Skip to main content
SpringerLink
Log in

Computational Diffusion MRI

International MICCAI Workshop, Lima, Peru, October 2020

  • Conference proceedings
  • © 2021

Overview

Editors:
  1. Noemi Gyori

    1. University College London, London, UK

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Jana Hutter

    1. Centre for Medical Engineering, King's College London, London, UK

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  3. Vishwesh Nath

    1. Nvidia, Nashville, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  4. Marco Palombo

    1. University College London, London, UK

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  5. Marco Pizzolato

    1. Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  6. Fan Zhang

    1. Laboratory of Mathematics in Imaging, Harvard Medical School, Boston, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Presents the latest developments in the highly active and rapidly growing field of diffusion MRI
  • Covers a broad range of topics, from the mathematical foundations of the diffusion process and signal acquisition, to new computational methods and estimation techniques for the in-vivo recovery of microstructural and connectivity features, as well as diffusion-relaxometry and frontline applications in research and clinical practice

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

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (23 papers)

  1. Front Matter

    Pages i-xi
    Download chapter PDF

  2. Diffusion MRI Signal Acquisition

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Image Reconstruction from Accelerated Slice-Interleaved Diffusion Encoding Data

      • Tiantian Xu, Ye Wu, Yoonmi Hong, Khoi Minh Huynh, Weili Lin, Wei-Tang Chang et al.
      Pages 3-12

    3. Towards Learned Optimal q-Space Sampling in Diffusion MRI

      • Tomer Weiss, Sanketh Vedula, Ortal Senouf, Oleg Michailovich, Alex Bronstein
      Pages 13-28

    4. A Signal Peak Separation Index for Axisymmetric B-Tensor Encoding

      • Gaëtan Rensonnet, Jonathan Rafael-Patiño, Benoît Macq, Jean-Philippe Thiran, Gabriel Girard, Marco Pizzolato
      Pages 29-42

  3. Orientation Processing: Tractography and Visualization

    1. Front Matter

      Pages 43-43
      Download chapter PDF

    2. Improving Tractography Accuracy Using Dynamic Filtering

      • Matteo Battocchio, Simona Schiavi, Maxime Descoteaux, Alessandro Daducci
      Pages 45-54

    3. Diffeomorphic Alignment of Along-Tract Diffusion Profiles from Tractography

      • David S. Lee, Ashish Sahib, Antoni Kubicki, Katherine L. Narr, Roger P. Woods, Shantanu H. Joshi
      Pages 55-67

    4. Direct Reconstruction of Crossing Muscle Fibers in the Human Tongue Using a Deep Neural Network

      • Muhan Shao, Aaron Carass, Arnold D. Gomez, Jiachen Zhuo, Xiao Liang, Maureen Stone et al.
      Pages 69-80

    5. Learning Anatomical Segmentations for Tractography  from Diffusion MRI

      • Christian Ewert, David Kügler, Anastasia Yendiki, Martin Reuter
      Pages 81-93

    6. Diffusion MRI Fiber Orientation Distribution Function Estimation Using Voxel-Wise Spherical U-Net

      • Sara Sedlar, Théodore Papadopoulo, Rachid Deriche, Samuel Deslauriers-Gauthier
      Pages 95-106

  4. Microstructure Modeling and Representation

    1. Front Matter

      Pages 107-107
      Download chapter PDF

    2. Stick Stippling for Joint 3D Visualization of Diffusion MRI Fiber Orientations and Density

      • Ryan P. Cabeen, David H. Laidlaw, Arthur W. Toga
      Pages 109-119

    3. Q-Space Quantitative Diffusion MRI Measures Using a Stretched-Exponential Representation

      • Tomasz Pieciak, Maryam Afzali, Fabian Bogusz, Santiago Aja-Fernández, Derek K. Jones
      Pages 121-133

    4. Repeatability of Soma and Neurite Metrics in Cortical and Subcortical Grey Matter

      • Sila Genc, Maxime Chamberland, Kristin Koller, Chantal M. W. Tax, Hui Zhang, Marco Palombo et al.
      Pages 135-145

    5. DW-MRI Microstructure Model of Models Captured Via Single-Shell Bottleneck Deep Learning

      • Vishwesh Nath, Karthik Ramadass, Kurt G. Schilling, Colin B. Hansen, Rutger Fick, Sudhir K. Pathak et al.
      Pages 147-157

    6. Deep Learning Model Fitting for Diffusion-Relaxometry: A Comparative Study

      • Francesco Grussu, Marco Battiston, Marco Palombo, Torben Schneider, Claudia A. M. Gandini Wheeler-Kingshott, Daniel C. Alexander
      Pages 159-172

    7. Pretraining Improves Deep Learning Based Tissue Microstructure Estimation

      • Yuxing Li, Yu Qin, Zhiwen Liu, Chuyang Ye
      Pages 173-185

  5. Signal Augmentation and Super Resolution

    1. Front Matter

      Pages 187-187
      Download chapter PDF

    2. Enhancing Diffusion Signal Augmentation Using Spherical Convolutions

      • Simon Koppers, Dorit Merhof
      Pages 189-200
Back to top

Keywords

About this book

This book gathers papers presented at the Workshop on Computational Diffusion MRI, CDMRI 2020, held under the auspices of the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), which took place virtually on October 8th, 2020, having originally been planned to take place in Lima, Peru.

This book presents the latest developments in the highly active and rapidly growing field of diffusion MRI. While offering new perspectives on the most recent research challenges in the field, the selected articles also provide a valuable starting point for anyone interested in learning computational techniques for diffusion MRI. The book includes rigorous mathematical derivations, a large number of rich, full-colour visualizations, and clinically relevant results. As such, it is of interest to researchers and practitioners in the fields of computer science, MRI physics, and applied mathematics. The reader will find numerous contributions coveringa 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 diffusion-relaxometry and frontline applications in research and clinical practice.


Editors and Affiliations

  • University College London, London, UK

    Noemi Gyori, Marco Palombo

  • Centre for Medical Engineering, King's College London, London, UK

    Jana Hutter

  • Nvidia, Nashville, USA

    Vishwesh Nath

  • Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark

    Marco Pizzolato

  • Laboratory of Mathematics in Imaging, Harvard Medical School, Boston, USA

    Fan Zhang

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation