4D Flow images of the brain are a rich and multi-dimensional data set. To simplify this data while retaining the most important features, we represent the neurovasculature as a flow distribution network graph (FDNG). Here we show (A) time-averaged pathlines derived from the 4D flow velocity information, (B) identification of vessels (yellow) and schematic representation as a FDNG (blue), and (C) a standardized FDNG containing mean and standard deviations of flow values over a group of healthy controls with the same Circle of Willis structure variant.

Primary contact: Susanne Schnell (PhD)
Investigators: Susanne Schnell (PhD), TBD
Collaborations: Northwestern University (Michael Markl, Ann Ragin, Maria Aristova)