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Precise quantification of streamlines lengths #1507
As discussed in #1501.
The only time at which it is safe to perform a multiplication between number of vertices and step size in order to derive the streamline length is within the tractography propagation algorithm itself, when a fixed step size is guaranteed. As soon as there is the possibility of an inconsistent step size (input data from a file, various resampling strategies, truncation), this is no longer safe, and so the sum of inter-vertex distances must be calculated.
Couple of points to note:
referenced this pull request
Dec 9, 2018
Looking at this, I'm reminded that we might want to change the default setting for the max length. Currently, it's set to 100× voxel size, which is really a bit useless. Might be best reserved for a separate pull request - but how do people feel about setting it to the largest image dimension instead (i.e. max FoV)?
Agreed the default is a bit useless. I don't think max FoV will be enough though: if you cropped your FoV to just the brain mask (which many people often do, to deal with large datasets / high resolutions), this doesn't allow a streamline to run "back and forth" through the brain anymore. The default should, in my opinion, just be something that is realistically not reached, but is there anyway to avoid streamlines looping infinitely. So going by my earlier reasoning/argument ... what about 2x max FoV...?
I think I might have proposed this last time around? Was still concerned about the influence of FoV cropping though. We've never figured out a better heuristic so it really needs its own issue listing.