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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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