Skip to main content
SpringerLink
Log in
Book cover

Computational Diffusion MRI

MICCAI Workshop, Shenzhen, China, October 2019

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Elisenda Bonet-Carne

    1. Centre for Medical Imaging and Centre for Medical Image Computing, 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. Marco Palombo

    1. Centre for Medical Image Computing, University College London, London, UK

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  4. Marco Pizzolato

    1. Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  5. Farshid Sepehrband

    1. Laboratory of Neuro Imaging (LONI), University of Southern California, Los Angeles, USA

    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

  • Contributions on new important topics that are gaining momentum within the diffusion MRI community
  • Careful mathematical derivations and large number of rich full-color visualizations
  • Biologically or clinically relevant results

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 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 169.99
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 (17 papers)

  1. Front Matter

    Pages i-xi
    Download chapter PDF

  2. Diffusion MRI Signal Acquisition and Processing Strategies

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Connectome 2.0: Cutting-Edge Hardware Ushers in New Opportunities for Computational Diffusion MRI

      • Anastasia Yendiki, Thomas Witzel, Susie Y. Huang
      Pages 3-12

    3. Alternative Diffusion Anisotropy Metric from Reduced MRI Acquisitions

      • Santiago Aja-Fernández, Antonio Tristán-Vega, Rodrigo de Luis-García, Derek K. Jones
      Pages 13-24

    4. Optimized Response Function Estimation for Spherical Deconvolution

      • Tom Dela Haije, Aasa Feragen
      Pages 25-34

    5. Optimal Fiber Diffusion Model Restoration

      • Clint Greene, Kate Revill, Cathrin Buetefisch, Ken Rose, Scott Grafton
      Pages 35-47

    6. Diffusion Anisotropy Identification by Short Diffusion-Diffusion Correlation Spectroscopy

      • Fangrong Zong, Yan Zhuo, Natasha Spindler, Huabing Liu, Petrik Galvosas
      Pages 49-59

  3. Machine Learning for Diffusion MRI

    1. Front Matter

      Pages 61-61
      Download chapter PDF

    2. Current Challenges and Future Directions in Diffusion MRI: From Model- to Data- Driven Analysis

      • Kurt G. Schilling, Baxter Rogers, Adam W. Anderson, Bennett A. Landman
      Pages 63-78

    3. Spatial Sparse Estimation of Fiber Orientation Distribution Using Deep Alternating Directions Method of Multipliers Network

      • Ridho Akbar, Yuanjing Feng, Fan Zhang, Jianzhong He, Qingrun Zeng, Lipeng Ning et al.
      Pages 79-89

    4. Free-Water Correction in Diffusion MRI: A Reliable and Robust Learning Approach

      • Leon Weninger, Simon Koppers, Chuh-Hyoun Na, Kerstin Juetten, Dorit Merhof
      Pages 91-99

    5. Convolutional Neural Networks for Fiber Orientation Distribution Enhancement to Improve Single-Shell Diffusion MRI Tractography

      • Oeslle Lucena, Sjoerd B. Vos, Vejay Vakharia, John Duncan, Sebastien Ourselin, Rachel Sparks
      Pages 101-112

    6. q-Space Novelty Detection with Variational Autoencoders

      • Aleksei Vasilev, Vladimir Golkov, Marc Meissner, Ilona Lipp, Eleonora Sgarlata, Valentina Tomassini et al.
      Pages 113-124

    7. DWI Simulation-Assisted Machine Learning Models for Microstructure Estimation

      • Jonathan Rafael-Patino, Thomas Yu, Victor Delvigne, Muhamed Barakovic, Marco Pizzolato, Gabriel Girard et al.
      Pages 125-134

    8. Convolutional Neural Network on DTI Data for Sub-cortical Brain Structure Segmentation

      • G. R. Pinheiro, D. S. Carmo, C. Yasuda, R. A. Lotufo, L. Rittner
      Pages 135-146

  4. Diffusion MRI Outside the Brain and Clinical Applications

    1. Front Matter

      Pages 147-147
      Download chapter PDF

    2. A Framework to Construct a Longitudinal DW-MRI Infant Atlas Based on Mixed Effects Modeling of dODF Coefficients

      • Heejong Kim, Martin Styner, Joseph Piven, Guido Gerig
      Pages 149-159

    3. Investigation of Changes in Anomalous Diffusion Parameters in a Mouse Model of Brain Tumour

      • Qianqian Yang, Simon Puttick, Zara C. Bruce, Bryan W. Day, Viktor Vegh
      Pages 161-172

    4. A Network-Based Analysis of the Preterm Adolescent Brain Using PCA and Graph Theory

      • Hassna Irzan, Michael Hütel, Carla Semedo, Helen O’Reilly, Manisha Sahota, Sebastien Ourselin et al.
      Pages 173-181

    5. Diffusion MRI Fiber Tractography by Flow Field Formation with Extended Physarum Solver: A Pilot Study with 2D Phantoms

      • Yoshitaka Masutani
      Pages 183-192
Back to top

Keywords

About this book

This volume gathers papers presented at the Workshop on Computational Diffusion MRI (CDMRI 2019), held under the auspices of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), which took place in Shenzhen, China on October 17, 2019.

This book presents the latest advances in the rapidly expanding field of diffusion MRI. It 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 about computational techniques in diffusion MRI. The book includes rigorous mathematical derivations, a wealth of rich, full-colour visualisations and extensive 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. Readers will find 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 diffusion-relaxometry and frontline applications in research and clinical practice. This edition includes invited works from high-profile researchers with a specific focus on three new and important topics that are gaining momentum within the diffusion MRI community, including diffusion MRI signal acquisition and processing strategies, machine learning for diffusion MRI, and diffusion MRI outside the brain and clinical applications.



Editors and Affiliations

  • Centre for Medical Imaging and Centre for Medical Image Computing, University College London, London, UK

    Elisenda Bonet-Carne

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

    Jana Hutter

  • Centre for Medical Image Computing, University College London, London, UK

    Marco Palombo

  • Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Marco Pizzolato

  • Laboratory of Neuro Imaging (LONI), University of Southern California, Los Angeles, USA

    Farshid Sepehrband

  • 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