株式会社極東書店トップ ＞ 商品一覧 ＞ 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. 1st ed. 2022
商品詳細
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. 1st ed. 2022
・ISBN 978-3-030-97280-6 paper EUR 54.99
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| 著者・編者 | Aubreville, Marc / Zimmerer, David / Heinrich, Mattias (eds.), |
|---|---|
| シリーズ | (Lecture Notes in Computer Science) |
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2022 |
| ページ数 | 194 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A01-90368＞ |
解説
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.