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An Unsupervised Group Average Cortical Parcellation Using Diffusion MRI to Probe Cytoarchitecture

Ganepola, T; Nagy, Z; Alexander, DC; Sereno, MI; (2017) An Unsupervised Group Average Cortical Parcellation Using Diffusion MRI to Probe Cytoarchitecture. In: Fuster, A and Ghosh, A and Kaden, E and Rathi, Y and Reisert, M, (eds.) MICCAI 2016: Computational Diffusion MRI. (pp. pp. 145-156). Springer International Publishing: Cham, Switzerland.

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Abstract

Cortical parcellations provide valuable localisation resources for other neuroimaging modalities such as fMRI as well as insight into the structure-function relationship of the brain. The venerable but now dated ex vivo Brodmann map is currently being superseded by in vivo techniques that can better take into account intersubject variability. One popular in vivo method focusses on myeloarchitecture by measuring T1. This, however, probes only one aspect of cortical microstructure and is less useful in regions of low myelination. In contrast, diffusion MRI (dMRI) is sensitive to several additional microstructural features and can potentially provide a richer set of information regarding the architecture of grey matter microcircuitry. The following study used 3T HARDI data of multiple subjects to produce an entirely unsupervised, hemisphere-wide, group-average, parcellation. A qualitative assessment of the resulting cortical parcellation demonstrates several spatially coherent clusters in areas corresponding to well known functional anatomical areas. In addition, it exhibits some cluster boundaries that correlate with independently derived myelin mapping data for the same set of subjects, whilst also providing distinct clusters in areas (e.g., within MT+) where myelination is a less informative measurement.

Type: Proceedings paper
Title: An Unsupervised Group Average Cortical Parcellation Using Diffusion MRI to Probe Cytoarchitecture
Event: International Conference on Medical Image Computing and Computer-Assisted Intervention
ISBN-13: 9783319541297
DOI: 10.1007/978-3-319-54130-3_12
Publisher version: http://dx.doi.org/10.1007/978-3-319-54130-3_12
Language: English
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1559579
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