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© 2019

Machine Learning in Medical Imaging

10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings

  • Heung-Il Suk
  • Mingxia Liu
  • Pingkun Yan
  • Chunfeng Lian
Conference proceedings MLMI 2019

Part of the Lecture Notes in Computer Science book series (LNCS, volume 11861)

Also part of the Image Processing, Computer Vision, Pattern Recognition, and Graphics book sub series (LNIP, volume 11861)

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Xuhua Ren, Lichi Zhang, Dongming Wei, Dinggang Shen, Qian Wang
    Pages 1-8
  3. Bolin Lai, Shiqi Peng, Guangyu Yao, Ya Zhang, Xiaoyun Zhang, Yanfeng Wang et al.
    Pages 9-17
  4. Yiqiu Shen, Nan Wu, Jason Phang, Jungkyu Park, Gene Kim, Linda Moy et al.
    Pages 18-26
  5. Hykoush Asaturyan, E. Louise Thomas, Julie Fitzpatrick, Jimmy D. Bell, Barbara Villarini
    Pages 27-35
  6. Haomiao Ni, Hong Liu, Kuansong Wang, Xiangdong Wang, Xunjian Zhou, Yueliang Qian
    Pages 36-44
  7. Sen Zhang, Changzheng Zhang, Lanjun Wang, Cixing Li, Dandan Tu, Rui Luo et al.
    Pages 54-62
  8. Changzheng Zhang, Dong Liu, Lanjun Wang, Yaoxin Li, Xiaoshi Chen, Rui Luo et al.
    Pages 63-72
  9. Feng Yang, Hang Yu, Kamolrat Silamut, Richard J. Maude, Stefan Jaeger, Sameer Antani
    Pages 73-80
  10. Shengyang Li, Xiaoyun Zhang, Xiaoxia Wang, Yumin Zhong, Xiaofen Yao, Ya Zhang et al.
    Pages 81-88
  11. Ali Hatamizadeh, Assaf Hoogi, Debleena Sengupta, Wuyue Lu, Brian Wilcox, Daniel Rubin et al.
    Pages 98-105
  12. Shunbo Hu, Lintao Zhang, Guoqiang Li, Mingtao Liu, Deqian Fu, Wenyin Zhang
    Pages 106-114
  13. Jinzheng Cai, Yingda Xia, Dong Yang, Daguang Xu, Lin Yang, Holger Roth
    Pages 124-132
  14. Wenqi Li, Fausto Milletarì, Daguang Xu, Nicola Rieke, Jonny Hancox, Wentao Zhu et al.
    Pages 133-141
  15. Junwei Li, Wei Shao, Zhongnian Li, Weida Li, Daoqiang Zhang
    Pages 142-150
  16. Abdullah-Al-Zubaer Imran, Demetri Terzopoulos
    Pages 151-159
  17. Wei Huang, Mingyuan Luo, Xi Liu, Peng Zhang, Huijun Ding, Dong Ni
    Pages 160-168

About these proceedings

Introduction

This book constitutes the proceedings of the 10th International Workshop on Machine Learning in Medical Imaging, MLMI 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. 

The 78 papers presented in this volume were carefully reviewed and selected from 158 submissions. 
They focus on major trends and challenges in the 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 ct image image analysis image reconstruction image registration image segmentation learning algorithms medical images neural networks recurrent neural networks segmentation methods Support Vector Machines (SVM)

Editors and affiliations

  1. 1.Korea UniversitySeoulKorea (Republic of)
  2. 2.University of North CarolinaChapel HillUSA
  3. 3.Rensselaer Polytechnic InstituteTroyUSA
  4. 4.University of North CarolinaChapel HillUSA

Bibliographic information

  • Book Title Machine Learning in Medical Imaging
  • Book Subtitle 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings
  • Editors Heung-Il Suk
    Mingxia Liu
    Pingkun Yan
    Chunfeng Lian
  • Series Title Lecture Notes in Computer Science
  • Series Abbreviated Title Lect.Notes Computer
  • DOI https://doi.org/10.1007/978-3-030-32692-0
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science Computer Science (R0)
  • Softcover ISBN 978-3-030-32691-3
  • eBook ISBN 978-3-030-32692-0
  • Series ISSN 0302-9743
  • Series E-ISSN 1611-3349
  • Edition Number 1
  • Number of Pages XVIII, 695
  • Number of Illustrations 65 b/w illustrations, 245 illustrations in colour
  • Topics Image Processing and Computer Vision
    Artificial Intelligence
  • Buy this book on publisher's site