usage: __main__.py [-h] (--gaussian SIGMA | --spline SIGMA NB_CTRL_POINT)
[--compress [COMPRESS_TH]] [--reference REFERENCE]
[-v [{DEBUG,INFO,WARNING}]] [-f]
in_tractogram out_tractogram
This script will smooth the streamlines, usually to remove the 'wiggles' in
probabilistic tracking.
Two choices of methods are available:
- Gaussian will use the surrounding coordinates for smoothing. Streamlines are
resampled to 1mm step-size and the smoothing is performed on the coordinate
array. The sigma will be indicative of the number of points surrounding the
center points to be used for blurring.
- Spline will fit a spline curve to every streamline using a sigma and the
number of control points. The sigma represents the allowed distance from the
control points. The final streamlines are obtained by evaluating the spline at
constant intervals so that it will have the same number of points as initially.
This script enforces endpoints to remain the same.
WARNING:
- too low of a sigma (e.g: 1) with a lot of control points (e.g: 15)
will create crazy streamlines that could end up out of the bounding box.
- data_per_point will be lost.
Formerly: scil_smooth_streamlines.py
positional arguments:
in_tractogram Input tractography file.
out_tractogram Output tractography file.
options:
-h, --help show this help message and exit
--gaussian SIGMA Sigma for smoothing. Use the value of surronding
X,Y,Z points on the streamline to blur the streamlines.
A good sigma choice would be around 5.
--spline SIGMA NB_CTRL_POINT
Sigma for smoothing. Model each streamline as a spline.
A good sigma choice would be around 5 and control point around 10.
--compress [COMPRESS_TH]
If set, compress the resulting streamline. Value is the maximum
compression distance in mm.[0.1]
--reference REFERENCE
Reference anatomy for tck/vtk/fib/dpy file
support (.nii or .nii.gz).
-v [{DEBUG,INFO,WARNING}]
Produces verbose output depending on the provided level.
Default level is warning, default when using -v is info.
-f Force overwriting of the output files.