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Myocardial Pathology Segmentation Combining Multi-Sequence Cardiac Magnetic Resonance Images

First Challenge, MyoPS 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Xiahai Zhuang

    1. Fudan University, Shanghai, China

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    You can also search for this editor in PubMed   Google Scholar

  2. Lei Li

    1. Shanghai Jiao Tong University, Shanghai, China

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12554)

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

Included in the following conference series:

Conference proceedings info: MyoPS 2020.

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Table of contents (17 papers)

  1. Front Matter

    Pages i-viii
    Download chapter PDF

  2. Stacked BCDU-Net with Semantic CMR Synthesis: Application to Myocardial Pathology Segmentation Challenge

    • Carlos Martín-Isla, Maryam Asadi-Aghbolaghi, Polyxeni Gkontra, Victor M. Campello, Sergio Escalera, Karim Lekadir
    Pages 1-16

  3. EfficientSeg: A Simple But Efficient Solution to Myocardial Pathology Segmentation Challenge

    • Jianpeng Zhang, Yutong Xie, Zhibin Liao, Johan Verjans, Yong Xia
    Pages 17-25

  4. Two-Stage Method for Segmentation of the Myocardial Scars and Edema on Multi-sequence Cardiac Magnetic Resonance

    • Yanfei Liu, Maodan Zhang, Qi Zhan, Dongdong Gu, Guocai Liu
    Pages 26-36

  5. Multi-modality Pathology Segmentation Framework: Application to Cardiac Magnetic Resonance Images

    • Zhen Zhang, Chenyu Liu, Wangbin Ding, Sihan Wang, Chenhao Pei, Mingjing Yang et al.
    Pages 37-48

  6. Myocardial Edema and Scar Segmentation Using a Coarse-to-Fine Framework with Weighted Ensemble

    • Shuwei Zhai, Ran Gu, Wenhui Lei, Guotai Wang
    Pages 49-59

  7. Exploring Ensemble Applications for Multi-sequence Myocardial Pathology Segmentation

    • Markus J. Ankenbrand, David Lohr, Laura M. Schreiber
    Pages 60-67

  8. Max-Fusion U-Net for Multi-modal Pathology Segmentation with Attention and Dynamic Resampling

    • Haochuan Jiang, Chengjia Wang, Agisilaos Chartsias, Sotirios A. Tsaftaris
    Pages 68-81

  9. Fully Automated Deep Learning Based Segmentation of Normal, Infarcted and Edema Regions from Multiple Cardiac MRI Sequences

    • Xiaoran Zhang, Michelle Noga, Kumaradevan Punithakumar
    Pages 82-91

  10. CMS-UNet: Cardiac Multi-task Segmentation in MRI with a U-Shaped Network

    • Weisheng Li, Linhong Wang, Sheng Qin
    Pages 92-101

  11. Automatic Myocardial Scar Segmentation from Multi-sequence Cardiac MRI Using Fully Convolutional Densenet with Inception and Squeeze-Excitation Module

    • Tewodros Weldebirhan Arega, Stéphanie Bricq
    Pages 102-117

  12. Dual Attention U-Net for Multi-sequence Cardiac MR Images Segmentation

    • Hong Yu, Sen Zha, Yubin Huangfu, Chen Chen, Meng Ding, Jiangyun Li
    Pages 118-127

  13. Accurate Myocardial Pathology Segmentation with Residual U-Net

    • Altunok Elif, Oksuz Ilkay
    Pages 128-137

  14. Stacked and Parallel U-Nets with Multi-output for Myocardial Pathology Segmentation

    • Zhou Zhao, Nicolas Boutry, Élodie Puybareau
    Pages 138-145

  15. Dual-Path Feature Aggregation Network Combined Multi-layer Fusion for Myocardial Pathology Segmentation with Multi-sequence Cardiac MR

    • Feiyan Li, Weisheng Li
    Pages 146-158

  16. Cascaded Framework with Complementary CMR Information for Myocardial Pathology Segmentation

    • Jun Ma
    Pages 159-166

  17. Recognition and Standardization of Cardiac MRI Orientation via Multi-tasking Learning and Deep Neural Networks

    • Ke Zhang, Xiahai Zhuang
    Pages 167-176

  18. Correction to: Two-Stage Method for Segmentation of the Myocardial Scars and Edema on Multi-sequence Cardiac Magnetic Resonance

    • Yanfei Liu, Maodan Zhang, Qi Zhan, Dongdong Gu, Guocai Liu
    Pages C1-C1

  19. Back Matter

    Pages 177-177
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  1. Myocardial Pathology Segmentation Combining Multi-Sequence Cardiac Magnetic Resonance Images

Keywords

About this book

This book constitutes the First Myocardial Pathology Segmentation Combining Multi-Sequence CMR Challenge, MyoPS 2020, which was held in conjunction with the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The challenge took place virtually due to the COVID-19 crisis.

The 12 full and 4 short papers presented in this volume were carefully reviewed and selected form numerous submissions. This challenge aims not only to benchmark various myocardial pathology segmentation algorithms, but also to cover the topic of general cardiac image segmentation, registration and modeling, and raise discussions for further technical development and clinical deployment.

Editors and Affiliations

  • Fudan University, Shanghai, China

    Xiahai Zhuang

  • Shanghai Jiao Tong University, Shanghai, China

    Lei Li

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