ep-surface_fit_parameterized is a ChRIS plugin
for experimenting with the parameters of surface_fit (ASP algorithm from CIVET).
surface_fit_script.pl is a Perl wrapper for surface_fit.
ep_surface_fit(.py) is a Python script for running surface_fit_script.pl
as a ChRIS ds-plugin on multiple subjects.
ep_surface_fit processes every laplacian grid (*.mnc) + starting surface (*.obj)
pair found in its input directory. For every *.mnc file found, ep_surface_fit will
search for a *.obj surface file in the same directory to use as a starting surface.
When multiple inputs are found, they are processed in parallel.
Multiple stages of surface_fit can be run by specifying multiple values
as a comma-separated list.
If some parameter values are given as CSV whereas others are given as singular,
the singular value is reused for later iterations. Example:
ep_surface_fit --iter-outer 100,100,400 --stretch-weight 80,60,40 --laplacian-weight 1e-4 ...The schedule is interpreted as:
- 100 iterations with sw=80 lw=1e-4
- 100 iterations with sw=60 lw=1e-4
- 400 iterations with sw=40 lw=1e-4
Number of triangles in the surface mesh, i.e. resolution
- 20480 improves performance and is more suitable for fetal brains 20-28 GA
- 81920 is standard
- 327680 is used for high-resolution adult human brain
Distance to move per iteration.
- large value converges faster
- small value decreases risk of self-intersection
...