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Improved Functional MRI Activation Mapping in White Matter Through Diffusion-Adapted Spatial Filtering

Abramian, David ; Larsson, Martin LU orcid ; Eklund, Anders and Behjat, Hamid LU (2020) 17th IEEE International Symposium on Biomedical Imaging, ISBI 2020 In Proceedings - International Symposium on Biomedical Imaging 2020-April. p.539-543
Abstract

Brain activation mapping using functional MRI (fMRI) based on blood oxygenation level-dependent (BOLD) contrast has been conventionally focused on probing gray matter, the BOLD contrast in white matter having been generally disregarded. Recent results have provided evidence of the functional significance of the white matter BOLD signal, showing at the same time that its correlation structure is highly anisotropic, and related to the diffusion tensor in shape and orientation. This evidence suggests that conventional isotropic Gaussian filters are inadequate for denoising white matter fMRI data, since they are incapable of adapting to the complex anisotropic domain of white matter axonal connections. In this paper we explore a graph-based... (More)

Brain activation mapping using functional MRI (fMRI) based on blood oxygenation level-dependent (BOLD) contrast has been conventionally focused on probing gray matter, the BOLD contrast in white matter having been generally disregarded. Recent results have provided evidence of the functional significance of the white matter BOLD signal, showing at the same time that its correlation structure is highly anisotropic, and related to the diffusion tensor in shape and orientation. This evidence suggests that conventional isotropic Gaussian filters are inadequate for denoising white matter fMRI data, since they are incapable of adapting to the complex anisotropic domain of white matter axonal connections. In this paper we explore a graph-based description of the white matter developed from diffusion MRI data, which is capable of encoding the anisotropy of the domain. Based on this representation we design localized spatial filters that adapt to white matter structure by leveraging graph signal processing principles. The performance of the proposed filtering technique is evaluated on semi-synthetic data, where it shows potential for greater sensitivity and specificity in white matter activation mapping, compared to isotropic filtering.

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Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
adaptive filtering, diffusion MRI, functional MRI, white matter
host publication
ISBI 2020 - 2020 IEEE International Symposium on Biomedical Imaging
series title
Proceedings - International Symposium on Biomedical Imaging
volume
2020-April
article number
9098582
pages
5 pages
publisher
IEEE Computer Society
conference name
17th IEEE International Symposium on Biomedical Imaging, ISBI 2020
conference location
Iowa City, United States
conference dates
2020-04-03 - 2020-04-07
external identifiers
  • scopus:85085867329
ISSN
1945-8452
1945-7928
ISBN
9781538693308
DOI
10.1109/ISBI45749.2020.9098582
language
English
LU publication?
yes
id
55d4d7f2-d462-49be-a436-82c3c8cb070f
date added to LUP
2021-01-11 20:32:47
date last changed
2024-05-16 01:35:19
@inproceedings{55d4d7f2-d462-49be-a436-82c3c8cb070f,
  abstract     = {{<p>Brain activation mapping using functional MRI (fMRI) based on blood oxygenation level-dependent (BOLD) contrast has been conventionally focused on probing gray matter, the BOLD contrast in white matter having been generally disregarded. Recent results have provided evidence of the functional significance of the white matter BOLD signal, showing at the same time that its correlation structure is highly anisotropic, and related to the diffusion tensor in shape and orientation. This evidence suggests that conventional isotropic Gaussian filters are inadequate for denoising white matter fMRI data, since they are incapable of adapting to the complex anisotropic domain of white matter axonal connections. In this paper we explore a graph-based description of the white matter developed from diffusion MRI data, which is capable of encoding the anisotropy of the domain. Based on this representation we design localized spatial filters that adapt to white matter structure by leveraging graph signal processing principles. The performance of the proposed filtering technique is evaluated on semi-synthetic data, where it shows potential for greater sensitivity and specificity in white matter activation mapping, compared to isotropic filtering.</p>}},
  author       = {{Abramian, David and Larsson, Martin and Eklund, Anders and Behjat, Hamid}},
  booktitle    = {{ISBI 2020 - 2020 IEEE International Symposium on Biomedical Imaging}},
  isbn         = {{9781538693308}},
  issn         = {{1945-8452}},
  keywords     = {{adaptive filtering; diffusion MRI; functional MRI; white matter}},
  language     = {{eng}},
  pages        = {{539--543}},
  publisher    = {{IEEE Computer Society}},
  series       = {{Proceedings - International Symposium on Biomedical Imaging}},
  title        = {{Improved Functional MRI Activation Mapping in White Matter Through Diffusion-Adapted Spatial Filtering}},
  url          = {{http://dx.doi.org/10.1109/ISBI45749.2020.9098582}},
  doi          = {{10.1109/ISBI45749.2020.9098582}},
  volume       = {{2020-April}},
  year         = {{2020}},
}