Table of Contents

• Generative Modelling of the Ageing Heart with Cross-Sectional Imaging and Clinical DataMengyun Qiao, Berke Doga Basaran, Huaqi Qiu, Shuo Wang, Yi Guo 0002, Yuanyuan Wang 0001, Paul M. Matthews, Daniel Rueckert, Wenjia Bai. 3-12 [doi]
• Multi-modal Latent-Space Self-alignment for Super-Resolution Cardiac MR SegmentationYu Deng, Yang Wen, Linglong Qian, Esther Puyol-Antón, Hao Xu, Kuberan Pushparajah, Zina M. Ibrahim, Richard J. B. Dobson, Alistair A. Young. 26-35 [doi]
• Towards Real-Time Optimization of Left Atrial Appendage Occlusion Device Placement Through Physics-Informed Neural NetworksXabier Morales, Carlos Albors, Jordi Mill, Oscar Camara. 36-45 [doi]
• Haemodynamic Changes in the Fetal Circulation Post-connection to an Artificial Placenta: A Computational Modelling StudyMaria Inmaculada Villanueva, Marc López, Sergio Sánchez, Patricia Garcia-Canadilla, Paula C. Randanne, Ameth Hawkins, Elisenda Eixarch, Elisenda Bonet-Carne, Eduard Gratacós, Fátima Crispi, Bart H. Bijnens, Gabriel Bernardino. 46-55 [doi]
• Personalized Fast Electrophysiology Simulations to Evaluate Arrhythmogenicity of Ventricular Slow Conduction ChannelsDolors Serra, Paula Franco, Pau Romero, Ignacio García-Fernández, Miguel Lozano, David Soto, Diego Penela, Antonio Berruezo, Oscar Camara, Rafael Sebastián. 56-64 [doi]
• Self-supervised Motion Descriptor for Cardiac Phase Detection in 4D CMR Based on Discrete Vector Field EstimationsSven Koehler, Tarique Hussain, Hamza Hussain, Daniel Young, Samir Sarikouch, Thomas Pickardt, Gerald Greil, Sandy Engelhardt. 65-78 [doi]
• Going Off-Grid: Continuous Implicit Neural Representations for 3D Vascular ModelingDieuwertje Alblas, Christoph Brune, Kak Khee Yeung, Jelmer M. Wolterink. 79-90 [doi]
• Comparison of Semi- and Un-Supervised Domain Adaptation Methods for Whole-Heart SegmentationMarica Muffoletto, Hao Xu, Hugo Barbaroux, Karl P. Kunze, Radhouène Neji, René M. Botnar, Claudia Prieto, Daniel Rueckert, Alistair A. Young. 91-100 [doi]
• Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance ImagingEmily Chan, Ciaran O'Hanlon, Carlota Asegurado Marquez, Marwenie Petalcorin, Jorge Mariscal Harana, Haotian Gu, Raymond J. Kim, Robert M. Judd, Philip J. Chowienczyk, Julia A. Schnabel, Reza Razavi, Andrew P. King, Bram Ruijsink, Esther Puyol-Antón. 101-111 [doi]
• An Atlas-Based Analysis of Biventricular Mechanics in Tetralogy of FallotSachin Govil, Sanjeet Hegde, James C. Perry, Jeffrey H. Omens, Andrew D. McCulloch. 112-122 [doi]
• Review of Data Types and Model Dimensionality for Cardiac DTI SMS-Related Artefact RemovalMichael Tänzer, Sea Hee Yook, Pedro Ferreira, Guang Yang 0006, Daniel Rueckert, Sonia Nielles-Vallespin. 123-132 [doi]
• Improving Echocardiography Segmentation by Polar TransformationZishun Feng, Joseph A. Sivak, Ashok K. Krishnamurthy. 133-142 [doi]
• Spatiotemporal Cardiac Statistical Shape Modeling: A Data-Driven ApproachJadie Adams, Nawazish Khan, Alan Morris, Shireen Y. Elhabian. 143-156 [doi]
• Interpretable Prediction of Post-Infarct Ventricular Arrhythmia Using Graph Convolutional NetworkBuntheng Ly, Sonny Finsterbach, Marta Nuñez Garcia, Pierre Jaïs, Damien Garreau, Hubert Cochet, Maxime Sermesant. 157-167 [doi]
• Unsupervised Echocardiography Registration Through Patch-Based MLPs and TransformersZihao Wang, Yingyu Yang, Maxime Sermesant, Hervé Delingette. 168-178 [doi]
• Sensitivity Analysis of Left Atrial Wall Modeling Approaches and Inlet/Outlet Boundary Conditions in Fluid Simulations to Predict Thrombus FormationCarlos Albors, Jordi Mill, Henrik A. Kjeldsberg, David Vilades Medel, Andy L. Olivares, Kristian Valen-Sendstad, Oscar Camara. 179-189 [doi]
• APHYN-EP: Physics-Based Deep Learning Framework to Learn and Forecast Cardiac Electrophysiology DynamicsVictoriya Kashtanova, Mihaela Pop, Ibrahim Ayed, Patrick Gallinari, Maxime Sermesant. 190-199 [doi]
• Unsupervised Machine Learning Exploration of Morphological and Haemodynamic Indices to Predict Thrombus Formation in the Left Atrial AppendageMarta Saiz-Vivó, Jordi Mill, Josquin Harrison, Guillermo Jiménez-Pérez, Benoit Legghe, Xavier Iriart, Hubert Cochet, Gemma Piella, Maxime Sermesant, Oscar Camara. 200-210 [doi]
• Geometrical Deep Learning for the Estimation of Residence Time in the Left AtriaDaniel Cañadas Gómez, Xabier Morales Ferez, Oscar Camara-Rey. 211-220 [doi]
• Explainable Electrocardiogram Analysis with Wave Decomposition: Application to Myocardial Infarction DetectionYingyu Yang, Marie Rocher, Pamela Moceri, Maxime Sermesant. 221-232 [doi]
• A Systematic Study of Race and Sex Bias in CNN-Based Cardiac MR SegmentationTiarna Lee, Esther Puyol-Antón, Bram Ruijsink, Miaojing Shi, Andrew P. King. 233-244 [doi]
• Mesh U-Nets for 3D Cardiac Deformation ModelingMarcel Beetz, Jorge Corral Acero, Abhirup Banerjee, Ingo Eitel, Ernesto Zacur, Torben Lange, Thomas Stiermaier, Ruben Evertz, Sören J. Backhaus, Holger Thiele, Alfonso Bueno-Orovio, Pablo Lamata, Andreas Schuster, Vicente Grau. 245-257 [doi]
• Skeletal Model-Based Analysis of the Tricuspid Valve in Hypoplastic Left Heart SyndromeJared Vicory, Christian Herz, Ye Han, David Allemang, Maura Flynn, Alana Cianciulli, Hannah H. Nam, Patricia Sabin, Andras Lasso, Matthew A. Jolley, Beatriz Paniagua. 258-268 [doi]
• Simplifying Disease Staging Models into a Single Anatomical Axis - A Case Study of Aortic Coarctation In-uteroUxio Hermida, Milou van Poppel, David Stojanovski, David F. A. Lloyd, Johannes Steinweg, Trisha V. Vigneswaran, John M. Simpson, Reza Razavi, Adelaide de Vecchi, Kuberan Pushparajah, Pablo Lamata. 269-279 [doi]
• Point2Mesh-Net: Combining Point Cloud and Mesh-Based Deep Learning for Cardiac Shape ReconstructionMarcel Beetz, Abhirup Banerjee, Vicente Grau. 280-290 [doi]
• Post-Infarction Risk Prediction with Mesh Classification NetworksMarcel Beetz, Jorge Corral Acero, Abhirup Banerjee, Ingo Eitel, Ernesto Zacur, Torben Lange, Thomas Stiermaier, Ruben Evertz, Sören J. Backhaus, Holger Thiele, Alfonso Bueno-Orovio, Pablo Lamata, Andreas Schuster, Vicente Grau. 291-301 [doi]
• Statistical Shape Modeling of Biventricular Anatomy with Shared BoundariesKrithika Iyer, Alan Morris, Brian Zenger, Karthik Karanth, Benjamin A. Orkild, Oleksandre Korshak, Shireen Y. Elhabian. 302-316 [doi]
• Computerized Analysis of the Human Heart to Guide Targeted Treatment of Atrial FibrillationRoshan Sharma, Andy Lo, Zhaohan Xiong, Xiaoxiao Zhuang, James Kennelly, Anuradha Kulathilaka, Marta Nuñez Garcia, Vadim V. Fedorov, Martin K. Stiles, Mark L. Trew, Christopher P. Bradley, Jichao Zhao. 317-329 [doi]
• 3D Mitral Valve Surface Reconstruction from 3D TEE via Graph Neural NetworksMatthias Ivantsits, Boris Pfahringer, Markus Hüllebrand, Lars Walczak, Lennart Tautz, Olena Nemchyna, Serdar Akansel, Jörg Kempfert, Simon H. Sündermann, Anja Hennemuth. 330-339 [doi]
• Efficient MRI Reconstruction with Reinforcement Learning for Automatic Acquisition StoppingRuru Xu, Ilkay Öksüz. 340-348 [doi]
• Unsupervised Cardiac Segmentation Utilizing Synthesized Images from Anatomical LabelsSihan Wang, Fuping Wu, Lei Li 0020, Zheyao Gao, Byung-Woo Hong, Xiahai Zhuang. 349-358 [doi]
• PAT-CNN: Automatic Segmentation and Quantification of Pericardial Adipose Tissue from T2-Weighted Cardiac Magnetic Resonance ImagesZhuoyu Li, Camille Petri, James Howard, Graham Cole, Marta Varela. 359-368 [doi]
• Deep Computational Model for the Inference of Ventricular Activation PropertiesLei Li 0020, Julià Camps, Abhirup Banerjee, Marcel Beetz, Blanca Rodríguez, Vicente Grau. 369-380 [doi]
• Semi-supervised Domain Generalization for Cardiac Magnetic Resonance Image Segmentation with High Quality Pseudo LabelsWanqin Ma, Huifeng Yao, Yiqun Lin, Jiarong Guo, Xiaomeng Li 0001. 383-391 [doi]
• Cardiac Segmentation Using Transfer Learning Under Respiratory Motion ArtifactsCarles García-Cabrera, Eric Arazo, Kathleen M. Curran, Noel E. O'Connor, Kevin McGuinness. 392-398 [doi]
• Deep Learning Based Classification and Segmentation for Cardiac Magnetic Resonance Imaging with Respiratory Motion ArtifactsAlejandro Mora-Rubio, Michelle Noga, Kumaradevan Punithakumar. 399-408 [doi]
• Multi-task Swin Transformer for Motion Artifacts Classification and Cardiac Magnetic Resonance Image SegmentationMichal K. Grzeszczyk, Szymon Plotka, Arkadiusz Sitek. 409-417 [doi]
• Automatic Quality Assessment of Cardiac MR Images with Motion Artefacts Using Multi-task Learning and K-Space Motion Artefact AugmentationTewodros Weldebirhan Arega, Stéphanie Bricq, Fabrice Mériaudeau. 418-428 [doi]
• Motion-Related Artefact Classification Using Patch-Based Ensemble and Transfer Learning in Cardiac MRIRuizhe Li, Xin Chen. 429-438 [doi]
• Automatic Image Quality Assessment and Cardiac Segmentation Based on CMR ImagesHaixia Li, Shanshan Jiang, Song Tian, Xiuzheng Yue, Weibo Chen, Yihui Fan. 439-446 [doi]
• Detecting Respiratory Motion Artefacts for Cardiovascular MRIs to Ensure High-Quality SegmentationAmin Ranem, John Kalkhof, Caner Özer, Anirban Mukhopadhyay 0003, Ilkay Öksüz. 447-456 [doi]
• 3D MRI Cardiac Segmentation Under Respiratory Motion ArtifactsYongqing Kou, Rongjun Ge, Daoqiang Zhang. 457-465 [doi]
• Combination Special Data Augmentation and Sampling Inspection Network for Cardiac Magnetic Resonance Imaging Quality ClassificationXiaowu Sun, Li-Hsin Cheng, Rob J. van der Geest. 476-484 [doi]
• Automatic Cardiac Magnetic Resonance Respiratory Motions Assessment and SegmentationAbdul Qayyum, Moona Mazher, Steven A. Niederer, Fabrice Mériaudeau, Imran Razzak. 485-493 [doi]
• Robust Cardiac MRI Segmentation with Data-Centric Models to Improve Performance via Intensive Pre-training and AugmentationShizhan Gong, Weitao Lu, Jize Xie, Xiaofan Zhang, Shaoting Zhang, Qi Dou 0001. 494-504 [doi]
• A Deep Learning-Based Fully Automatic Framework for Motion-Existing Cine Image Quality Control and Quantitative AnalysisHuili Yang, Lexiaozi Fan, Nikolay Iakovlev, Daniel Kim. 505-512 [doi]