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Computational Diffusion MRI

MICCAI Workshop, Boston, MA, USA, September 2014

  • Conference proceedings
  • © 2014

Overview

Editors:
  1. Lauren O'Donnell

    1. Harvard Medical School Brigham and Women's Hospital, Boston, USA

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  2. Gemma Nedjati-Gilani

    1. Dept. of Computer Science, University College London Dept of Computer Science, London, United Kingdom

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  3. Yogesh Rathi

    1. Harvard Medical School Brigham and Women's Hospital, Boston, USA

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  4. Marco Reisert

    1. University Medical Center Freiburg Department of Radiology, Freiburg, Germany

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  5. Torben Schneider

    1. Queen Square Multiple Sclerosis Centre, UCL Institute of Neurology, Queen Square House, Queen Square, London, United Kingdom

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  • 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

Part of the book series: Mathematics and Visualization (MATHVISUAL)

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Table of contents (18 papers)

  1. Front Matter

    Pages i-ix
    Download chapter PDF

  2. Network Analysis

    1. Front Matter

      Pages 1-1
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    2. Vector Weights and Dual Graphs: An Emphasis on Connections in Brain Network Analysis

      • Peter Savadjiev, Carl-Fredrik Westin, Yogesh Rathi
      Pages 3-12

    3. Rich Club Network Analysis Shows Distinct Patterns of Disruption in Frontotemporal Dementia and Alzheimer’s Disease

      • Madelaine Daianu, Neda Jahanshad, Julio E. Villalon-Reina, Mario F. Mendez, George Bartzokis, Elvira E. Jimenez et al.
      Pages 13-22

    4. Parcellation-Independent Multi-Scale Framework for Brain Network Analysis

      • M. D. Schirmer, G. Ball, S. J. Counsell, A. D. Edwards, D. Rueckert, J. V. Hajnal et al.
      Pages 23-32

  3. Clinical Applications

    1. Front Matter

      Pages 33-33
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    2. Multiple Stages Classification of Alzheimer’s Disease Based on Structural Brain Networks Using Generalized Low Rank Approximations (GLRAM)

      • L. Zhan, Z. Nie, J. Ye, Y. Wang, Y. Jin, N. Jahanshad et al.
      Pages 35-44

    3. The Added Value of Diffusion Tensor Imaging for Automated White Matter Hyperintensity Segmentation

      • Hugo J. Kuijf, Chantal M. W. Tax, L. Karlijn Zaanen, Willem H. Bouvy, Jeroen de Bresser, Alexander Leemans et al.
      Pages 45-53

    4. Algebraic Connectivity of Brain Networks Shows Patterns of Segregation Leading to Reduced Network Robustness in Alzheimer’s Disease

      • Madelaine Daianu, Neda Jahanshad, Talia M. Nir, Cassandra D. Leonardo, Clifford R. Jack Jr., Michael W. Weiner et al.
      Pages 55-64

    5. Diffusion-Map: A Novel Visualizing Biomarker for Diffusion Tensor Imaging of Human Brain White Matter

      • Mohammad Hadi Aarabi, Hamid Saligheh Rad
      Pages 65-77

    6. A Multi-Parametric Diffusion Magnetic Resonance Imaging Texture Feature Model for Prostate Cancer Analysis

      • Farzad Khalvati, Amen Modhafar, Andrew Cameron, Alexander Wong, Masoom A. Haider
      Pages 79-88

    7. Predicting Poststroke Depression from Brain Connectivity

      • J. Mitra, K.-K. Shen, S. Ghose, P. Bourgeat, J. Fripp, O. Salvado et al.
      Pages 89-99

  4. Tractography

    1. Front Matter

      Pages 101-101
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    2. Fiber Bundle Segmentation Using Spectral Embedding and Supervised Learning

      • Dorothée Vercruysse, Daan Christiaens, Frederik Maes, Stefan Sunaert, Paul Suetens
      Pages 103-114

    3. Atlas-Guided Global Tractography: Imposing a Prior on the Local Track Orientation

      • Daan Christiaens, Marco Reisert, Thijs Dhollander, Frederik Maes, Stefan Sunaert, Paul Suetens
      Pages 115-123

  5. Q-space Reconstruction

    1. Front Matter

      Pages 125-125
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    2. Magnitude and Complex Based Diffusion Signal Reconstruction

      • Marco Pizzolato, Aurobrata Ghosh, Timothé Boutelier, Rachid Deriche
      Pages 127-140

    3. Diffusion Propagator Estimation Using Gaussians Scattered in q-Space

      • Lipeng Ning, Oleg Michailovich, Carl-Fredrik Westin, Yogesh Rathi
      Pages 141-150

    4. An Analytical 3D Laplacian Regularized SHORE Basis and Its Impact on EAP Reconstruction and Microstructure Recovery

      • Rutger Fick, Demian Wassermann, Gonzalo Sanguinetti, Rachid Deriche
      Pages 151-165

  6. Post-processing

    1. Front Matter

      Pages 167-167
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Keywords

About this book

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.

Editors and Affiliations

  • Harvard Medical School Brigham and Women's Hospital, Boston, USA

    Lauren O'Donnell, Yogesh Rathi

  • Dept. of Computer Science, University College London Dept of Computer Science, London, United Kingdom

    Gemma Nedjati-Gilani

  • University Medical Center Freiburg Department of Radiology, Freiburg, Germany

    Marco Reisert

  • Queen Square Multiple Sclerosis Centre, UCL Institute of Neurology, Queen Square House, Queen Square, London, United Kingdom

    Torben Schneider

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