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Left Atrial and Scar Quantification and Segmentation

First Challenge, LAScarQS 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Xiahai Zhuang

    1. Fudan University, Shanghai, China

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  2. Lei Li

    1. University of Oxford, Oxford, UK

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  3. Sihan Wang

    1. Fudan University, Shanghai, China

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  4. Fuping Wu

    1. University of Oxford, Oxford, UK

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13586)

Included in the following conference series:

Conference proceedings info: LAScarQS 2022.

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Table of contents (15 papers)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. LASSNet: A Four Steps Deep Neural Network for Left Atrial Segmentation and Scar Quantification

    • Arthur L. Lefebvre, Carolyna A. P. Yamamoto, Julie K. Shade, Ryan P. Bradley, Rebecca A. Yu, Rheeda L. Ali et al.
    Pages 1-15

  3. Multi-depth Boundary-Aware Left Atrial Scar Segmentation Network

    • Mengjun Wu, Wangbin Ding, Mingjing Yang, Liqin Huang
    Pages 16-23

  4. Self Pre-training with Single-Scale Adapter for Left Atrial Segmentation

    • Can Tu, Ziyan Huang, Zhongying Deng, Yuncheng Yang, Chenglong Ma, Junjun He et al.
    Pages 24-35

  5. UGformer for Robust Left Atrium and Scar Segmentation Across Scanners

    • Tianyi Liu, Size Hou, Jiayuan Zhu, Zilong Zhao, Haochuan Jiang
    Pages 36-48

  6. Automatically Segment the Left Atrium and Scars from LGE-MRIs Using a Boundary-Focused nnU-Net

    • Yuchen Zhang, Yanda Meng, Yalin Zheng
    Pages 49-59

  7. Two Stage of Histogram Matching Augmentation for Domain Generalization: Application to Left Atrial Segmentation

    • Xuru Zhang, Xinye Yang, Lihua Huang, Liqin Huang
    Pages 60-68

  8. Sequential Segmentation of the Left Atrium and Atrial Scars Using a Multi-scale Weight Sharing Network and Boundary-Based Processing

    • Abbas Khan, Omnia Alwazzan, Martin Benning, Greg Slabaugh
    Pages 69-82

  9. LA-HRNet: High-Resolution Network for Automatic Left Atrial Segmentation in Multi-center LEG MRI

    • Tongtong Xie, Zhengeng Yang, Hongshan Yu
    Pages 83-92

  10. Edge-Enhanced Feature Guided Joint Segmentation of Left Atrial and Scars in LGE MRI Images

    • Siping Zhou, Kai-Ni Wang, Guang-Quan Zhou
    Pages 93-105

  11. TESSLA: Two-Stage Ensemble Scar Segmentation for the Left Atrium

    • Shaheim Ogbomo-Harmitt, Jakub Grzelak, Ahmed Qureshi, Andrew P. King, Oleg Aslanidi
    Pages 106-114

  12. Deep U-Net Architecture with Curriculum Learning for Left Atrial Segmentation

    • Lei Jiang, Yan Li, Yifan Wang, Hengfei Cui, Yong Xia, Yanning Zhang
    Pages 115-123

  13. Cross-Domain Segmentation of Left Atrium Based on Multi-scale Decision Level Fusion

    • Feiyan Li, Weisheng Li
    Pages 124-132

  14. Using Polynomial Loss and Uncertainty Information for Robust Left Atrial and Scar Quantification and Segmentation

    • Tewodros Weldebirhan Arega, Stéphanie Bricq, Fabrice Meriaudeau
    Pages 133-144

  15. Automated Segmentation of the Left Atrium and Scar Using Deep Convolutional Neural Networks

    • Kumaradevan Punithakumar, Michelle Noga
    Pages 145-152

  16. Automatic Semi-supervised Left Atrial Segmentation Using Deep-Supervision 3DResUnet with Pseudo Labeling Approach for LAScarQS 2022 Challenge

    • Moona Mazher, Abdul Qayyum, Mohamed Abdel-Nasser, Domenec Puig
    Pages 153-161

  17. Back Matter

    Pages 163-164
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  1. Left Atrial and Scar Quantification and Segmentation

Keywords

About this book

This book constitutes the First Left Atrial and Scar Quantification and Segmentation Challenge, LAScarQS 2022, which was held in conjunction with the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, in Singapore, in September 2022.

The 15 papers presented in this volume were carefully reviewed and selected form numerous submissions. The aim of the challenge is not only benchmarking various LA scar segmentation algorithms, but also covering the topic of general cardiac image segmentation, quantification, joint optimization, and model generalization, and raising discussions for further technical development and clinical deployment.

Editors and Affiliations

  • Fudan University, Shanghai, China

    Xiahai Zhuang, Sihan Wang

  • University of Oxford, Oxford, UK

    Lei Li, Fuping Wu

Bibliographic Information

  • Book Title: Left Atrial and Scar Quantification and Segmentation

  • Book Subtitle: First Challenge, LAScarQS 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings

  • Editors: Xiahai Zhuang, Lei Li, Sihan Wang, Fuping Wu

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-31778-1

  • Publisher: Springer Cham

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

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023

  • Softcover ISBN: 978-3-031-31777-4Published: 05 May 2023

  • eBook ISBN: 978-3-031-31778-1Published: 04 May 2023

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: X, 164

  • Number of Illustrations: 11 b/w illustrations, 72 illustrations in colour

  • Topics: Computer Imaging, Vision, Pattern Recognition and Graphics

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