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Simplifying Medical Ultrasound

4th International Workshop, ASMUS 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Bernhard Kainz

    1. Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany

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  2. Alison Noble

    1. University of Oxford, Oxford, UK

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  3. Julia Schnabel

    1. Technical University of Munich, Munich, Germany

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  4. Bishesh Khanal

    1. Nepal Institute for Applied Mathematics and Informatics Institute for Research NAAMII, Lalitpur, Nepal

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  5. Johanna Paula Müller

    1. Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany

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  6. Thomas Day

    1. King's College London, London, UK

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14337)

Included in the following conference series:

Conference proceedings info: ASMUS 2023.

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About this book

This book constitutes the proceedings of the 4th International Workshop on Advances in Simplifying Medical UltraSound, ASMUS 2023, held in conjunction with MICCAI 2023, the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention. The conference took place in Vancouver, BC, Canada, on October 8, 2023.

The 19 papers presented in this book were carefully reviewed and selected from 30 submissions. They were organized in topical sections as follows:​ advanced imaging, segmentation, and ultrasound techniques; predictive analysis, learning, and classification; multimodal imaging, reconstruction, and real-time applications; diagnostic enhancements and novel ultrasound innovations.

Keywords

Table of contents (19 papers)

  1. Front Matter

    Pages i-xiii
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  2. Advanced Imaging, Segmentation, and Ultrasound Techniques

    1. Front Matter

      Pages 1-1
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    2. Ultrasound Video Segmentation with Adaptive Temporal Memory

      • He Zhao, Qianhui Men, Alexander Gleed, Aris T. Papageorghiou, J. Alison Noble
      Pages 3-12

    3. An Automatic Guidance and Quality Assessment System for Doppler Imaging of Umbilical Artery

      • Chun Kit Wong, Manxi Lin, Alberto Raheli, Zahra Bashir, Morten Bo Søndergaard Svendsen, Martin Grønnebæk Tolsgaard et al.
      Pages 13-22

    4. SonoSAM - Segment Anything on Ultrasound Images

      • Hariharan Ravishankar, Rohan Patil, Vikram Melapudi, Pavan Annangi
      Pages 23-33

    5. Echo from Noise: Synthetic Ultrasound Image Generation Using Diffusion Models for Real Image Segmentation

      • David Stojanovski, Uxio Hermida, Pablo Lamata, Arian Beqiri, Alberto Gomez
      Pages 34-43Open Access

    6. Graph Convolutional Neural Networks for Automated Echocardiography View Recognition: A Holistic Approach

      • Sarina Thomas, Cristiana Tiago, Børge Solli Andreassen, Svein-Arne Aase, Jurica Šprem, Erik Steen et al.
      Pages 44-54

  3. Predictive Analysis, Learning, and Classification

    1. Front Matter

      Pages 55-55
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    2. Leveraging Shape and Spatial Information for Spontaneous Preterm Birth Prediction

      • Paraskevas Pegios, Emilie Pi Fogtmann Sejer, Manxi Lin, Zahra Bashir, Morten Bo Søndergaard Svendsen, Mads Nielsen et al.
      Pages 57-67

    3. Leveraging Self-supervised Learning for Fetal Cardiac Planes Classification Using Ultrasound Scan Videos

      • Joseph Geo Benjamin, Mothilal Asokan, Amna Alhosani, Hussain Alasmawi, Werner Gerhard Diehl, Leanne Bricker et al.
      Pages 68-78

    4. Self-Supervised Learning to More Efficiently Generate Segmentation Masks for Wrist Ultrasound

      • Yuyue Zhou, Jessica Knight, Banafshe Felfeliyan, Shrimanti Ghosh, Fatima Alves-Pereira, Christopher Keen et al.
      Pages 79-88

    5. Synthetic Boost: Leveraging Synthetic Data for Enhanced Vision-Language Segmentation in Echocardiography

      • Rabin Adhikari, Manish Dhakal, Safal Thapaliya, Kanchan Poudel, Prasiddha Bhandari, Bishesh Khanal
      Pages 89-99

    6. SimNorth: A Novel Contrastive Learning Approach for Clustering Prenatal Ultrasound Images

      • Juan Prieto, Chiraz Benabdelkader, Teeranan Pokaprakarn, Hina Shah, Yuri Sebastião, Qing Dan et al.
      Pages 100-108

  4. Multimodal Imaging, Reconstruction, and Real-time Applications

    1. Front Matter

      Pages 109-109
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    2. HoloPOCUS: Portable Mixed-Reality 3D Ultrasound Tracking, Reconstruction and Overlay

      • Kian Wei Ng, Yujia Gao, Mohammed Shaheryar Furqan, Zachery Yeo, Joel Lau, Kee Yuan Ngiam et al.
      Pages 111-120

    3. MIC-CUSP: Multimodal Image Correlations for Ultrasound-Based Prostate Cancer Detection

      • Indrani Bhattacharya, Sulaiman Vesal, Hassan Jahanandish, Moonhyung Choi, Steve Zhou, Zachary Kornberg et al.
      Pages 121-131

    4. GAJA - Guided self-Acquisition of Joint ultrAsound images

      • Marco Colussi, Sergio Mascetti, Dragan Ahmetovic, Gabriele Civitarese, Marco Cacciatori, Flora Peyvandi et al.
      Pages 132-141

    5. Privileged Anatomical and Protocol Discrimination in Trackerless 3D Ultrasound Reconstruction

      • Qi Li, Ziyi Shen, Qian Li, Dean C. Barratt, Thomas Dowrick, Matthew J. Clarkson et al.
      Pages 142-151

  5. Diagnostic Enhancements and Novel Ultrasound Innovations

    1. Front Matter

      Pages 153-153
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    2. The Open Kidney Ultrasound Data Set

      • Rohit Singla, Cailin Ringstrom, Grace Hu, Victoria Lessoway, Janice Reid, Christopher Nguan et al.
      Pages 155-164
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Other volumes

  1. Simplifying Medical Ultrasound

Editors and Affiliations

  • Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany

    Bernhard Kainz, Johanna Paula Müller

  • University of Oxford, Oxford, UK

    Alison Noble

  • Technical University of Munich, Munich, Germany

    Julia Schnabel

  • Nepal Institute for Applied Mathematics and Informatics Institute for Research NAAMII, Lalitpur, Nepal

    Bishesh Khanal

  • King's College London, London, UK

    Thomas Day

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