© 2016

Machine Learning in Medical Imaging

7th International Workshop, MLMI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings

  • Li Wang
  • Ehsan Adeli
  • Qian Wang
  • Yinghuan Shi
  • Heung-Il Suk
Conference proceedings MLMI 2016

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10019)

Also part of the Image Processing, Computer Vision, Pattern Recognition, and Graphics book sub series (LNIP, volume 10019)

Table of contents

  1. Front Matter
    Pages I-XIV
  2. Chen Zu, Yue Gao, Brent Munsell, Minjeong Kim, Ziwen Peng, Yingying Zhu et al.
    Pages 1-9
  3. Christoph Jud, Nadia Möri, Benedikt Bitterli, Philippe C. Cattin
    Pages 10-17
  4. Gerard Sanroma, Oualid M. Benkarim, Gemma Piella, Miguel Ángel González Ballester
    Pages 27-35
  5. Lifang Wei, Shunbo Hu, Yaozong Gao, Xiaohuan Cao, Guorong Wu, Dinggang Shen
    Pages 36-44
  6. Jessie Thomson, Terence O’Neill, David Felson, Tim Cootes
    Pages 45-52
  7. Jun Zhang, Yaozong Gao, Sang Hyun Park, Xiaopeng Zong, Weili Lin, Dinggang Shen
    Pages 61-68
  8. Minjeong Kim, Guorong Wu, Isrem Rekik, Dinggang Shen
    Pages 69-76
  9. Xiaofeng Zhu, Heung-Il Suk, Kim-Han Thung, Yingying Zhu, Guorong Wu, Dinggang Shen
    Pages 77-85
  10. Yan Wang, Xi Wu, Guangkai Ma, Zongqing Ma, Ying Fu, Jiliu Zhou
    Pages 86-94
  11. Chen Qin, Ricardo Guerrero Moreno, Christopher Bowles, Christian Ledig, Philip Scheltens, Frederik Barkhof et al.
    Pages 104-112
  12. Jinjie Wu, Jun Shi, Shihui Ying, Qi Zhang, Yan Li
    Pages 122-129
  13. Yuan Liu, Hasan E. Çetingül, Benjamin L. Odry, Mariappan S. Nadar
    Pages 130-138
  14. Mingchen Gao, Ziyue Xu, Le Lu, Adam P. Harrison, Ronald M. Summers, Daniel J. Mollura
    Pages 147-155
  15. Mohammad Arafat Hussain, Ghassan Hamarneh, Timothy W. O’Connell, Mohammed F. Mohammed, Rafeef Abugharbieh
    Pages 156-163

About these proceedings


This book constitutes the refereed proceedings of the 7th International Workshop on Machine Learning in Medical Imaging, MLMI 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016.

The 38 full papers presented in this volume were carefully reviewed and selected from 60 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.


computer-aided diagnosis image processing machine learning neural networks supervised learning 3D ultrasound brain MRI classification deep learning dimensionality reduction ensemble learning factorization methods image segmentation kernel methods manifold learning medical image analysis multi-task learning regression trees sensorless reconstruction shape representation

Editors and affiliations

  • Li Wang
    • 1
  • Ehsan Adeli
    • 2
  • Qian Wang
    • 3
  • Yinghuan Shi
    • 4
  • Heung-Il Suk
    • 5
  1. 1.University of North Carolina Chapel HillUSA
  2. 2.University of North Carolina Chapel HillUSA
  3. 3.Shanghai Jiaotong University ShanghaiChina
  4. 4.Nanjing University NanjingChina
  5. 5.Korea University SeoulKorea (Republic of)

Bibliographic information