Abstract #2897
Data-driven optimisation of multi-shell HARDI
Jacques-Donald Tournier 1,2 , Emer Hughes 1,3 , Nora Tusor 1,3 , Stamatios N. Sotiropoulos 4 , Saad Jbabdi 4 , Jesper Andersson 4 , Daniel Rueckert 5 , A. David Edwards 1,3 , and Joseph V Hajnal 1,2
1
Centre for the Developing Brain, Kings
College London, London, London, United Kingdom,
2
Department
of Biomedical Engineering, Kings College London, London,
London, United Kingdom,
3
Department
of Perinatal Imaging & Health, Kings College London,
London, London, United Kingdom,
4
FMRIB
Centre, University of Oxford, Oxford, United Kingdom,
5
Department
of Computing, Imperial College London, London, United
Kingdom
A number of recently proposed methods make use of data
acquired using multi-shell HARDI, characterised by the
number of b-values used, their actual values, and the
number of DW directions acquired per b-value shell. To
date, these schemes have been optimised with respect to
a particular reconstruction algorithm, with no guarantee
of suitability for other methods. In this study, we
present a data-driven approach to optimise these
protocols, and apply it to design a multi-shell scheme
suitable for use in neonatal imaging.
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