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Simulation and Synthesis in Medical Imaging

6th International Workshop, SASHIMI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings

  • Conference proceedings
  • © 2021

Overview

Editors:
  1. David Svoboda

    1. Masaryk University, Brno, Czech Republic

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  2. Ninon Burgos

    1. CNRS – Paris Brain Institute, Paris, France

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  3. Jelmer M. Wolterink

    1. University of Twente, Enschede, The Netherlands

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  4. Can Zhao

    1. NVIDIA, Santa Clara, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12965)

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

Included in the following conference series:

Conference proceedings info: SASHIMI 2021.

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Table of contents (15 papers)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Method-Oriented Papers

    1. Front Matter

      Pages 1-1
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    2. Detail Matters: High-Frequency Content for Realistic Synthetic MRI Generation

      • Filip Rusak, Rodrigo Santa Cruz, Elliot Smith, Jurgen Fripp, Clinton Fookes, Pierrick Bourgeat et al.
      Pages 3-13

    3. Joint Image and Label Self-super-Resolution

      • Samuel W. Remedios, Shuo Han, Blake E. Dewey, Dzung L. Pham, Jerry L. Prince, Aaron Carass
      Pages 14-23

    4. Super-Resolution by Latent Space Exploration: Training with Poorly-Aligned Clinical and Micro CT Image Dataset

      • Tong Zheng, Hirohisa Oda, Yuichiro Hayashi, Shota Nakamura, Masahiro Oda, Kensaku Mori
      Pages 24-33

    5. A Glimpse into the Future: Disease Progression Simulation for Breast Cancer in Mammograms

      • Ibrahim Jubran, Moshiko Raboh, Shaked Perek, David Gruen, Efrat Hexter
      Pages 34-43

    6. Synth-by-Reg (SbR): Contrastive Learning for Synthesis-Based Registration of Paired Images

      • Adrià Casamitjana, Matteo Mancini, Juan Eugenio Iglesias
      Pages 44-54

    7. Learning-Based Template Synthesis for Groupwise Image Registration

      • Ziyi He, Albert C. S. Chung
      Pages 55-66

    8. The Role of MRI Physics in Brain Segmentation CNNs: Achieving Acquisition Invariance and Instructive Uncertainties

      • Pedro Borges, Richard Shaw, Thomas Varsavsky, Kerstin Klaser, David Thomas, Ivana Drobnjak et al.
      Pages 67-76

    9. Transfer Learning in Optical Microscopy

      • Martin Kozlovský, David Wiesner, David Svoboda
      Pages 77-86

    10. X-ray Synthesis Based on Triangular Mesh Models Using GPU-Accelerated Ray Tracing for Multi-modal Breast Image Registration

      • J. Maul, S. Said, N. Ruiter, T. Hopp
      Pages 87-96

  3. Application-Oriented Papers

    1. Front Matter

      Pages 97-97
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    2. Frozen-to-Paraffin: Categorization of Histological Frozen Sections by the Aid of Paraffin Sections and Generative Adversarial Networks

      • Michael Gadermayr, Maximilian Tschuchnig, Lea Maria Stangassinger, Christina Kreutzer, Sebastien Couillard-Despres, Gertie Janneke Oostingh et al.
      Pages 99-109

    3. SequenceGAN: Generating Fundus Fluorescence Angiography Sequences from Structure Fundus Image

      • Wanyue Li, Yi He, Wen Kong, Jing Wang, Guohua Deng, Yiwei Chen et al.
      Pages 110-120

    4. Cerebral Blood Volume Prediction Based on Multi-modality Magnetic Resonance Imaging

      • Yongsheng Pan, Jingyu Huang, Bao Wang, Peng Zhao, Yingchao Liu, Yong Xia
      Pages 121-130

    5. Cine-MRI Simulation to Evaluate Tumor Tracking

      • José D. Tascón-Vidarte, Isak Wahlstedt, Julien Jomier, Kenny Erleben, Ivan R. Vogelius, Sune Darkner
      Pages 131-141

    6. GAN-Based Synthetic FDG PET Images from T1 Brain MRI Can Serve to Improve Performance of Deep Unsupervised Anomaly Detection Models

      • Daria Zotova, Julien Jung, Carole Lartizien
      Pages 142-152

  4. Correction to: Frozen-to-Paraffin: Categorization of Histological Frozen Sections by the Aid of Paraffin Sections and Generative Adversarial Networks

    • Michael Gadermayr, Maximilian Tschuchnig, Lea Maria Stangassinger, Christina Kreutzer, Sebastien Couillard-Despres, Gertie Janneke Oostingh et al.
    Pages C1-C1

  5. Back Matter

    Pages 153-154
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Other volumes

  1. Simulation and Synthesis in Medical Imaging

Keywords

About this book

This book constitutes the refereed proceedings of the 6th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in September 2021.*

The 14 full papers presented were carefully reviewed and selected from 18 submissions. The contributions span the following broad categories in alignment with the initial call-for-papers: methods based on generative models or adversarial learning for MRI/CT/ microscopy image synthesis, and several applications of image synthesis and simulation for data augmentation, image enhancement, or segmentation.

*The workshop was held virtually.

Editors and Affiliations

  • Masaryk University, Brno, Czech Republic

    David Svoboda

  • CNRS – Paris Brain Institute, Paris, France

    Ninon Burgos

  • University of Twente, Enschede, The Netherlands

    Jelmer M. Wolterink

  • NVIDIA, Santa Clara, USA

    Can Zhao

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