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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 Quebec, 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.
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 Quebec, 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.
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Computational Diffusion MRI - International MICCAI Workshop, Granada, Spain, September 2018 (Hardcover, 1st ed. 2019)
Elisenda Bonet-Carne, Francesco Grussu, Lipeng Ning, Farshid Sepehrband, Chantal M.W. Tax
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This volume gathers papers presented at the Workshop on
Computational Diffusion MRI (CDMRI'18), which was held under the
auspices of the International Conference on Medical Image Computing
and Computer Assisted Intervention in Granada, Spain on September
20, 2018. 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.
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