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13th STACOM@MICCAI 2022: Singapore
- Oscar Camara
, Esther Puyol-Antón
Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers - 13th International Workshop, STACOM 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers. Lecture Notes in Computer Science 13593, Springer 2022, ISBN 978-3-031-23442-2
Regular Papers
- Mengyun Qiao, Berke Doga Basaran, Huaqi Qiu, Shuo Wang, Yi Guo, Yuanyuan Wang, Paul M. Matthews, Daniel Rueckert, Wenjia Bai:
Generative Modelling of the Ageing Heart with Cross-Sectional Imaging and Clinical Data. 3-12 - Xiaoran Zhang
Learning Correspondences of Cardiac Motion from Images Using Biomechanics-Informed Modeling. 13-25 - Yu Deng, Yang Wen, Linglong Qian, Esther Puyol-Antón, Hao Xu, Kuberan Pushparajah, Zina M. Ibrahim, Richard J. B. Dobson
Multi-modal Latent-Space Self-alignment for Super-Resolution Cardiac MR Segmentation. 26-35 - Xabier Morales, Carlos Albors, Jordi Mill, Oscar Camara:
Towards Real-Time Optimization of Left Atrial Appendage Occlusion Device Placement Through Physics-Informed Neural Networks. 36-45 - Maria Inmaculada Villanueva, Marc López, Sergio Sánchez, Patricia Garcia-Cañadilla, Paula C. Randanne, Ameth Hawkins, Elisenda Eixarch, Elisenda Bonet-Carne, Eduard Gratacós, Fátima Crispi, Bart H. Bijnens, Gabriel Bernardino
Haemodynamic Changes in the Fetal Circulation Post-connection to an Artificial Placenta: A Computational Modelling Study. 46-55 - Dolors Serra
Personalized Fast Electrophysiology Simulations to Evaluate Arrhythmogenicity of Ventricular Slow Conduction Channels. 56-64 - Sven Koehler
Self-supervised Motion Descriptor for Cardiac Phase Detection in 4D CMR Based on Discrete Vector Field Estimations. 65-78 - Dieuwertje Alblas, Christoph Brune
Going Off-Grid: Continuous Implicit Neural Representations for 3D Vascular Modeling. 79-90 - Marica Muffoletto, Hao Xu, Hugo Barbaroux
Comparison of Semi- and Un-Supervised Domain Adaptation Methods for Whole-Heart Segmentation. 91-100 - Emily 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
Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance Imaging. 101-111 - Sachin Govil, Sanjeet Hegde, James C. Perry, Jeffrey H. Omens, Andrew D. McCulloch:
An Atlas-Based Analysis of Biventricular Mechanics in Tetralogy of Fallot. 112-122 - Michael Tänzer
Review of Data Types and Model Dimensionality for Cardiac DTI SMS-Related Artefact Removal. 123-132 - Zishun Feng, Joseph A. Sivak, Ashok K. Krishnamurthy:
Improving Echocardiography Segmentation by Polar Transformation. 133-142 - Jadie Adams, Nawazish Khan, Alan Morris, Shireen Y. Elhabian:
Spatiotemporal Cardiac Statistical Shape Modeling: A Data-Driven Approach. 143-156 - Buntheng Ly, Sonny Finsterbach, Marta Nuñez Garcia, Pierre Jaïs, Damien Garreau, Hubert Cochet, Maxime Sermesant:
Interpretable Prediction of Post-Infarct Ventricular Arrhythmia Using Graph Convolutional Network. 157-167 - Zihao Wang, Yingyu Yang
Unsupervised Echocardiography Registration Through Patch-Based MLPs and Transformers. 168-178 - Carlos Albors, Jordi Mill, Henrik A. Kjeldsberg, David Vilades Medel, Andy L. Olivares, Kristian Valen-Sendstad, Oscar Camara:
Sensitivity Analysis of Left Atrial Wall Modeling Approaches and Inlet/Outlet Boundary Conditions in Fluid Simulations to Predict Thrombus Formation. 179-189 - Victoriya Kashtanova, Mihaela Pop, Ibrahim Ayed, Patrick Gallinari, Maxime Sermesant:
APHYN-EP: Physics-Based Deep Learning Framework to Learn and Forecast Cardiac Electrophysiology Dynamics. 190-199 - Marta Saiz-Vivó
Unsupervised Machine Learning Exploration of Morphological and Haemodynamic Indices to Predict Thrombus Formation in the Left Atrial Appendage. 200-210 - Daniel Cañadas Gómez, Xabier Morales Ferez, Oscar Camara-Rey:
Geometrical Deep Learning for the Estimation of Residence Time in the Left Atria. 211-220 - Yingyu Yang
Explainable Electrocardiogram Analysis with Wave Decomposition: Application to Myocardial Infarction Detection. 221-232 - Tiarna Lee, Esther Puyol-Antón, Bram Ruijsink, Miaojing Shi, Andrew P. King
A Systematic Study of Race and Sex Bias in CNN-Based Cardiac MR Segmentation. 233-244 - Marcel Beetz, Jorge Corral Acero, Abhirup Banerjee
Mesh U-Nets for 3D Cardiac Deformation Modeling. 245-257 - Jared Vicory, Christian Herz, Ye Han
Skeletal Model-Based Analysis of the Tricuspid Valve in Hypoplastic Left Heart Syndrome. 258-268 - Uxio Hermida
Simplifying Disease Staging Models into a Single Anatomical Axis - A Case Study of Aortic Coarctation In-utero. 269-279 - Marcel Beetz, Abhirup Banerjee
Point2Mesh-Net: Combining Point Cloud and Mesh-Based Deep Learning for Cardiac Shape Reconstruction. 280-290 - Marcel Beetz, Jorge Corral Acero, Abhirup Banerjee
Post-Infarction Risk Prediction with Mesh Classification Networks. 291-301 - Krithika Iyer, Alan Morris, Brian Zenger, Karthik Karanth, Benjamin A. Orkild, Oleksandre Korshak, Shireen Y. Elhabian:
Statistical Shape Modeling of Biventricular Anatomy with Shared Boundaries. 302-316 - Roshan Sharma, Andy Lo, Zhaohan Xiong, Xiaoxiao Zhuang, James Kennelly, Anuradha Kulathilaka, Marta Nuñez Garcia, Vadim V. Fedorov, Martin K. Stiles
Computerized Analysis of the Human Heart to Guide Targeted Treatment of Atrial Fibrillation. 317-329 - Matthias Ivantsits
3D Mitral Valve Surface Reconstruction from 3D TEE via Graph Neural Networks. 330-339 - Ruru Xu, Ilkay Öksüz:
Efficient MRI Reconstruction with Reinforcement Learning for Automatic Acquisition Stopping. 340-348 - Sihan Wang, Fuping Wu, Lei Li, Zheyao Gao, Byung-Woo Hong, Xiahai Zhuang:
Unsupervised Cardiac Segmentation Utilizing Synthesized Images from Anatomical Labels. 349-358 - Zhuoyu Li, Camille Petri, James Howard, Graham Cole, Marta Varela
PAT-CNN: Automatic Segmentation and Quantification of Pericardial Adipose Tissue from T2-Weighted Cardiac Magnetic Resonance Images. 359-368 - Lei Li
Deep Computational Model for the Inference of Ventricular Activation Properties. 369-380
CMRxMotion Challenge Papers
- Wanqin Ma, Huifeng Yao, Yiqun Lin, Jiarong Guo, Xiaomeng Li:
Semi-supervised Domain Generalization for Cardiac Magnetic Resonance Image Segmentation with High Quality Pseudo Labels. 383-391 - Carles García-Cabrera
Cardiac Segmentation Using Transfer Learning Under Respiratory Motion Artifacts. 392-398 - Alejandro Mora-Rubio
Deep Learning Based Classification and Segmentation for Cardiac Magnetic Resonance Imaging with Respiratory Motion Artifacts. 399-408 - Michal K. Grzeszczyk, Szymon Plotka, Arkadiusz Sitek
Multi-task Swin Transformer for Motion Artifacts Classification and Cardiac Magnetic Resonance Image Segmentation. 409-417 - Tewodros Weldebirhan Arega, Stéphanie Bricq, Fabrice Mériaudeau:
Automatic Quality Assessment of Cardiac MR Images with Motion Artefacts Using Multi-task Learning and K-Space Motion Artefact Augmentation. 418-428 - Ruizhe Li
Motion-Related Artefact Classification Using Patch-Based Ensemble and Transfer Learning in Cardiac MRI. 429-438 - Haixia Li, Shanshan Jiang, Song Tian, Xiuzheng Yue, Weibo Chen, Yihui Fan:
Automatic Image Quality Assessment and Cardiac Segmentation Based on CMR Images. 439-446 - Amin Ranem
Detecting Respiratory Motion Artefacts for Cardiovascular MRIs to Ensure High-Quality Segmentation. 447-456 - Yongqing Kou, Rongjun Ge, Daoqiang Zhang:
3D MRI Cardiac Segmentation Under Respiratory Motion Artifacts. 457-465 - Sina Amirrajab
Cardiac MR Image Segmentation and Quality Control in the Presence of Respiratory Motion Artifacts Using Simulated Data. 466-475 - Xiaowu Sun, Li-Hsin Cheng
Combination Special Data Augmentation and Sampling Inspection Network for Cardiac Magnetic Resonance Imaging Quality Classification. 476-484 - Abdul Qayyum, Moona Mazher
Automatic Cardiac Magnetic Resonance Respiratory Motions Assessment and Segmentation. 485-493 - Shizhan Gong, Weitao Lu, Jize Xie, Xiaofan Zhang, Shaoting Zhang, Qi Dou:
Robust Cardiac MRI Segmentation with Data-Centric Models to Improve Performance via Intensive Pre-training and Augmentation. 494-504 - Huili Yang, Lexiaozi Fan, Nikolay Iakovlev, Daniel Kim:
A Deep Learning-Based Fully Automatic Framework for Motion-Existing Cine Image Quality Control and Quantitative Analysis. 505-512
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