Machine Learning in Medical Imaging [electronic resource] : 6th International Workshop, MLMI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Proceedings / edited by Luping Zhou, Li Wang, Qian Wang, Yinghuan Shi.
Contributor(s): Zhou, Luping [editor.] | Wang, Li [editor.] | Wang, Qian [editor.] | Shi, Yinghuan [editor.] | SpringerLink (Online service).
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BookSeries: Lecture Notes in Computer Science: 9352Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Description: XII, 341 p. 128 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319248882.Subject(s): Computer science | Health informatics | Data mining | Artificial intelligence | Image processing | Pattern recognition | Computer Science | Image Processing and Computer Vision | Pattern Recognition | Health Informatics | Data Mining and Knowledge Discovery | Artificial Intelligence (incl. Robotics)Additional physical formats: Printed edition:: No titleDDC classification: 006.6 | 006.37 Online resources: Click here to access online
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Springer eBooksSummary: This book constitutes the proceedings of the 6th International Workshop on Machine Learning in Medical Imaging, MLMI 2015, held in conjunction with MICCAI 2015, in Munich in October 2015. The 40 full papers presented in this volume were carefully reviewed and selected from 69 submissions. The workshop focuses on major trends and challenges in the area of machine learning in medical imaging and present works aimed to identify new cutting-edge techniques and their use in medical imaging. .
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This book constitutes the proceedings of the 6th International Workshop on Machine Learning in Medical Imaging, MLMI 2015, held in conjunction with MICCAI 2015, in Munich in October 2015. The 40 full papers presented in this volume were carefully reviewed and selected from 69 submissions. The workshop focuses on major trends and challenges in the area of machine learning in medical imaging and present works aimed to identify new cutting-edge techniques and their use in medical imaging. .
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