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Biomedical Image Registration

10th International Workshop, WBIR 2022, Munich, Germany, July 10–12, 2022, Proceedings

  • Conference proceedings
  • © 2022

Overview

Editors:
  1. Alessa Hering

    1. Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands

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  2. Julia Schnabel

    1. Helmholtz Center Munich, Neuherberg, Germany

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  3. Miaomiao Zhang

    1. University of Virginia, Charlottesville, USA

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  4. Enzo Ferrante

    1. CONICET, Universidad Nacional del Litoral, Santa Fe, Argentina

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  5. Mattias Heinrich

    1. Universität zu Lübeck, Lübeck, Germany

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  6. Daniel Rueckert

    1. GALILEO, Technical University of Munich, Munich, Germany

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13386)

Included in the following conference series:

Conference proceedings info: WBIR 2022.

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About this book

This book constitutes the refereed proceedings of the 10th International Workshop on Biomedical Image Registration, WBIR 2020, which was supposed to be held in Munich, Germany, in July 2022.

The 11 full and poster papers together with 17 short papers included in this volume were carefully reviewed and selected from 32 submitted papers. The papers are organized in the following topical sections: optimization, deep learning architectures, neuroimaging, diffeomorphisms, uncertainty, topology and metrics.

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Table of contents (26 papers)

  1. Front Matter

    Pages i-xi
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  2. Atlases/Topology

    1. Front Matter

      Pages 1-1
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    2. Unsupervised Non-correspondence Detection in Medical Images Using an Image Registration Convolutional Neural Network

      • Julia Andresen, Timo Kepp, Jan Ehrhardt, Claus von der Burchard, Johann Roider, Heinz Handels
      Pages 3-7

    3. Weighted Metamorphosis for Registration of Images with Different Topologies

      • Anton François, Matthis Maillard, Catherine Oppenheim, Johan Pallud, Isabelle Bloch, Pietro Gori et al.
      Pages 8-17

    4. LDDMM Meets GANs: Generative Adversarial Networks for Diffeomorphic Registration

      • Ubaldo Ramon, Monica Hernandez, Elvira Mayordomo
      Pages 18-28

    5. Towards a 4D Spatio-Temporal Atlas of the Embryonic and Fetal Brain Using a Deep Learning Approach for Groupwise Image Registration

      • Wietske A. P. Bastiaansen, Melek Rousian, Régine P. M. Steegers-Theunissen, Wiro J. Niessen, Anton H. J. Koning, Stefan Klein
      Pages 29-34

  3. Uncertainty

    1. Front Matter

      Pages 35-35
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    2. DeepSTAPLE: Learning to Predict Multimodal Registration Quality for Unsupervised Domain Adaptation

      • Christian Weihsbach, Alexander Bigalke, Christian N. Kruse, Hellena Hempe, Mattias P. Heinrich
      Pages 37-46

    3. A Method for Image Registration via Broken Geodesics

      • Alphin J. Thottupattu, Jayanthi Sivaswamy, Venkateswaran P. Krishnan
      Pages 47-56

    4. Deformable Image Registration Uncertainty Quantification Using Deep Learning for Dose Accumulation in Adaptive Proton Therapy

      • A. Smolders, T. Lomax, D. C. Weber, F. Albertini
      Pages 57-66

    5. Distinct Structural Patterns of the Human Brain: A Caveat for Registration

      • Frithjof Kruggel
      Pages 67-71

  4. Architectures

    1. Front Matter

      Pages 73-73
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    2. A Multi-organ Point Cloud Registration Algorithm for Abdominal CT Registration

      • Samuel Joutard, Thomas Pheiffer, Chloe Audigier, Patrick Wohlfahrt, Reuben Dorent, Sebastien Piat et al.
      Pages 75-84

    3. Voxelmorph++

      • Mattias P. Heinrich, Lasse Hansen
      Pages 85-95

    4. Unsupervised Learning of Diffeomorphic Image Registration via TransMorph

      • Junyu Chen, Eric C. Frey, Yong Du
      Pages 96-102

    5. SuperWarp: Supervised Learning and War** on U-Net for Invariant Subvoxel-Precise Registration

      • Sean I. Young, Yaël Balbastre, Adrian V. Dalca, William M. Wells, Juan Eugenio Iglesias, Bruce Fischl
      Pages 103-115

  5. Optimisation

    1. Front Matter

      Pages 117-117
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    2. Learn to Fuse Input Features for Large-Deformation Registration with Differentiable Convex-Discrete Optimisation

      • Hanna Siebert, Mattias P. Heinrich
      Pages 119-123

    3. Multi-magnification Networks for Deformable Image Registration on Histopathology Images

      • Oezdemir Cetin, Yiran Shu, Nadine Flinner, Paul Ziegler, Peter Wild, Heinz Koeppl
      Pages 124-133

    4. Realtime Optical Flow Estimation on Vein and Artery Ultrasound Sequences Based on Knowledge-Distillation

      • Till Nicke, Laura Graf, Mikko Lauri, Sven Mischkewitz, Simone Frintrop, Mattias P. Heinrich
      Pages 134-143
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Other volumes

  1. Biomedical Image Registration

Editors and Affiliations

  • Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands

    Alessa Hering

  • Helmholtz Center Munich, Neuherberg, Germany

    Julia Schnabel

  • University of Virginia, Charlottesville, USA

    Miaomiao Zhang

  • CONICET, Universidad Nacional del Litoral, Santa Fe, Argentina

    Enzo Ferrante

  • Universität zu Lübeck, Lübeck, Germany

    Mattias Heinrich

  • GALILEO, Technical University of Munich, Munich, Germany

    Daniel Rueckert

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