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Computational Diffusion MRI

Editat de Lauren O'Donnell, Gemma Nedjati-Gilani, Yogesh Rathi, Marco Reisert, Torben Schneider
en Limba Engleză Paperback – 6 oct 2016
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.
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Specificații

ISBN-13: 9783319363448
ISBN-10: 3319363441
Pagini: 232
Ilustrații: IX, 219 p. 63 illus., 51 illus. in color.
Dimensiuni: 155 x 235 x 13 mm
Greutate: 0.36 kg
Ediția:Softcover reprint of the original 1st edition 2014
Editura: Springer
Locul publicării:Cham, Switzerland

Cuprins

I. Network analysis.- II. Clinical applications.- III. Tractography.- IV. Q-space reconstruction.- V. Post-processing.

Textul de pe ultima copertă

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.

Caracteristici

Contains papers presented at the 2014 MICCAI Workshop on Computational Diffusion MRI, CDMRI’14 Details new computational methods applied to diffusion magnetic resonance imaging data Contributions include both careful mathematical derivations and a large number of rich full-color visualizations Includes supplementary material: sn.pub/extras