Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating..., Kartoniert / Broschiert
Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning
- 10th Workshop, CLIP 2021, Second Workshop, DCL 2021, First Workshop, LL-COVID19 2021, and First Workshop and Tutorial, PPML 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, Proceedings
(soweit verfügbar beim Lieferanten)
- Herausgeber:
- Cristina Oyarzun Laura, Yufei Chen, Shadi Albarqouni, Spyridon Bakas, Bennett Landman, Nicola Rieke, Holger Roth, Xiaoxiao Li, Daguang Xu, Maria Gabrani, Ender Konukoglu, M. Jorge Cardoso, Michal Guindy, Daniel Rueckert, Alexander Ziller, Dmitrii Usynin, Jonathan Passerat-Palmbach, Michal Rosen-Zvi, Georgios Kaissis, Marius George Linguraru, Raj Shekhar, Stefan Wesarg, Marius Erdt, Klaus Drechsler
- Verlag:
- Springer, 11/2021
- Einband:
- Kartoniert / Broschiert, Paperback
- Sprache:
- Englisch
- ISBN-13:
- 9783030908737
- Artikelnummer:
- 10785924
- Umfang:
- 216 Seiten
- Nummer der Auflage:
- 21001
- Ausgabe:
- 1st edition 2021
- Gewicht:
- 335 g
- Maße:
- 235 x 155 mm
- Stärke:
- 11 mm
- Erscheinungstermin:
- 14.11.2021
- Serie:
- Lecture Notes in Computer Science - Band 12969
- Hinweis
-
Achtung: Artikel ist nicht in deutscher Sprache!
Klappentext
This book constitutes the refereed proceedings of the 10th International Workshop on Clinical Image-Based Procedures, CLIP 2021, Second MICCAI Workshop on Distributed and Collaborative Learning, DCL 2021, First MICCAI Workshop, LL-COVID19, First Secure and Privacy-Preserving Machine Learning for Medical Imaging Workshop and Tutorial, PPML 2021, held in conjunction with MICCAI 2021, in October 2021. The workshops were planned to take place in Strasbourg, France, but were held virtually due to the COVID-19 pandemic. CLIP 2021 accepted 9 papers from the 13 submissions received. It focuses on holistic patient models for personalized healthcare with the goal to bring basic research methods closer to the clinical practice.
For DCL 2021, 4 papers from 7 submissions were accepted for publication. They deal with machine learning applied to problems where data cannot be stored in centralized databases and information privacy is a priority.
LL-COVID19 2021 accepted 2 papers out of 3 submissions dealing with the use of AI models in clinical practice.
And for PPML 2021, 2 papers were accepted from a total of 6 submissions, exploring the use of privacy techniques in the medical imaging community.
