Improved Functional MRI Activation Mapping in White Matter Through Diffusion-Adapted Spatial Filtering
(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.
(Less)
- author
- Abramian, David ; Larsson, Martin LU ; Eklund, Anders and Behjat, Hamid LU
- organization
- publishing date
- 2020-04
- 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
- 1945-7928
- 1945-8452
- 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
- 2024-09-19 13:30:51
@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 = {{1945-7928}}, 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}}, }