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Biomedical Image Registration - 10th International Workshop, WBIR 2022, Munich, Germany, July 10-12, 2022, Proceedings... Biomedical Image Registration - 10th International Workshop, WBIR 2022, Munich, Germany, July 10-12, 2022, Proceedings (Paperback, 1st ed. 2022)
Alessa Hering, Julia Schnabel, Miaomiao Zhang, Enzo Ferrante, Mattias Heinrich, …
R2,175 Discovery Miles 21 750 Ships in 10 - 15 working days

This book constitutes the refereed proceedings of the 10th International Workshop on Biomedical Image Registration, WBIR 2020, which was supposed to be held in Munich, Germany, in July 2022.The 11 full and poster papers together with 17 short papers included in this volume were carefully reviewed and selected from 32 submitted papers. The papers are organized in the following topical sections: optimization, deep learning architectures, neuroimaging, diffeomorphisms, uncertainty, topology and metrics.

Biomedical Image Registration, Domain Generalisation and Out-of-Distribution Analysis - MICCAI 2021 Challenges: MIDOG 2021,... Biomedical Image Registration, Domain Generalisation and Out-of-Distribution Analysis - MICCAI 2021 Challenges: MIDOG 2021, MOOD 2021, and Learn2Reg 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27-October 1, 2021, Proceedings (Paperback, 1st ed. 2022)
Marc Aubreville, David Zimmerer, Mattias Heinrich
R1,656 Discovery Miles 16 560 Ships in 10 - 15 working days

This book constitutes three challenges that were held in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, which was planned to take place in Strasbourg, France but changed to an online event due to the COVID-19 pandemic. The peer-reviewed 18 long and 9 short papers included in this volume stem from the following three biomedical image analysis challenges: Mitosis Domain Generalization Challenge (MIDOG 2021), Medical Out-of-Distribution Analysis Challenge (MOOD 2021), and Learn2Reg (L2R 2021). The challenges share the need for developing and fairly evaluating algorithms that increase accuracy, reproducibility and efficiency of automated image analysis in clinically relevant applications.

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