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 | ISBN 9783031234439

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

herausgegeben von Oscar Camara und weiteren
Mitwirkende
Herausgegeben vonOscar Camara
Herausgegeben vonEsther Puyol-Antón
Herausgegeben vonChen Qin
Herausgegeben vonMaxime Sermesant
Herausgegeben vonAvan Suinesiaputra
Herausgegeben vonShuo Wang
Herausgegeben vonAlistair Young
Buchcover Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers  | EAN 9783031234439 | ISBN 3-031-23443-X | ISBN 978-3-031-23443-9

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

herausgegeben von Oscar Camara und weiteren
Mitwirkende
Herausgegeben vonOscar Camara
Herausgegeben vonEsther Puyol-Antón
Herausgegeben vonChen Qin
Herausgegeben vonMaxime Sermesant
Herausgegeben vonAvan Suinesiaputra
Herausgegeben vonShuo Wang
Herausgegeben vonAlistair Young

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.