From the comparison in Fig. we see that AFT, OrientationJ, and Skeletonize have different performances. For the experiments analysed here, the existing software is either not suitable at all (Skeletonize), does not provide a metric of anisotropy (OrientationJ/Skeletonize) or can only recover a single orientation angle for a given area (all). RFT, however, addresses all mentioned shortcomings and can combine the resulting data into WOP values for any given area within an image. The WOP value(s) can be calculated for images containing both low contrast (Fig. , cropped areas) and high contrast (Fig. ). Further, we can calculate anisotropy maps that indicate structure that can be visually confirmed as indicated with the MRI images (Fig. ) showing high WOP values around the edges of the parabola and low WOP values in the unstructured centre.