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Paperback. Condition: new. Paperback. This Open Access book constitutes the refereed proceedings of the First MICCAI Challenge, HNTSMRG 2024, Held in Conjunction with MICCAI 2024, in Marrakesh, Morocco, on October 17, 2024.The 20 full papers and 1 overview paper included in this volume were carefully reviewed and selected from a total of 21 submissions.The HNTS-MRG 2024 Challenge focuses on advancing clinical workflows by leveraging artificial intelligence (AI) for automated segmentation of tumor regions in multi-timepoint MRI scans. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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ISBN 10: 3031832736 ISBN 13: 9783031832734
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ISBN 10: 3031832736 ISBN 13: 9783031832734
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This Open Access book constitutes the refereed proceedings of the First MICCAI Challenge, HNTSMRG 2024, Held in Conjunction with MICCAI 2024, in Marrakesh, Morocco, on October 17, 2024.The 20 full papers and 1 overview paper included in this volume were carefully reviewed and selected from a total of 21 submissions.The HNTS-MRG 2024 Challenge focuses on advancing clinical workflows by leveraging artificial intelligence (AI) for automated segmentation of tumor regions in multi-timepoint MRI scans.
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ISBN 10: 3031274199 ISBN 13: 9783031274190
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Taschenbuch. Condition: Neu. Head and Neck Tumor Segmentation for MR-Guided Applications | First MICCAI Challenge, HNTS-MRG 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 17, 2024, Proceedings | Kareem A. Wahid (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xi | Englisch | 2025 | Springer | EAN 9783031832734 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Published by Springer International Publishing, 2021
ISBN 10: 3030671933 ISBN 13: 9783030671938
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the First 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2020, which was held in conjunction with the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The challenge took place virtually due to the COVID-19 pandemic.The 2 full and 8 short papers presented together with an overview paper in this volume were carefully reviewed and selected form numerous submissions. This challenge aims to evaluate and compare the current state-of-the-art methods for automatic head and neck tumor segmentation. In the context of this challenge, a dataset of 204 delineated PET/CT images was made available for training as well as 53 PET/CT images for testing. Various deep learning methods were developed by the participants with excellent results.