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© 2020

Machine Learning in Medical Imaging

11th International Workshop, MLMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings

  • Mingxia Liu
  • Pingkun Yan
  • Chunfeng Lian
  • Xiaohuan Cao
Conference proceedings MLMI 2020

Part of the Lecture Notes in Computer Science book series (LNCS, volume 12436)

Also part of the Image Processing, Computer Vision, Pattern Recognition, and Graphics book sub series (LNIP, volume 12436)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Dongren Yao, Jing Sui, Erkun Yang, Pew-Thian Yap, Dinggang Shen, Mingxia Liu
    Pages 1-10
  3. Weifeng Hu, Xiaofen Yao, Zhou Zheng, Xiaoyun Zhang, Yumin Zhong, Xiaoxia Wang et al.
    Pages 11-20
  4. Qinglin Dong, Ning Qiang, Jinglei Lv, Xiang Li, Liang Dong, Tianming Liu et al.
    Pages 21-29
  5. Zhou Zheng, Xiaoxia Wang, Xiaoyun Zhang, Yumin Zhong, Xiaofen Yao, Ya Zhang et al.
    Pages 30-39
  6. Eva Schnider, Antal Horváth, Georg Rauter, Azhar Zam, Magdalena Müller-Gerbl, Philippe C. Cattin
    Pages 40-49
  7. Bo Hu, Shenglong Zhou, Zhiwei Xiong, Feng Wu
    Pages 60-69
  8. Yuxin Kang, Hansheng Li, Xin Han, Boju Pan, Yuan Li, Yan Jin et al.
    Pages 70-79
  9. Raghavendra Selvan, Frederik Faye, Jon Middleton, Akshay Pai
    Pages 80-90
  10. Xuan Li, Yuchen Lu, Christian Desrosiers, Xue Liu
    Pages 91-100
  11. Yue Zhang, Jiong Wu, Yilong Liu, Yifan Chen, Ed X. Wu, Xiaoying Tang
    Pages 101-110
  12. Hao Guan, Erkun Yang, Li Wang, Pew-Thian Yap, Mingxia Liu, Dinggang Shen
    Pages 111-119
  13. Huahong Zhang, Rohit Bakshi, Francesca Bagnato, Ipek Oguz
    Pages 120-129
  14. Zhuowei Li, Qing Xia, Wenji Wang, Zhennan Yan, Ruohan Yin, Changjie Pan et al.
    Pages 130-138
  15. Pingjun Chen, Xiao Chen, Eric Z. Chen, Hanchao Yu, Terrence Chen, Shanhui Sun
    Pages 150-159
  16. Xi Fang, Thomas Sanford, Baris Turkbey, Sheng Xu, Bradford J. Wood, Pingkun Yan
    Pages 160-169
  17. Zhenyuan Ning, Yu Zhang, Yongsheng Pan, Tao Zhong, Mingxia Liu, Dinggang Shen
    Pages 170-179
  18. Carlos Tor-Diez, Antonio Reyes Porras, Roger J. Packer, Robert A. Avery, Marius George Linguraru
    Pages 180-188

About these proceedings

Introduction

This book constitutes the proceedings of the 11th International Workshop on Machine Learning in Medical Imaging, MLMI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic.

The 68 papers presented in this volume were carefully reviewed and selected from 101 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.


Keywords

artificial intelligence automatic segmentations bioinformatics cellular image analysis computer vision computer-aided diagnosis deep learning image analysis image processing image quality image reconstruction image segmentation machine learning medical images molecular imaging network protocols neural networks pattern recognition segmentation methods signal processing

Editors and affiliations

  • Mingxia Liu
    • 1
  • Pingkun Yan
    • 2
  • Chunfeng Lian
    • 3
  • Xiaohuan Cao
    • 4
  1. 1.University of North Carolina at Chapel HillChapel HillUSA
  2. 2.Rensselaer Polytechnic InstituteTroyUSA
  3. 3.University of North Carolina at Chapel HillChapel HillUSA
  4. 4.United Imaging IntelligenceShanghaiChina

Bibliographic information

  • Book Title Machine Learning in Medical Imaging
  • Book Subtitle 11th International Workshop, MLMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings
  • Editors Mingxia Liu
    Pingkun Yan
    Chunfeng Lian
    Xiaohuan Cao
  • Series Title Lecture Notes in Computer Science
  • Series Abbreviated Title Lect.Notes Computer
  • DOI https://doi.org/10.1007/978-3-030-59861-7
  • Copyright Information Springer Nature Switzerland AG 2020
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science Computer Science (R0)
  • Softcover ISBN 978-3-030-59860-0
  • eBook ISBN 978-3-030-59861-7
  • Series ISSN 0302-9743
  • Series E-ISSN 1611-3349
  • Edition Number 1
  • Number of Pages XV, 686
  • Number of Illustrations 172 b/w illustrations, 230 illustrations in colour
  • Topics Image Processing and Computer Vision
    Artificial Intelligence
    Pattern Recognition
    Computer Applications
  • Buy this book on publisher's site