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Herausgeber: 
  • Francesco Grussu
  • Lipeng Ning
  • Chantal M. W. Tax
  • Elisenda Bonet-Carne
  • Farshid Sepehrband
  • Computational Diffusion MRI: International MICCAI Workshop, Granada, Spain, September 2018 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Juni 2019  
    Genre:  Schulbücher 
     
    Artificial Intelligence / Biomathematics / C / Computer modelling & simulation / computer science / Computer science—Mathematics / Computer simulation / Computer Vision
    ISBN:  9783030058302 
    EAN-Code: 
    9783030058302 
    Verlag:  Springer EN 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Mathematics and Visualization  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  763 gr 
    Seiten:  390 
    Illustration:  XII, 390 p. 126 illus., 109 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This volume gathers papers presented at the Workshop on Computational Diffusion MRI (CDMRI'18), which was held under the auspices of the International Conference on Medical Image Computing and Computer Assisted Intervention in Granada, Spain on September 20, 2018. 
    It presents the latest developments in the highly active and rapidly growing field of diffusion MRI. The reader will find papers on a broad range of topics, from the mathematical foundations of the diffusion process and signal generation, to new computational methods and estimation techniques for the in-vivo recovery of microstructural and connectivity features, as well as harmonisation and frontline applications in research and clinical practice. The respective papers constitute invited works from high-profile researchers with a specific focus on three topics that are now gaining momentum within the diffusion MRI community: i) machine learning for diffusion MRI; ii) diffusion MRI outside the brain (e.g. in the placenta); and iii) diffusion MRI for multimodal imaging. 
    The book shares new perspectives on the latest research challenges for those currently working in the field, but also offers a valuable starting point for anyone interested in learning computational techniques in diffusion MRI. It includes rigorous mathematical derivations, a wealth of full-colour visualisations, and clinically relevant results. As such, it will be of interest to researchers and practitioners in the fields of computer science, MRI physics and applied mathematics alike. 
      



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