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Improved Functional MRI Activation Mapping in White Matter Through Diffusion-Adapted Spatial Filtering
Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering.
Centre for Mathematical Sciences, Lund University, Sweden.
Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning.
Department of Biomedical Engineering, Lund University, Sweden.
2020 (English)In: ISBI 2020: IEEE International Symposium on Biomedical Imaging, IEEE, 2020Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
IEEE, 2020.
Series
IEEE International Symposium on Biomedical Imaging, ISSN 1945-7928, E-ISSN 1945-8452
Keywords [en]
functional MRI, diffusion MRI, white matter, adaptive filtering
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:liu:diva-165857DOI: 10.1109/ISBI45749.2020.9098582ISI: 000578080300102ISBN: 978-1-5386-9330-8 (electronic)OAI: oai:DiVA.org:liu-165857DiVA, id: diva2:1433272
Conference
IEEE 17th International Symposium on Biomedical Imaging (ISBI), Iowa City, IA, USA, 3-7 April 2020
Funder
Swedish Research Council, 2017- 04889Swedish Research Council, 2018-06689
Note

Funding agencies: Swedish Research CouncilSwedish Research Council [2018-06689, 2017-04889]; Center for Industrial Information Technology (CENIIT) at Linkoping University; Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation

Available from: 2020-05-29 Created: 2020-05-29 Last updated: 2020-10-31Bibliographically approved

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Abramian, DavidEklund, Anders

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