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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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  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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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.

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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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Other volumes

  1. Information Processing in Medical Imaging

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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