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Herausgeber: 
  • Thomas Schultz
  • Gemma Nedjati-Gilani
  • Lauren O'Donnell
  • Eleftheria Panagiotaki
  • Archana Venkataraman
  • Computational Diffusion MRI and Brain Connectivity: MICCAI Workshops, Nagoya, Japan, September 22nd, 2013 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  Januar 2014  
    Genre:  EDV / Informatik 
     
    Automated Pattern Recognition / C / Combinatorics & graph theory / Computational Science and Engineering / Computer mathematics / Computer Vision / Data and Information Visualization / Epidemiology & medical statistics / Image processing / Image Processing and Computer Vision / Mathematical physics / Mathematics / Mathematics and Statistics / Optical data processing / pattern recognition / Probability & statistics / Statistics / Statistics for Life Sciences, Medicine, Health Sciences / Statistics in Life Sciences, Medicine, Health Sciences / Theoretical, Mathematical and Computational Physics / Visualization
    ISBN:  9783319024745 
    EAN-Code: 
    9783319024745 
    Verlag:  Springer International Publishing 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Mathematics and Visualization  
    Dimensionen:  H 241 mm / B 160 mm / D 21 mm 
    Gewicht:  576 gr 
    Seiten:  272 
    Zus. Info:  HC runder Rücken kaschiert 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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.

      
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