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Measurement tensors in diffusion MRI: generalizing the concept of diffusion encoding

Westin, Carl-Fredrik ; Szczepankiewicz, Filip LU orcid ; Pasternak, Ofer ; Ozarslan, Evren ; Topgaard, Daniel LU ; Knutsson, Hans and Nilsson, Markus LU (2014) In Lecture Notes in Computer Science 17(Pt 3). p.16-209
Abstract

In traditional diffusion MRI, short pulsed field gradients (PFG) are used for the diffusion encoding. The standard Stejskal-Tanner sequence uses one single pair of such gradients, known as single-PFG (sPFG). In this work we describe how trajectories in q-space can be used for diffusion encoding. We discuss how such encoding enables the extension of the well-known scalar b-value to a tensor-valued entity we call the diffusion measurement tensor. The new measurements contain information about higher order diffusion propagator covariances not present in sPFG. As an example analysis, we use this new information to estimate a Gaussian distribution over diffusion tensors in each voxel, described by its mean (a diffusion tensor) and its... (More)

In traditional diffusion MRI, short pulsed field gradients (PFG) are used for the diffusion encoding. The standard Stejskal-Tanner sequence uses one single pair of such gradients, known as single-PFG (sPFG). In this work we describe how trajectories in q-space can be used for diffusion encoding. We discuss how such encoding enables the extension of the well-known scalar b-value to a tensor-valued entity we call the diffusion measurement tensor. The new measurements contain information about higher order diffusion propagator covariances not present in sPFG. As an example analysis, we use this new information to estimate a Gaussian distribution over diffusion tensors in each voxel, described by its mean (a diffusion tensor) and its covariance (a 4th order tensor).

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author
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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Algorithms, Brain, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Information Storage and Retrieval, Nerve Fibers, Myelinated, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity
in
Lecture Notes in Computer Science
volume
17
issue
Pt 3
pages
8 pages
publisher
Springer
external identifiers
  • pmid:25320801
  • scopus:84906968830
ISSN
1611-3349
DOI
10.1007/978-3-319-10443-0_27
language
English
LU publication?
yes
id
9b80b5d9-e377-4a67-b680-d5d0fb344151
alternative location
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4386881/pdf/nihms676739.pdf
date added to LUP
2016-04-11 14:06:21
date last changed
2025-01-11 00:43:53
@article{9b80b5d9-e377-4a67-b680-d5d0fb344151,
  abstract     = {{<p>In traditional diffusion MRI, short pulsed field gradients (PFG) are used for the diffusion encoding. The standard Stejskal-Tanner sequence uses one single pair of such gradients, known as single-PFG (sPFG). In this work we describe how trajectories in q-space can be used for diffusion encoding. We discuss how such encoding enables the extension of the well-known scalar b-value to a tensor-valued entity we call the diffusion measurement tensor. The new measurements contain information about higher order diffusion propagator covariances not present in sPFG. As an example analysis, we use this new information to estimate a Gaussian distribution over diffusion tensors in each voxel, described by its mean (a diffusion tensor) and its covariance (a 4th order tensor).</p>}},
  author       = {{Westin, Carl-Fredrik and Szczepankiewicz, Filip and Pasternak, Ofer and Ozarslan, Evren and Topgaard, Daniel and Knutsson, Hans and Nilsson, Markus}},
  issn         = {{1611-3349}},
  keywords     = {{Algorithms; Brain; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Nerve Fibers, Myelinated; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity}},
  language     = {{eng}},
  number       = {{Pt 3}},
  pages        = {{16--209}},
  publisher    = {{Springer}},
  series       = {{Lecture Notes in Computer Science}},
  title        = {{Measurement tensors in diffusion MRI: generalizing the concept of diffusion encoding}},
  url          = {{http://dx.doi.org/10.1007/978-3-319-10443-0_27}},
  doi          = {{10.1007/978-3-319-10443-0_27}},
  volume       = {{17}},
  year         = {{2014}},
}