Machine Learning in Medical Imaging
5th International Workshop, MLMI 2014, Held in Conjunction with MICCAI 2014, Boston, MA, USA, September 14, 2014, Proceedings
Editors: Wu, Guorong, Zhang, Daoqiang, Zhou, Luping (Eds.)
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- About this book
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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.
- Table of contents (40 chapters)
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Sparsity-Learning-Based Longitudinal MR Image Registration for Early Brain Development
Pages 1-8
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Graph-Based Label Propagation in Fetal Brain MR Images
Pages 9-16
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Deep Learning Based Automatic Immune Cell Detection for Immunohistochemistry Images
Pages 17-24
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Stacked Multiscale Feature Learning for Domain Independent Medical Image Segmentation
Pages 25-32
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Detection of Mammographic Masses by Content-Based Image Retrieval
Pages 33-41
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Table of contents (40 chapters)
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Machine Learning in Medical Imaging
- Book Subtitle
- 5th International Workshop, MLMI 2014, Held in Conjunction with MICCAI 2014, Boston, MA, USA, September 14, 2014, Proceedings
- Editors
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- Guorong Wu
- Daoqiang Zhang
- Luping Zhou
- Series Title
- Image Processing, Computer Vision, Pattern Recognition, and Graphics
- Series Volume
- 8679
- Copyright
- 2014
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing Switzerland
- eBook ISBN
- 978-3-319-10581-9
- DOI
- 10.1007/978-3-319-10581-9
- Softcover ISBN
- 978-3-319-10580-2
- Edition Number
- 1
- Number of Pages
- XII, 332
- Number of Illustrations
- 136 b/w illustrations
- Topics
