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＜電子ブック＞
Computational Diffusion MRI : MICCAI Workshop, Boston, MA, USA, September 2014 / edited by Lauren O'Donnell, Gemma Nedjati-Gilani, Yogesh Rathi, Marco Reisert, Torben Schneider
(Mathematics and Visualization. ISSN:2197666X)

版	1st ed. 2014.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2014
本文言語	英語
大きさ	IX, 219 p. 63 illus., 51 illus. in color : online resource
著者標目	O'Donnell, Lauren editor Nedjati-Gilani, Gemma editor Rathi, Yogesh editor Reisert, Marco editor Schneider, Torben editor SpringerLink (Online service)
件　名	LCSH:Biomathematics LCSH:Mathematics -- Data processing  全ての件名で検索 LCSH:Computer vision LCSH:Pattern recognition systems FREE:Mathematical and Computational Biology FREE:Computational Mathematics and Numerical Analysis FREE:Computer Vision FREE:Automated Pattern Recognition
一般注記	I. Network analysis -- II. Clinical applications -- III. Tractography -- IV. Q-space reconstruction -- V. Post-processing This book contains papers presented at the 2014 MICCAI Workshop on Computational Diffusion MRI, CDMRI’14. Detailing new computational methods applied to diffusion magnetic resonance imaging data, it offers readers a snapshot of the current state of the art and covers a wide range of topics from fundamental theoretical work on mathematical modeling to the development and evaluation of robust algorithms and applications in neuroscientific studies and clinical practice.   Inside, readers will find information on brain network analysis, mathematical modeling for clinical applications, tissue microstructure imaging, super-resolution methods, signal reconstruction, visualization, and more. Contributions include both careful mathematical derivations and a large number of rich full-color visualizations.   Computational techniques are key to the continued success and development of diffusion MRI and to its widespread transfer into the clinic. This volume will offer a valuable starting point for anyone interested in learning computational diffusion MRI. It also offers new perspectives and insights on current research challenges for those currently in the field. The book will be of interest to researchers and practitioners in computer science, MR physics, and applied mathematics HTTP:URL=https://doi.org/10.1007/978-3-319-11182-7

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