Skip to main content

Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health

Third MICCAI Workshop, DART 2021, and First MICCAI Workshop, FAIR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, Proceedings

  • Conference proceedings
  • © 2021

Access provided by Autonomous University of Puebla

Overview

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12968)

Buy print copy

Softcover Book USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

About this book

This book constitutes the refereed proceedings of the Third MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2021, and the First MICCAI Workshop on Affordable Healthcare and AI for Resource Diverse Global Health, FAIR 2021, held in conjunction with MICCAI 2021, in September/October 2021. The workshops were planned to take place in Strasbourg, France, but were held virtually due to the COVID-19 pandemic.

DART 2021 accepted 13 papers from the 21 submissions received. The workshop aims at creating a discussion forum to compare, evaluate, and discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains.

For FAIR 2021, 10 papers from 17 submissions were accepted for publication. They focus on Image-to-Image Translation particularly for low-dose or low-resolution settings; Model Compactness and Compression; Domain Adaptation and Transfer Learning; Active, Continual and Meta-Learning.

 

 


Similar content being viewed by others

Keywords

Table of contents (23 papers)

  1. Domain Adaptation and Representation Transfer

  2. Affordable AI and Healthcare

Other volumes

  1. Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health

Editors and Affiliations

  • Helmholtz Zentrum München, Neuherberg, Germany

    Shadi Albarqouni

  • King's College London, London, UK

    M. Jorge Cardoso

  • Chinese University of Hong Kong, Hong Kong, Hong Kong

    Qi Dou

  • Imperial College London, London, UK

    Konstantinos Kamnitsas

  • NepAl Applied Mathematics and Informatics Institute for Research (NAAMII), Kathmandu, Nepal

    Bishesh Khanal

  • Istanbul Technical University, Istanbul, Türkiye

    Islem Rekik

  • Nvidia GmbH, München, Germany

    Nicola Rieke

  • Indian Institute of Technology Kharagpur, Kharagpur, India

    Debdoot Sheet

  • University of Edinburgh, Edinburgh, UK

    Sotirios Tsaftaris

  • Nvidia Corporation, Santa Clara, USA

    Daguang Xu, Ziyue Xu

Bibliographic Information

  • Book Title: Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health

  • Book Subtitle: Third MICCAI Workshop, DART 2021, and First MICCAI Workshop, FAIR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, Proceedings

  • Editors: Shadi Albarqouni, M. Jorge Cardoso, Qi Dou, Konstantinos Kamnitsas, Bishesh Khanal, Islem Rekik, Nicola Rieke, Debdoot Sheet, Sotirios Tsaftaris, Daguang Xu, Ziyue Xu

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-030-87722-4

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer Nature Switzerland AG 2021

  • Softcover ISBN: 978-3-030-87721-7Published: 24 September 2021

  • eBook ISBN: 978-3-030-87722-4Published: 23 September 2021

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XV, 264

  • Number of Illustrations: 5 b/w illustrations, 90 illustrations in colour

  • Topics: Image Processing and Computer Vision, Artificial Intelligence, Computational Biology/Bioinformatics, Health Informatics

Publish with us