© 2010

Machine Learning in Medical Imaging

First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Beijing, China, September 20, 2010. Proceedings

  • Fei Wang
  • Pingkun Yan
  • Kenji Suzuki
  • Dinggang Shen
  • State-of-the-art research

  • Fast-track conference proceedings

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Conference proceedings MLMI 2010

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6357)

Table of contents

  1. Front Matter
  2. Sushil Mittal, Yefeng Zheng, Bogdan Georgescu, Fernando Vega-Higuera, Shaohua Kevin Zhou, Peter Meer et al.
    Pages 1-9
  3. Xiao Dong, Huanxiang Lu, Yasuo Sakurai, Hitoshi Yamagata, Guoyan Zheng, Mauricio Reyes
    Pages 10-17
  4. Wei Huang, Kap Luk Chan, Huiqi Li, Joo Hwee Lim, Jiang Liu, Tien Yin Wong
    Pages 18-25
  5. Hakim C. Achterberg, Fedde van der Lijn, Tom den Heijer, Aad van der Lugt, Monique M. B. Breteler, Wiro J. Niessen et al.
    Pages 42-49
  6. Vincent Michel, Evelyn Eger, Christine Keribin, Bertrand Thirion
    Pages 50-57
  7. Marc Niethammer, David Borland, J. S. Marron, John Woosley, Nancy E. Thomas
    Pages 58-66
  8. Fangfang Zhou, Ying Zhao, Kwan-Liu Ma
    Pages 67-75
  9. Bing Nan Li, Chee Kong Chui, Sim Heng Ong, Toshikatsu Washio, Tomokazu Numano, Stephen Chang et al.
    Pages 76-83
  10. Yefeng Zheng, Fernando Vega-Higuera, Shaohua Kevin Zhou, Dorin Comaniciu
    Pages 84-91
  11. Bernard Ng, Arash Vahdat, Ghassan Hamarneh, Rafeef Abugharbieh
    Pages 108-115
  12. Robin Wolz, Paul Aljabar, Joseph V. Hajnal, Daniel Rueckert
    Pages 116-123
  13. André Gooßen, Thomas Pralow, Rolf-Rainer Grigat
    Pages 132-139
  14. Chong-Yaw Wee, Pew-Thian Yap, Jeffery N. Brownyke, Guy G. Potter, David C. Steffens, Kathleen Welsh-Bohmer et al.
    Pages 140-147
  15. Wei Bian, Jun Li, Dacheng Tao
    Pages 148-156

About these proceedings


The first International Workshop on Machine Learning in Medical Imaging, MLMI 2010, was held at the China National Convention Center, Beijing, China on Sept- ber 20, 2010 in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2010. Machine learning plays an essential role in the medical imaging field, including image segmentation, image registration, computer-aided diagnosis, image fusion, ima- guided therapy, image annotation, and image database retrieval. With advances in me- cal imaging, new imaging modalities, and methodologies such as cone-beam/multi-slice CT, 3D Ultrasound, tomosynthesis, diffusion-weighted MRI, electrical impedance to- graphy, and diffuse optical tomography, new machine-learning algorithms/applications are demanded in the medical imaging field. Single-sample evidence provided by the patient’s imaging data is often not sufficient to provide satisfactory performance; the- fore tasks in medical imaging require learning from examples to simulate a physician’s prior knowledge of the data. The MLMI 2010 is the first workshop on this topic. The workshop focuses on major trends and challenges in this area, and works to identify new techniques and their use in medical imaging. Our goal is to help advance the scientific research within the broad field of medical imaging and machine learning. The range and level of submission for this year's meeting was of very high quality. Authors were asked to submit full-length papers for review. A total of 38 papers were submitted to the workshop in response to the call for papers.


MRI anatomy computer-aided diagnosis image analysis image database retrieval image reconstruction image segmentation image-guided therapy machine learning medical imaging neural networks pathologic image analysis pattern re ultrasound imaging

Editors and affiliations

  • Fei Wang
    • 1
  • Pingkun Yan
    • 2
  • Kenji Suzuki
    • 3
  • Dinggang Shen
    • 4
  1. 1.IBM Research AlmadenSan JoseUSA
  2. 2.Philips Research North AmericaBriarcliff ManorUSA
  3. 3.The University of ChicagoChicagoUSA
  4. 4.University of North CarolinaChapel HillUSA

Bibliographic information