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Evaluation of diffusion MRI based feature sets for the classification of primary motor and somatosensory cortical areas

Ganepola, T; Zhang, J; Zhang, H; Sereno, M; Alexander, D; (2016) Evaluation of diffusion MRI based feature sets for the classification of primary motor and somatosensory cortical areas. In: Proceedings of the ISMRM 24th Annual Meeting & Exhibition. International Society for Magnetic Resonance Imaging: Singapore. Green open access

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Abstract

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.

Type: Proceedings paper
Title: Evaluation of diffusion MRI based feature sets for the classification of primary motor and somatosensory cortical areas
Event: ISMRM 24th Annual Meeting & Exhibition
Location: Singapore
Open access status: An open access version is available from UCL Discovery
Publisher version: http://www.ismrm.org/16/program_files/TP07.htm
Language: English
UCL classification: UCL
UCL > Provost and Vice Provost Offices
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/1475010
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