Computational Diffusion MRI and Brain Connectivity

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106,99 

MICCAI Workshops, Nagoya, Japan, September 22nd, 2013, Mathematics and Visualization

ISBN: 3319376845
ISBN 13: 9783319376844
Herausgeber: Thomas Schultz/Gemma Nedjati-Gilani/Archana Venkataraman et al
Verlag: Springer Verlag GmbH
Umfang: xiv, 255 S., 11 s/w Illustr., 67 farbige Illustr., 255 p. 78 illus., 67 illus. in color.
Erscheinungsdatum: 23.08.2016
Auflage: 1/2014
Produktform: Kartoniert
Einband: Kartoniert

This volume contains the proceedings from two closely related workshops: Computational Diffusion MRI (CDMRI’13) and Mathematical Methods from Brain Connectivity (MMBC’13), held under the auspices of the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, which took place in Nagoya, Japan, September 2013.Inside, readers will find contributions ranging from mathematical foundations and novel methods for the validation of inferring large-scale connectivity from neuroimaging data to the statistical analysis of the data, accelerated methods for data acquisition, and the most recent developments on mathematical diffusion modeling.This volume offers a valuable starting point for anyone interested in learning computational diffusion MRI and mathematical methods for brain connectivity as well as offers new perspectives and insights on current research challenges for those currently in the field. It will be of interest to researchers and practitioners in computer science, MR physics, and applied mathematics.

Artikelnummer: 9701203 Kategorie:

Beschreibung

This volume contains the proceedings from two closely related workshops: Computational Diffusion MRI (CDMRI13) and Mathematical Methods from Brain Connectivity (MMBC13), held under the auspices of the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, which took place in Nagoya, Japan, September 2013.Inside, readers will find contributions ranging from mathematical foundations and novel methods for the validation of inferring large-scale connectivity from neuroimaging data to the statistical analysis of the data, accelerated methods for data acquisition, and the most recent developments on mathematical diffusion modeling. This volume offers a valuable starting point for anyone interested in learning computational diffusion MRI and mathematical methods for brain connectivity as well as offers new perspectives and insights on current research challenges for those currently in the field. It will be of interest to researchers and practitioners in computer science, MR physics, and applied mathematics.

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E-Mail: juergen.hartmann@springer.com

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