Skip to main content

Medical Image Learning with Limited and Noisy Data

First International Workshop, MILLanD 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings

  • Conference proceedings
  • © 2022

Access provided by Autonomous University of Puebla

Overview

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13559)

Included in the following conference series:

Conference proceedings info: MILLanD 2022.

Buy print copy

Softcover Book USD 54.99
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 proceedings of the First Workshop on Medical Image Learning with Limited and Noisy Data, MILLanD 2022, held in conjunction with MICCAI 2022. The conference was held in Singapore. For this workshop, 22 papers from 54 submissions were accepted for publication. They selected papers focus on the challenges and limitations of current deep learning methods applied to limited and noisy medical data and present new methods for training models using such imperfect data.

Similar content being viewed by others

Keywords

Table of contents (22 papers)

  1. Efficient and Robust Annotation Strategies

  2. Weakly-Supervised, Self-supervised, and Contrastive Learning

  3. Active and Continual Learning

  4. Transfer Representation Learning

Other volumes

  1. Medical Image Learning with Limited and Noisy Data

Editors and Affiliations

  • National Institutes of Health, Bethesda, USA

    Ghada Zamzmi, Sameer Antani, Sivaramakrishnan Rajaraman, Zhiyun Xue

  • Northwestern University, Chicago, USA

    Ulas Bagci

  • Children's National Hospital, Washington, USA

    Marius George Linguraru

Bibliographic Information

  • Book Title: Medical Image Learning with Limited and Noisy Data

  • Book Subtitle: First International Workshop, MILLanD 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings

  • Editors: Ghada Zamzmi, Sameer Antani, Ulas Bagci, Marius George Linguraru, Sivaramakrishnan Rajaraman, Zhiyun Xue

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-16760-7

  • Publisher: Springer Cham

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

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022

  • Softcover ISBN: 978-3-031-16759-1Published: 22 September 2022

  • eBook ISBN: 978-3-031-16760-7Published: 21 September 2022

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XI, 240

  • Number of Illustrations: 6 b/w illustrations, 71 illustrations in colour

  • Topics: Computer Imaging, Vision, Pattern Recognition and Graphics

Publish with us