Machine Learning in Medical Imaging

8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Proceedings

  • Qian Wang
  • Yinghuan Shi
  • Heung-Il Suk
  • Kenji Suzuki
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10541)

Table of contents

  1. Front Matter
    Pages VII-XIX
  2. Marie Bieth, Esther Alberts, Markus Schwaiger, Bjoern Menze
    Pages 1-9
  3. Sylvester Chiang, Sharmila Balasingham, Lara Richmond, Belinda Curpen, Mia Skarpathiotakis, Anne Martel
    Pages 10-18
  4. Jiří Borovec, Jan Kybic, Rodrigo Nava
    Pages 19-26
  5. Felix Durlak, Michael Wels, Chris Schwemmer, Michael Sühling, Stefan Steidl, Andreas Maier
    Pages 27-35
  6. Boris Kodner, Shiri Gordon, Jacob Goldberger, Tammy Riklin Raviv
    Pages 36-44
  7. Seongah Jeong, Xiang Li, Jiarui Yang, Quanzheng Li, Vahid Tarokh
    Pages 45-52
  8. Jorge Samper-González, Ninon Burgos, Sabrina Fontanella, Hugo Bertin, Marie-Odile Habert, Stanley Durrleman et al.
    Pages 53-60
  9. Darko Štern, Philipp Kainz, Christian Payer, Martin Urschler
    Pages 61-69
  10. Anees Kazi, Shadi Albarqouni, Amelia Jimenez Sanchez, Sonja Kirchhoff, Peter Biberthaler, Nassir Navab et al.
    Pages 70-78
  11. Fahdi Kanavati, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori, Daniel Rueckert, Ben Glocker
    Pages 79-87
  12. Yani Chen, Bibo Shi, Zhewei Wang, Tao Sun, Charles D. Smith, Jundong Liu
    Pages 88-96
  13. Yao Xiao, Ajay Gupta, Pina C. Sanelli, Ruogu Fang
    Pages 97-105
  14. Yuru Pei, Yunai Yi, Gengyu Ma, Yuke Guo, Gui Chen, Tianmin Xu et al.
    Pages 114-122
  15. Yuru Pei, Haifang Qin, Gengyu Ma, Yuke Guo, Gui Chen, Tianmin Xu et al.
    Pages 123-131
  16. Dakai Jin, Ziyue Xu, Adam P. Harrison, Kevin George, Daniel J. Mollura
    Pages 141-149
  17. Pei Dong, Xiaohuan Cao, Jun Zhang, Minjeong Kim, Guorong Wu, Dinggang Shen
    Pages 150-158
  18. Jun Wang, Qian Wang, Shitong Wang, Dinggang Shen
    Pages 159-167

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 8th International Workshop on Machine Learning in Medical Imaging, MLMI 2017, held in conjunction with MICCAI 2017, in Quebec City, QC, Canada, in September 2017.

The 44 full papers presented in this volume were carefully reviewed and selected from 63 submissions. The main aim of this workshop is to help advance scientific research within the broad field of machine learning in medical imaging. The workshop focuses on major trends and challenges in this area, and presents works aimed to identify new cutting-edge techniques and their use in medical imaging.

Keywords

classification and regression trees convolutional neural networks deep learning factorization methods generative adversarial networks image analysis image processing image segmentation learning networks learning systems machine learning medical image analysis multi-task learning neural networks shape representation supervised learning

Editors and affiliations

  • Qian Wang
    • 1
  • Yinghuan Shi
    • 2
  • Heung-Il Suk
    • 3
  • Kenji Suzuki
    • 4
  1. 1.Shanghai Jiao Tong UniversityShanghaiChina
  2. 2.Nanjing University NanjingChina
  3. 3.Korea University SeoulKorea (Republic of)
  4. 4.Illinois Institute of TechnologyChicagoUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-67389-9
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-67388-2
  • Online ISBN 978-3-319-67389-9
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book