Image Processing, Computer Vision, Pattern Recognition, and Graphics

Machine Learning in Medical Imaging

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

Editors: Wang, F., Yan, P., Suzuki, K., Shen, D. (Eds.)

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About this book

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.

Table of contents (23 chapters)

  • Fast Automatic Detection of Calcified Coronary Lesions in 3D Cardiac CT Images

    Mittal, Sushil (et al.)

    Pages 1-9

  • Automated Intervertebral Disc Detection from Low Resolution, Sparse MRI Images for the Planning of Scan Geometries

    Dong, Xiao (et al.)

    Pages 10-17

  • Content-Based Medical Image Retrieval with Metric Learning via Rank Correlation

    Huang, Wei (et al.)

    Pages 18-25

  • A Hyper-parameter Inference for Radon Transformed Image Reconstruction Using Bayesian Inference

    Shouno, Hayaru (et al.)

    Pages 26-33

  • Patch-Based Generative Shape Model and MDL Model Selection for Statistical Analysis of Archipelagos

    Ganz, Melanie (et al.)

    Pages 34-41

Buy this book

eBook $69.99
price for USA (gross)
  • ISBN 978-3-642-15948-0
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $89.99
price for USA
  • ISBN 978-3-642-15947-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Machine Learning in Medical Imaging
Book Subtitle
First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Beijing, China, September 20, 2010, Proceedings
Editors
  • Fei Wang
  • Pingkun Yan
  • Kenji Suzuki
  • Dinggang Shen
Series Title
Image Processing, Computer Vision, Pattern Recognition, and Graphics
Series Volume
6357
Copyright
2010
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-642-15948-0
DOI
10.1007/978-3-642-15948-0
Softcover ISBN
978-3-642-15947-3
Edition Number
1
Number of Pages
IX, 192
Number of Illustrations and Tables
84 b/w illustrations
Topics