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Machine Learning in Medical Imaging : Third International Workshop, MLMI 2012, Held in Conjunction with MICCAI 2012, Nice, France, October 1, 2012, Revised Selected Papers / edited by Fei Wang, Dinggang Shen, Pingkun Yan, Kenji Suzuki.
SpringerLink Books Lecture Notes In Computer Science (LNCS) (1997-2024) Available online
View online- Format:
- Book
- Series:
- Computer Science (Springer-11645)
- LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 7588.
- Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 7588
- Language:
- English
- Subjects (All):
- Optical data processing.
- Pattern perception.
- Artificial intelligence.
- Database management.
- Computer graphics.
- Image Processing and Computer Vision.
- Pattern Recognition.
- Artificial Intelligence.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Database Management.
- Computer Graphics.
- Local Subjects:
- Image Processing and Computer Vision.
- Pattern Recognition.
- Artificial Intelligence.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Database Management.
- Computer Graphics.
- Physical Description:
- 1 online resource (XII, 276 pages) : 91 illustrations.
- Edition:
- First edition 2012.
- Contained In:
- Springer eBooks
- Place of Publication:
- Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012.
- System Details:
- text file PDF
- Summary:
- This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Medical Imaging, MLMI 2012, held in conjunction with MICCAI 2012, in Nice, France, in October 2012. The 33 revised full papers presented were carefully reviewed and selected from 67 submissions. The main aim of this workshop is to help advance the scientific research within the broad field of machine learning in medical imaging. It focuses on major trends and challenges in this area, and it presents work aimed to identify new cutting-edge techniques and their use in medical imaging.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-642-35428-1
- 9783642354281
- Access Restriction:
- Restricted for use by site license.
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