Multimodal Brain Image Analysis [electronic resource] : First International Workshop, MBIA 2011, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 18, 2011. Proceedings / edited by Tianming Liu, Dinggang Shen, Luis Ibanez, Xiaodong Tao.
By: Liu, Tianming [editor.].
Contributor(s): Shen, Dinggang [editor.] | Ibanez, Luis [editor.] | Tao, Xiaodong [editor.] | SpringerLink (Online service).
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BookSeries: Lecture Notes in Computer Science: 7012Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Description: IX, 162 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642244469.Subject(s): Computer science | Radiology, Medical | Computer software | Artificial intelligence | Computer graphics | Computer vision | Optical pattern recognition | Computer Science | Pattern Recognition | Image Processing and Computer Vision | Computer Graphics | Artificial Intelligence (incl. Robotics) | Algorithm Analysis and Problem Complexity | Imaging / RadiologyDDC classification: 006.4 Online resources: Click here to access online
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Springer eBooksSummary: This book constitutes the refereed proceedings of the First International Workshop on Multimodal Brain Image Analysis, held in conjunction with MICCAI 2011, in Toronto, Canada, in September 2011. The 15 revised full papers presented together with 4 poster papers were carefully reviewed and selected from 24 submissions. The objective of this workshop is to facilitate advancements in the multimodal brain image analysis field, in terms of analysis methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience, and clinical applications.
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This book constitutes the refereed proceedings of the First International Workshop on Multimodal Brain Image Analysis, held in conjunction with MICCAI 2011, in Toronto, Canada, in September 2011. The 15 revised full papers presented together with 4 poster papers were carefully reviewed and selected from 24 submissions. The objective of this workshop is to facilitate advancements in the multimodal brain image analysis field, in terms of analysis methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience, and clinical applications.
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