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Abstract #4416

Towards in-vivo voxel-wise parcellation of human brain cortex

Shahrzad Moeiniyan Bagheri1, Viktor Vegh1, and David Reutens1

1Centre for Advanced Imaging, The University of Queensland, St Lucia, Australia

The research aims to establish the feasibility of developing an automated method for in vivo voxel-wise parcellation of the human brain cortex. We combined our previously proposed residual analysis Magnetic Resonance Fingerprinting (MRF) approach with supervised classification. We show that extraction of a feature vector from a patch of voxels about a voxel of interest improves prediction accuracy by about 10%, as measured using the Area Under the Curve (AUC) metric. Our approach leads to an increase in the prediction accuracy rate for areas of distinct microstructural heterogeneity, such as the primary motor cortex.

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