Abstract #2002

Evaluation of Diffusion MRI Based Feature Sets for the Classification of Primary Motor and Somatosensory Cortical Areas.

Tara Ganepola^1,2, Jiaying Zhang², Hui Zhang², Martin I Sereno³, and Daniel C Alexander²

¹Department of Cognitive, Perceptual and Brain Sciences, University College London, London, United Kingdom, ²Centre for Medical Image Computing, University College London, London, United Kingdom, ³Birkbeck-UCL Centre for Neuroimaging, University College London, London, United Kingdom

In the following work several diffusion based feature vectors (DTI, NODDI, spherical harmonic (SH) invariants and fourth order tensor invariants (T4)) are compared in order to validate their usability in grey matter investigations. It was found that using multi-shell data and non-biophysical models such as SH and T4 achieves the highest classification accuracy between the primary motor and somatosensory cortical areas, and thus is likely to characterise grey matter tissues domains more effectively.

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