Journal article

Normalisation of Neonatal Brain Network Measures Using Stochastic Approaches

Markus Schirmer, Gareth Ball, Serena J Counsell, A David Edwards, Daniel Rueckert, Joseph V Hajnal, Paul Aljabar, K Mori (ed.), I Sakuma (ed.), Y Sato (ed.), C Barillot (ed.), N Navab (ed.)

MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION (MICCAI 2013), PT I | SPRINGER-VERLAG BERLIN | Published : 2013

Abstract

Diffusion tensor imaging, tractography and the subsequent derivation of network measures are becoming an established approach in the exploration of brain connectivity. However, no gold standard exists in respect to how the brain should be parcellated and therefore a variety of atlas- and random-based parcellation methods are used. The resulting challenge of comparing graphs with differing numbers of nodes and uncertain node correspondences necessitates the use of normalisation schemes to enable meaningful intra- and inter-subject comparisons. This work proposes methods for normalising brain network measures using random graphs. We show that the normalised measures are locally stable over dis..

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Grants

Awarded by King's College London, UK - MRC


Funding Acknowledgements

This research was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at Guy's and St Thomas' NHS Foundation Trust and King's College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. Medical Research Council (MRC) Centre for Transplantation, King's College London, UK - MRC grant no. MR/J006742/1.