Editors:
- Contributions on new important topics that are gaining momentum within the diffusion MRI community
- Details new computational methods and estimation techniques for microstructure imaging and brain connectivity mapping
- Features papers presented at the 2018 MICCAI Workshop on Computational Diffusion MRI (CDMRI’18)
Part of the book series: Mathematics and Visualization (MATHVISUAL)
Conference series link(s): MICCAI: International Conference on Medical Image Computing and Computer-Assisted Intervention
Conference proceedings info: MICCAI 2019.
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (31 papers)
-
Front Matter
-
Diffusion MRI Signal Acquisition and Processing Strategies
-
Front Matter
-
-
Machine Learning for Diffusion MRI
-
Front Matter
-
-
Diffusion MRI Signal Harmonization
-
Front Matter
-
Other Volumes
-
Computational Diffusion MRI
About this book
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.
Keywords
- diffusion MRI
- computational techniques
- medical image computing
- medical visualization
- image acquisition
- image registration
- image reconstruction
- image analysis
- image and signal processing
- machine learning
- brain MRI
- neuroimaging
- connectomics
- fibre tractography
- body MRI
- microsturcture imaging
- signal modelling
- parameter estimation
Editors and Affiliations
-
Centre for Medical Image Computing, University College London, London, UK
Elisenda Bonet-Carne
-
Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
Francesco Grussu
-
Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
Lipeng Ning
-
Laboratory of Neuro Imaging (LONI), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, USA
Farshid Sepehrband
-
Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK
Chantal M. W. Tax
Bibliographic Information
Book Title: Computational Diffusion MRI
Book Subtitle: International MICCAI Workshop, Granada, Spain, September 2018
Editors: Elisenda Bonet-Carne, Francesco Grussu, Lipeng Ning, Farshid Sepehrband, Chantal M. W. Tax
Series Title: Mathematics and Visualization
DOI: https://doi.org/10.1007/978-3-030-05831-9
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-05830-2Published: 07 June 2019
eBook ISBN: 978-3-030-05831-9Published: 17 May 2019
Series ISSN: 1612-3786
Series E-ISSN: 2197-666X
Edition Number: 1
Number of Pages: XII, 390
Number of Illustrations: 17 b/w illustrations, 109 illustrations in colour
Topics: Mathematical and Computational Biology, Numeric Computing, Math Applications in Computer Science, Image Processing and Computer Vision, Simulation and Modeling, Artificial Intelligence