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Information Processing in Medical Imaging

27th International Conference, IPMI 2021, Virtual Event, June 28–June 30, 2021, Proceedings

  • Conference proceedings
  • © 2021

Overview

Editors:
  1. Aasa Feragen

    1. Technical University of Denmark, Kgs Lyngby, Denmark

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    You can also search for this editor in PubMed   Google Scholar

  2. Stefan Sommer

    1. University of Copenhagen, Copenhagen, Denmark

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  3. Julia Schnabel

    1. King's College London, London, UK

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  4. Mads Nielsen

    1. University of Copenhagen, Copenhagen, Denmark

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12729)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: IPMI 2021.

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Table of contents (59 papers)

  1. Front Matter

    Pages i-xix
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  2. Registration

    1. Front Matter

      Pages 1-1
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    2. HyperMorph: Amortized Hyperparameter Learning for Image Registration

      • Andrew Hoopes, Malte Hoffmann, Bruce Fischl, John Guttag, Adrian V. Dalca
      Pages 3-17

    3. Deep Learning Based Geometric Registration for Medical Images: How Accurate Can We Get Without Visual Features?

      • Lasse Hansen, Mattias P. Heinrich
      Pages 18-30

    4. Diffeomorphic Registration with Density Changes for the Analysis of Imbalanced Shapes

      • Hsi-Wei Hsieh, Nicolas Charon
      Pages 31-42

  3. Causal Models and Interpretability

    1. Front Matter

      Pages 43-43
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    2. Estimation of Causal Effects in the Presence of Unobserved Confounding in the Alzheimer’s Continuum

      • Sebastian Pölsterl, Christian Wachinger
      Pages 45-57

    3. Multiple-Shooting Adjoint Method for Whole-Brain Dynamic Causal Modeling

      • Juntang Zhuang, Nicha Dvornek, Sekhar Tatikonda, Xenophon Papademetris, Pamela Ventola, James S. Duncan
      Pages 58-70

    4. Going Beyond Saliency Maps: Training Deep Models to Interpret Deep Models

      • Zixuan Liu, Ehsan Adeli, Kilian M. Pohl, Qingyu Zhao
      Pages 71-82

  4. Generative Modelling

    1. Front Matter

      Pages 83-83
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    2. Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training

      • Yunhe Gao, Zhiqiang Tang, Mu Zhou, Dimitris Metaxas
      Pages 85-97

    3. Blind Stain Separation Using Model-Aware Generative Learning and Its Applications on Fluorescence Microscopy Images

      • Xingyu Li
      Pages 98-107

    4. MR Slice Profile Estimation by Learning to Match Internal Patch Distributions

      • Shuo Han, Samuel Remedios, Aaron Carass, Michael Schär, Jerry L. Prince
      Pages 108-119

  5. Shape

    1. Front Matter

      Pages 121-121
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    2. Partial Matching in the Space of Varifolds

      • Pierre-Louis Antonsanti, Joan Glaunès, Thomas Benseghir, Vincent Jugnon, Irène Kaltenmark
      Pages 123-135

    3. Nested Grassmanns for Dimensionality Reduction with Applications to Shape Analysis

      • Chun-Hao Yang, Baba C. Vemuri
      Pages 136-149

    4. Hierarchical Morphology-Guided Tooth Instance Segmentation from CBCT Images

      • Zhiming Cui, Bojun Zhang, Chunfeng Lian, Changjian Li, Lei Yang, Wenping Wang et al.
      Pages 150-162

    5. Cortical Morphometry Analysis Based on Worst Transportation Theory

      • Min Zhang, Dongsheng An, Na Lei, Jianfeng Wu, Tong Zhao, Xiaoyin Xu et al.
      Pages 163-176

    6. Geodesic B-score for Improved Assessment of Knee Osteoarthritis

      • Felix Ambellan, Stefan Zachow, Christoph von Tycowicz
      Pages 177-188

  6. Brain Connectivity

    1. Front Matter

      Pages 189-189
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  1. Information Processing in Medical Imaging

Keywords

About this book

This book constitutes the proceedings of the 27th International Conference on Information Processing in Medical Imaging, IPMI 2021, which was held online during June 28-30, 2021. The conference was originally planned to take place in Bornholm, Denmark, but changed to a virtual format due to the COVID-19 pandemic.

The 59 full papers presented in this volume were carefully reviewed and selected from 200 submissions. They were organized in topical sections as follows: registration; causal models and interpretability; generative modelling; shape; brain connectivity; representation learning; segmentation; sequential modelling; learning with few or low quality labels; uncertainty quantification and generative modelling; and deep learning.

Editors and Affiliations

  • Technical University of Denmark, Kgs Lyngby, Denmark

    Aasa Feragen

  • University of Copenhagen, Copenhagen, Denmark

    Stefan Sommer, Mads Nielsen

  • King's College London, London, UK

    Julia Schnabel

Bibliographic Information

  • Book Title: Information Processing in Medical Imaging

  • Book Subtitle: 27th International Conference, IPMI 2021, Virtual Event, June 28–June 30, 2021, Proceedings

  • Editors: Aasa Feragen, Stefan Sommer, Julia Schnabel, Mads Nielsen

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-030-78191-0

  • Publisher: Springer Cham

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

  • Copyright Information: Springer Nature Switzerland AG 2021

  • Softcover ISBN: 978-3-030-78190-3Published: 21 June 2021

  • eBook ISBN: 978-3-030-78191-0Published: 20 June 2021

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XIX, 782

  • Number of Illustrations: 22 b/w illustrations, 261 illustrations in colour

  • Topics: Image Processing and Computer Vision

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