Computational Diffusion MRI

MICCAI Workshop, Québec, Canada, September 2017

  • Enrico Kaden
  • Francesco Grussu
  • Lipeng Ning
  • Chantal M. W. Tax
  • Jelle Veraart
Conference proceedings

Part of the Mathematics and Visualization book series (MATHVISUAL)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Data Acquisition and Modeling

    1. Front Matter
      Pages 1-1
    2. Evan Schwab, René Vidal, Nicolas Charon
      Pages 21-35
    3. Patryk Filipiak, Rutger Fick, Alexandra Petiet, Mathieu Santin, Anne-Charlotte Philippe, Stephane Lehericy et al.
      Pages 37-49
    4. Mauro Zucchelli, Maxime Descoteaux, Gloria Menegaz
      Pages 51-63
  3. Image Postprocessing

    1. Front Matter
      Pages 65-65
    2. Robert I. Reid, Zuzana Nedelska, Christopher G. Schwarz, Chadwick Ward, Clifford R. Jack Jr., The Alzheimer’s Disease Neuroimaging Initiative
      Pages 67-80
    3. Kévin Ginsburger, Fabrice Poupon, Achille Teillac, Jean-Francois Mangin, Cyril Poupon
      Pages 81-90
    4. Laurent Chauvin, Kuldeep Kumar, Christian Desrosiers, Jacques De Guise, Matthew Toews
      Pages 91-99
  4. Tractography and Connectivity

    1. Front Matter
      Pages 101-101
    2. Daniel Jörgens, Örjan Smedby, Rodrigo Moreno
      Pages 103-116
    3. Edwin Versteeg, Frans M. Vos, Gert Kwakkel, Frans C. T. van der Helm, Joor A. M. Arkesteijn, Olena Filatova
      Pages 117-128
    4. Francois Rheault, Etienne St-Onge, Jasmeen Sidhu, Quentin Chenot, Laurent Petit, Maxime Descoteaux
      Pages 129-139
    5. Michael Ankele, Thomas Schultz
      Pages 141-154
    6. Chendi Wang, Bernard Ng, Alborz Amir-Khalili, Rafeef Abugharbieh
      Pages 155-164
    7. Hamza Farooq, Yongxin Chen, Tryphon Georgiou, Christophe Lenglet
      Pages 165-174
    8. Silvia Obertino, Sofía Jiménez Hernández, Ilaria Boscolo Galazzo, Francesca Benedetta Pizzini, Mauro Zucchelli, Gloria Menegaz
      Pages 175-188
  5. Clinical Applications

    1. Front Matter
      Pages 189-189

About these proceedings

Introduction

This volume presents the latest developments in the highly active and rapidly growing field of diffusion MRI. The reader will find numerous contributions covering 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 frontline applications in neuroscience research and clinical practice.

These proceedings contain the papers presented at the 2017 MICCAI Workshop on Computational Diffusion MRI (CDMRI’17) held in Québec, Canada on September 10, 2017, sharing new perspectives on the most recent research challenges for those currently working in the field, but also offering a valuable starting point for anyone interested in learning computational techniques in diffusion MRI. This book includes rigorous mathematical derivations, a large number of rich, 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.

Keywords

brain network analysis connectomics fibre tractography high angular resolution diffusion imaging image and signal processing inverse problems medical image analysis medical visualisation microstructure imaging neuroimaging

Editors and affiliations

  • Enrico Kaden
    • 1
  • Francesco Grussu
    • 2
  • Lipeng Ning
    • 3
  • Chantal M. W. Tax
    • 4
  • Jelle Veraart
    • 5
  1. 1.Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUnited Kingdom
  2. 2.Institute of Neurology, Faculty of Brain SciencesUniversity College LondonLondonUnited Kingdom
  3. 3.Psychiatry Neuroimaging Laboratory, Brigham and Women’s HospitalHarvard Medical SchoolBostonUSA
  4. 4.Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffUnited Kingdom
  5. 5.Center for Biomedical ImagingNew York University School of MedicineNew YorkUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-73839-0
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-73838-3
  • Online ISBN 978-3-319-73839-0
  • Series Print ISSN 1612-3786
  • Series Online ISSN 2197-666X
  • About this book
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