© 2014

Machine Learning in Medical Imaging

5th International Workshop, MLMI 2014, Held in Conjunction with MICCAI 2014, Boston, MA, USA, September 14, 2014. Proceedings

  • Guorong Wu
  • Daoqiang Zhang
  • Luping Zhou
Conference proceedings MLMI 2014

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8679)

Table of contents

  1. Front Matter
  2. Qian Wang, Guorong Wu, Li Wang, Pengfei Shi, Weili Lin, Dinggang Shen
    Pages 1-8
  3. Lisa M. Koch, Robert Wright, Deniz Vatansever, Vanessa Kyriakopoulou, Christina Malamateniou, Prachi A. Patkee et al.
    Pages 9-16
  4. Ryan Kiros, Karteek Popuri, Dana Cobzas, Martin Jagersand
    Pages 25-32
  5. Menglin Jiang, Shaoting Zhang, Dimitris N. Metaxas
    Pages 33-41
  6. Chenhui Hu, Xue Hua, Paul M. Thompson, Georges El Fakhri, Quanzheng Li
    Pages 42-49
  7. Jianjia Zhang, Luping Zhou, Lei Wang, Wanqing Li
    Pages 59-67
  8. Zhen Yang, Shenghua Zhong, Aaron Carass, Sarah H. Ying, Jerry L. Prince
    Pages 68-76
  9. Ricardo Guerrero, Christian Ledig, Daniel Rueckert
    Pages 77-84
  10. Joseph G. Jacobs, Eleftheria Panagiotaki, Daniel C. Alexander
    Pages 85-92
  11. Mohammad Yaqub, Anil Kopuri, Sylvia Rueda, Peter B. Sullivan, Kenneth McCormick, J. Alison Noble
    Pages 109-116
  12. Youngjin Yoo, Tom Brosch, Anthony Traboulsee, David K. B. Li, Roger Tam
    Pages 117-124
  13. Hao Chen, Dong Ni, Xin Yang, Shengli Li, Pheng Ann Heng
    Pages 125-132
  14. Mohammad Ali Maraci, Raffaele Napolitano, Aris Papageorghiou, J. Alison Noble
    Pages 133-140
  15. Mawulawoé Komlagan, Vinh-Thong Ta, Xingyu Pan, Jean-Philippe Domenger, D. Louis Collins, Pierrick Coupé et al.
    Pages 141-148
  16. Harini Veeraraghavan, Duc Fehr, Ross Schmidtlein, Sinchun Hwang, Joseph O. Deasy
    Pages 149-156

About these proceedings


This book constitutes the refereed proceedings of the 5th International Workshop on Machine Learning in Medical Imaging, MLMI 2014, held in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2014, in Cambridge, MA, USA, in September 2014. The 40 contributions included in this volume were carefully reviewed and selected from 70 submissions. They focus on major trends and challenges in the area of machine learning in medical imaging and aim to identify new cutting-edge techniques and their use in medical imaging.


brain network analysis cellular image analysis computer-aided diagnostics/detection deep learning health informatics image registration image retrieval image segmentation machine learning manifold learning medical imaging multi-modality fusion multi-task learning sparse learning transfer learning unsupervised learning

Editors and affiliations

  • Guorong Wu
    • 1
  • Daoqiang Zhang
    • 2
  • Luping Zhou
    • 3
  1. 1.University of North Carolina at Chapel HillChapel HillUSA
  2. 2.Nanjing University of Aeronautics and AstronauticsNanjingChina
  3. 3.University of WollongongWollongongAustralia

Bibliographic information