J-Donald
Tournier1,2, Fernando Calamante1,2, Alan Connelly1,2
1Brain Research Institute, Florey
Neuroscience Institutes (Austin),
Probabilistic
streamlines algorithms are amongst the most promising methods for
fibre-tracking, but are potentially subject to a number of deficiencies.
These include a tendency to overshoot in highly curved regions, and to switch
directions in crossing fibre regions. To address both of these issues, we
propose a higher-order probabilistic streamlines algorithm, based on 2nd
order integration over fibre orientation distributions (iFOD2), with a
computational complexity similar to current first order methods. We
demonstrate the advantages of the proposed iFOD2 algorithm on simulated data,
and apply the method to in-vivo data.