9783030982522 - head and neck tumor segmentation and outcome prediction: second challenge, hecktor 2021, held in conjunction with miccai 2021, strasbourg, france, ... notes in computer science, band 13209) (4 Ergebnisse)

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the Second 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2021, which was held in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021. T…he challenge took place virtually on September 27, 2021, due to the COVID-19 pandemic.The 29 contributions presented, as well as an overview paper, 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 325 delineated PET/CT images was made available for training.
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Taschenbuch. Zustand: Neu. Head and Neck Tumor Segmentation and Outcome Prediction | Second Challenge, HECKTOR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings | Vincent Andrearczyk (u. a.) | Taschenbuch | Lecture Notes in Computer Science | x | Englisch | 2022 | Springer | EAN 9783…030982522 | 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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Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 340 | Sprache: Englisch | Produktart: Bücher | This book constitutes the Second 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2021, which was held in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Interv…ention, MICCAI 2021. The challenge took place virtually on September 27, 2021, due to the COVID-19 pandemic.The 29 contributions presented, as well as an overview paper, 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 325 delineated PET/CT images was made available for training.