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(Ebook) Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers: 14th International Workshop, STACOM 2023 Held in Conjunction with MICCAI 2023 Vancouver, BC, Canada, October 12, 2023 Revised Selected Papers by Oscar Camara, Esther Puyol-Antón, Maxime Sermesant, Avan Suinesiaputra, Qian Tao, (eds.) ISBN 9783031524486, 9783031524479, 3031524489, 3031524470

  • SKU: EBN-56370708
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Instant download (eBook) Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers: 14th International Workshop, STACOM 2023 Held in Conjunction with MICCAI 2023 Vancouver, BC, Canada, October 12, 2023 Revised Selected Papers after payment.
Authors:Oscar Camara, Esther Puyol-Antón, Maxime Sermesant, Avan Suinesiaputra, Qian Tao, (eds.)
Pages:508 pages.
Year:2024
Editon:1
Publisher:Springer
Language:english
File Size:12.62 MB
Format:pdf
ISBNS:9783031524486, 9783031524479, 3031524489, 3031524470
Categories: Ebooks

Product desciption

(Ebook) Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers: 14th International Workshop, STACOM 2023 Held in Conjunction with MICCAI 2023 Vancouver, BC, Canada, October 12, 2023 Revised Selected Papers by Oscar Camara, Esther Puyol-Antón, Maxime Sermesant, Avan Suinesiaputra, Qian Tao, (eds.) ISBN 9783031524486, 9783031524479, 3031524489, 3031524470

​This book constitutes the proceedings of the 14th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2023, as well as the Cardiac MRI Reconstruction Challenge, CMRxRecon Challenge. There was a total of 53 submissions to the workshop. The 24 regular workshop papers included in this volume were carefully reviewed and selected from 29 paper submissions. They deal with cardiac segmentation, modelling, strain quantification, registration, statistical shape analysis, and quality control. In addition, 21 papers from the CMRxRecon challenge are included in this volume. They focus on fast CMR image reconstruction and provide a benchmark dataset that enables the broader research community to promote advances in this area of research.
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