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.