Image Processing, Computer Vision, Pattern Recognition, and Graphics

Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning

Second MICCAI Workshop, DART 2020, and First MICCAI Workshop, DCL 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings

Editors: Albarqouni, S., Bakas, S., Kamnitsas, K., Cardoso, M.J., Landman, B., Li, W., Milletari, F., Rieke, N., Roth, H., Xu, D., Xu, Z. (Eds.)

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About this book

This book constitutes the refereed proceedings of the Second MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2020, and the First MICCAI Workshop on Distributed and Collaborative Learning, DCL 2020, held in conjunction with MICCAI 2020 in October 2020. The conference was planned to take place in Lima, Peru, but changed to an online format due to the Coronavirus pandemic. 

For DART 2020, 12 full papers were accepted from 18 submissions. They deal with methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical settings by making them robust and consistent across different domains.

For DCL 2020, the 8 papers included in this book were accepted from a total of 12 submissions. They focus on the comparison, evaluation and discussion of methodological advancement and practical ideas about machine learning applied to problems where data cannot be stored in centralized databases; where information privacy is a priority; where it is necessary to deliver strong guarantees on the amount and nature of private information that may be revealed by the model as a result of training; and where it's necessary to orchestrate, manage and direct clusters of nodes participating in the same learning task.



Table of contents (20 chapters)

Table of contents (20 chapters)
  • $$\alpha $$-UNet++: A Data-Driven Neural Network Architecture for Medical Image Segmentation

    Pages 3-12

    Chen, Yaxin (et al.)

  • DAPR-Net: Domain Adaptive Predicting-Refinement Network for Retinal Vessel Segmentation

    Pages 13-22

    Huang, Zichun (et al.)

  • Augmented Radiology: Patient-Wise Feature Transfer Model for Glioma Grading

    Pages 23-30

    Li, Zisheng (et al.)

  • Attention-Guided Deep Domain Adaptation for Brain Dementia Identification with Multi-site Neuroimaging Data

    Pages 31-40

    Guan, Hao (et al.)

  • Registration of Histopathology Images Using Self Supervised Fine Grained Feature Maps

    Pages 41-51

    Tong, James (et al.)

Buy this book

eBook $54.99
price for Brazil
  • ISBN 978-3-030-60548-3
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • Immediate eBook download after purchase and usable on all devices
  • Bulk discounts available
Softcover $69.99
price for Brazil
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Bibliographic Information

Bibliographic Information
Book Title
Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning
Book Subtitle
Second MICCAI Workshop, DART 2020, and First MICCAI Workshop, DCL 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings
Editors
  • Shadi Albarqouni
  • Spyridon Bakas
  • Konstantinos Kamnitsas
  • M. Jorge Cardoso
  • Bennett Landman
  • Wenqi Li
  • Fausto Milletari
  • Nicola Rieke
  • Holger Roth
  • Daguang Xu
  • Ziyue Xu
Series Title
Image Processing, Computer Vision, Pattern Recognition, and Graphics
Series Volume
12444
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-60548-3
DOI
10.1007/978-3-030-60548-3
Softcover ISBN
978-3-030-60547-6
Edition Number
1
Number of Pages
XIII, 212
Number of Illustrations
19 b/w illustrations, 67 illustrations in colour
Topics