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Simplifying Medical Ultrasound

Second International Workshop, ASMUS 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings

  • Conference proceedings
  • © 2021

Overview

Editors:
  1. J. Alison Noble

    1. University of Oxford, Oxford, UK

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  2. Stephen Aylward

    1. Kitware Inc., Carrboro, USA

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  3. Alexander Grimwood

    1. University College London, London, UK

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  4. Zhe Min

    1. University College London, London, UK

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  5. Su-Lin Lee

    1. University College London, London, UK

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  6. Yipeng Hu

    1. University College London, London, UK

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12967)

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

Included in the following conference series:

Conference proceedings info: ASMUS 2021.

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About this book

This book constitutes the proceedings of the Second International Workshop on Advances in Simplifying Medical UltraSound, ASMUS 2021, held on September 27, 2021, in conjunction with MICCAI 2021, the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention. The conference was planned to take place in Strasbourg, France, but changed to an online event due to the Coronavirus pandemic.

The 22 papers presented in this book were carefully reviewed and selected from 30 submissions. They were organized in topical sections as follows: segmentation and detection; registration, guidance and robotics; classification and image synthesis; and quality assessment and quantitative imaging.




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Table of contents (22 papers)

  1. Front Matter

    Pages i-xiii
    Download chapter PDF

  2. Segmentation and Detection

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Automatic Ultrasound Vessel Segmentation with Deep Spatiotemporal Context Learning

      • Baichuan Jiang, Alvin Chen, Shyam Bharat, Mingxin Zheng
      Pages 3-13

    3. Multimodal Continual Learning with Sonographer Eye-Tracking in Fetal Ultrasound

      • Arijit Patra, Yifan Cai, Pierre Chatelain, Harshita Sharma, Lior Drukker, Aris T. Papageorghiou et al.
      Pages 14-24

    4. Development and Evaluation of Intraoperative Ultrasound Segmentation with Negative Image Frames and Multiple Observer Labels

      • Liam F. Chalcroft, Jiongqi Qu, Sophie A. Martin, Iani JMB Gayo, Giulio V. Minore, Imraj RD Singh et al.
      Pages 25-34

    5. Automatic Tomographic Ultrasound Imaging Sequence Extraction of the Anal Sphincter

      • Helena Williams, Laura Cattani, Tom Vercauteren, Jan Deprest, Jan D’hooge
      Pages 35-44

    6. Lung Ultrasound Segmentation and Adaptation Between COVID-19 and Community-Acquired Pneumonia

      • Harry Mason, Lorenzo Cristoni, Andrew Walden, Roberto Lazzari, Thomas Pulimood, Louis Grandjean et al.
      Pages 45-53

    7. An Efficient Tracker for Thyroid Nodule Detection and Tracking During Ultrasound Screening

      • Ting Liu, Xing An, Bin Lin, Yanbo Liu, Wenlong Xu, Yuxi Liu et al.
      Pages 54-62

    8. TransBridge: A Lightweight Transformer for Left Ventricle Segmentation in Echocardiography

      • Kaizhong Deng, Yanda Meng, Dongxu Gao, Joshua Bridge, Yaochun Shen, Gregory Lip et al.
      Pages 63-72

  3. Registration, Guidance and Robotics

    1. Front Matter

      Pages 73-73
      Download chapter PDF

    2. Adversarial Affine Registration for Real-Time Intraoperative Registration of 3-D US-US for Brain Shift Correction

      • Marek Wodzinski, Andrzej Skalski
      Pages 75-84

    3. Robust Ultrasound-to-Ultrasound Registration for Intra-operative Brain Shift Correction with a Siamese Neural Network

      • Amir Pirhadi, Hassan Rivaz, M. Omair Ahmad, Yiming Xiao
      Pages 85-95

    4. Pose Estimation of 2D Ultrasound Probe from Ultrasound Image Sequences Using CNN and RNN

      • Kanta Miura, Koichi Ito, Takafumi Aoki, Jun Ohmiya, Satoshi Kondo
      Pages 96-105

    5. Evaluation of Low-Cost Hardware Alternatives for 3D Freehand Ultrasound Reconstruction in Image-Guided Neurosurgery

      • Étienne Léger, Houssem Eddine Gueziri, D. Louis Collins, Tiberiu Popa, Marta Kersten-Oertel
      Pages 106-115

    6. Application Potential of Robot-Guided Ultrasound During CT-Guided Interventions

      • Josefine Schreiter, Fabian Joeres, Christine March, Maciej Pech, Christian Hansen
      Pages 116-125

  4. Classification and Image Synthesis

    1. Front Matter

      Pages 127-127
      Download chapter PDF

    2. Towards Scale and Position Invariant Task Classification Using Normalised Visual Scanpaths in Clinical Fetal Ultrasound

      • Clare Teng, Harshita Sharma, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble
      Pages 129-138

    3. Efficient Echocardiogram View Classification with Sampling-Free Uncertainty Estimation

      • Ang Nan Gu, Christina Luong, Mohammad H. Jafari, Nathan Van Woudenberg, Hany Girgis, Purang Abolmaesumi et al.
      Pages 139-148

    4. Contrastive Learning for View Classification of Echocardiograms

      • Agisilaos Chartsias, Shan Gao, Angela Mumith, Jorge Oliveira, Kanwal Bhatia, Bernhard Kainz et al.
      Pages 149-158

    5. Imaging Biomarker Knowledge Transfer for Attention-Based Diagnosis of COVID-19 in Lung Ultrasound Videos

      • Tyler Lum, Mobina Mahdavi, Oron Frenkel, Christopher Lee, Mohammad H. Jafari, Fatemeh Taheri Dezaki et al.
      Pages 159-168
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Other volumes

  1. Simplifying Medical Ultrasound

Editors and Affiliations

  • University of Oxford, Oxford, UK

    J. Alison Noble

  • Kitware Inc., Carrboro, USA

    Stephen Aylward

  • University College London, London, UK

    Alexander Grimwood, Zhe Min, Su-Lin Lee, Yipeng Hu

Bibliographic Information

  • Book Title: Simplifying Medical Ultrasound

  • Book Subtitle: Second International Workshop, ASMUS 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings

  • Editors: J. Alison Noble, Stephen Aylward, Alexander Grimwood, Zhe Min, Su-Lin Lee, Yipeng Hu

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-030-87583-1

  • Publisher: Springer Cham

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

  • Copyright Information: Springer Nature Switzerland AG 2021

  • Softcover ISBN: 978-3-030-87582-4Published: 23 September 2021

  • eBook ISBN: 978-3-030-87583-1Published: 22 September 2021

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XIII, 230

  • Number of Illustrations: 13 b/w illustrations, 64 illustrations in colour

  • Topics: Computer Imaging, Vision, Pattern Recognition and Graphics, Artificial Intelligence, Computational Biology/Bioinformatics

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