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Spectral Characterization of Functional MRI Data on Voxel-Resolution Cortical Graphs
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- Behjat, Hamid (author)
- Lund University,Lunds universitet,Avdelningen för Biomedicinsk teknik,Institutionen för biomedicinsk teknik,Institutioner vid LTH,Lunds Tekniska Högskola,Department of Biomedical Engineering,Departments at LTH,Faculty of Engineering, LTH
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- Larsson, Martin (author)
- Lund University,Lunds universitet,Matematik LTH,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Mathematics (Faculty of Engineering),Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH
- (creator_code:org_t)
- 2020
- 2020
- English 5 s.
- In: ISBI 2020 - 2020 IEEE International Symposium on Biomedical Imaging. - 1945-7928 .- 1945-8452. - 9781538693308 ; 2020-April, s. 558-562
- Conference paper (peer-reviewed)
Abstract
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- The human cortical layer exhibits a convoluted morphology that is unique to each individual. Conventional volumetric fMRI processing schemes take for granted the rich information provided by the underlying anatomy. We present a method to study fMRI data on subject-specific cerebral hemisphere cortex (CHC) graphs, which encode the cortical morphology at the resolution of voxels in 3-D. Using graph signal processing principles, we study spectral energy metrics associated to fMRI data, on 100 subjects from the Human Connectome Project database, across seven tasks. Experimental results signify the strength of CHC graphs' Laplacian eigenvector bases in capturing subtle spatial patterns specific to different functional loads as well as to sets of experimental conditions within each task.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)
Keyword
- cortical morphology
- functional MRI
- graph signal processing
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