCAT2.0: Synthesis of realistic numerical phantoms by combining left-ventricular shape learning, biophysical simulations and tissue texture generation

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4D Myocardium Reconstruction with Decoupled Motion and Shape Model

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Artificial Intelligence–Based Feature Analysis of Pulmonary Vein Morphology on Computed Tomography Scans and Risk of Atrial Fibrillation Recurrence After Catheter Ablation: A Multi-Site Study

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Segmentation of the left ventricular endocardium from magnetic resonance images by using different statistical shape models

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Predicting one-year left ventricular mass index regression following transcatheter aortic valve replacement in patients with severe aortic stenosis: A new era is coming

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