Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers

1. Front Matter

   Pages i-xiv

   PDF

2. Regular Papers

   1. Front Matter

      Pages 1-1

      PDF

   2. Generative Modelling of the Ageing Heart with Cross-Sectional Imaging and Clinical Data

      • Mengyun Qiao, Berke Doga Basaran, Huaqi Qiu, Shuo Wang, Yi Guo, Yuanyuan Wang et al.

      Pages 3-12

   3. Learning Correspondences of Cardiac Motion from Images Using Biomechanics-Informed Modeling

      • Xiaoran Zhang, Chenyu You, Shawn Ahn, Juntang Zhuang, Lawrence Staib, James Duncan

      Pages 13-25

   4. Multi-modal Latent-Space Self-alignment for Super-Resolution Cardiac MR Segmentation

      • Yu Deng, Yang Wen, Linglong Qian, Esther Puyol Anton, Hao Xu, Kuberan Pushparajah et al.

      Pages 26-35

   5. Towards Real-Time Optimization of Left Atrial Appendage Occlusion Device Placement Through Physics-Informed Neural Networks

      • Xabier Morales, Carlos Albors, Jordi Mill, Oscar Camara

      Pages 36-45

   6. Haemodynamic Changes in the Fetal Circulation Post-connection to an Artificial Placenta: A Computational Modelling Study

      • Maria Inmaculada Villanueva, Marc López, Sergio Sánchez, Patricia Garcia-Cañadilla, Paula C. Randanne, Ameth Hawkins et al.

      Pages 46-55

   7. Personalized Fast Electrophysiology Simulations to Evaluate Arrhythmogenicity of Ventricular Slow Conduction Channels

      • Dolors Serra, Paula Franco, Pau Romero, Ignacio García-Fernández, Miguel Lozano, David Soto et al.

      Pages 56-64

   8. Self-supervised Motion Descriptor for Cardiac Phase Detection in 4D CMR Based on Discrete Vector Field Estimations

      • Sven Koehler, Tarique Hussain, Hamza Hussain, Daniel Young, Samir Sarikouch, Thomas Pickardt et al.

      Pages 65-78

   9. Going Off-Grid: Continuous Implicit Neural Representations for 3D Vascular Modeling

      • Dieuwertje Alblas, Christoph Brune, Kak Khee Yeung, Jelmer M. Wolterink

      Pages 79-90

   10. Comparison of Semi- and Un-Supervised Domain Adaptation Methods for Whole-Heart Segmentation

       • Marica Muffoletto, Hao Xu, Hugo Barbaroux, Karl P. Kunze, Radhouene Neji, René Botnar et al.

       Pages 91-100

   11. Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance Imaging

       • Emily Chan, Ciaran O’Hanlon, Carlota Asegurado Marquez, Marwenie Petalcorin, Jorge Mariscal-Harana, Haotian Gu et al.

       Pages 101-111

   12. An Atlas-Based Analysis of Biventricular Mechanics in Tetralogy of Fallot

       • Sachin Govil, Sanjeet Hegde, James C. Perry, Jeffrey H. Omens, Andrew D. McCulloch

       Pages 112-122

   13. Review of Data Types and Model Dimensionality for Cardiac DTI SMS-Related Artefact Removal

       • Michael Tänzer, Sea Hee Yook, Pedro Ferreira, Guang Yang, Daniel Rueckert, Sonia Nielles-Vallespin

       Pages 123-132

   14. Improving Echocardiography Segmentation by Polar Transformation

       • Zishun Feng, Joseph A. Sivak, Ashok K. Krishnamurthy

       Pages 133-142

   15. Spatiotemporal Cardiac Statistical Shape Modeling: A Data-Driven Approach

       • Jadie Adams, Nawazish Khan, Alan Morris, Shireen Elhabian

       Pages 143-156

   16. Interpretable Prediction of Post-Infarct Ventricular Arrhythmia Using Graph Convolutional Network

       • Buntheng Ly, Sonny Finsterbach, Marta Nuñez-Garcia, Pierre Jais, Damien Garreau, Hubert Cochet et al.

       Pages 157-167

   17. Unsupervised Echocardiography Registration Through Patch-Based MLPs and Transformers

       • Zihao Wang, Yingyu Yang, Maxime Sermesant, Hervé Delingette

       Pages 168-178

   18. Sensitivity Analysis of Left Atrial Wall Modeling Approaches and Inlet/Outlet Boundary Conditions in Fluid Simulations to Predict Thrombus Formation

       • Carlos Albors, Jordi Mill, Henrik A. Kjeldsberg, David Viladés Medel, Andy L. Olivares, Kristian Valen-Sendstad et al.

       Pages 179-189

   19. APHYN-EP: Physics-Based Deep Learning Framework to Learn and Forecast Cardiac Electrophysiology Dynamics

       • Victoriya Kashtanova, Mihaela Pop, Ibrahim Ayed, Patrick Gallinari, Maxime Sermesant

       Pages 190-199

This book constitutes the proceedings of the 13th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2022, held in conjunction with the 25th MICCAI conference.

The 34 regular workshop papers included in this volume were carefully reviewed and selected after being revised and deal with topics such as: common cardiac segmentation and modelling problems to more advanced generative modelling for ageing hearts, learning cardiac motion using biomechanical networks, physics-informed neural networks for left atrial appendage occlusion, biventricular mechanics for Tetralogy of Fallot, ventricular arrhythmia prediction by using graph convolutional network, and deeper analysis of racial and sex biases from machine learning-based cardiac segmentation.

In addition, 14 papers from the CMRxMotion challenge are included in the proceedings which aim to assess the effects of respiratory motion on cardiac MRI (CMR) imaging quality and examine the robustness of segmentation models in face of respiratory motion artefacts.

A total of 48 submissions to the workshop was received.

• artificial intelligence
• computer science
• computer systems
• computer vision
• deep learning
• education
• engineering
• image analysis
• image processing
• image quality
• image reconstruction
• image segmentation
• internet
• learning
• machine learning
• mathematics
• neural networks
• pattern recognition
• segmentation methods
• signal processing

• Pompeu Fabra University, Barcelona, Spain

  Oscar Camara

• King’s College London, London, UK

  Esther Puyol-Antón, Avan Suinesiaputra, Alistair Young

• Imperial College London, London, UK

  Chen Qin

• Inria, Sophia Antipolis, France

  Maxime Sermesant

• Fudan University, Shanghai, China

  Shuo Wang

Policies and ethics