AFNI program: 3dNwarpXYZ
Output of -help
Usage: 3dNwarpXYZ [options] -nwarp 'warp specification' XYZfile.1D > Output.1D
Transforms the DICOM xyz coordinates in the input XYZfile.1D (3 columns)
based on the '-nwarp' specification -- which is as in 3dNwarpApply
(e.g., allows inversion, catenation, et cetera).
If this warp is the _WARP output from 3dQwarp, then it takes XYZ values
from the base dataset and transforms them to the corresponding source
dataset location.
To do the reverse operation -- to take an XYZ in the source dataset
and find out where it goes to in the base dataset -- do one of these:
* use the _WARPINV output from 3dQwarp instead of the _WARP output;
* use the 'INV(dataset)' form for '-nwarp' (will be slow);
* use the '-iwarp' option described below.
The first 2 choices should be equivalent. The third choice will give
slightly different results, since the method used for warp inversion
for just a few discrete points is very different than the full warp
inversion algorithm -- this difference is for speed.
The mean Euclidean error between '-iwarp' and _WARPINV is about 0.006 mm
in one test. The largest error (using 1000 random points) in this test
was about 0.05 mm. About 95% of points had 0.015 mm error or less.
For any 3D brain MRI purpose that Zhark can envision, this level of
concordance should be adequately good-iful.
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CLARIFICATION about the confusing forward and inverse warp issue
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If the following is the correct command to take a source dataset to
the place that you want it to go:
3dNwarpApply -nwarp 'SOME_WARP' -source DATASET -prefix JUNK
then the next command is the one to take coordinates in the source
dataset to the same place
3dNwarpXYZ -nwarp 'SOME_WARP' -iwarp XYZsource.1D > XYZwarped.1D
For example, a command like the above has been used to warp (x,y,z)
coordinates for ECOG sensors that were picked out manually on a CT volume.
An AFNI nonlinear warp stores the displacements (in DICOM mm) from the
base dataset grid to the source dataset grid. For computing the source
dataset warped to the base dataset grid, these displacements are needed,
so that for each grid point in the output (warped) dataset, the corresponding
location in the source dataset can be found. That is, this 'forward' warp is
good for finding where a given point in the base dataset maps to in the
source dataset.
However, for finding where a given point in the source dataset maps to
in the base dataset, the 'inverse' warp is needed, which is why the
'-iwarp' option was added to 3dNwarpXYZ.
Zhark knows the above is confusing, and hopes that your distraction by
this issue will aid him in his ruthless quest for Galactic Domination!
(And for warm cranberry scones with fresh clotted cream.)
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OTHER OPTIONS (i.e., besides the mandatory '-nwarp')
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-iwarp = Compute the inverse warp for each input (x,y,z) triple.
++ As mentioned above, this program does NOT compute the
inverse warp over the full grid (unlike the 'INV()' method
and the '-iwarp' options to other 3dNwarp* programs), but
uses a different method that is designed to be fast when
applied to a relatively few input points.
++ The upshot is that using '-iwarp' here will give slightly
different results than using 'INV()', but for any practical
application the differences should be negligible.
July 2014 - Zhark the Coordinated
++ Compile date = Oct 31 2024 {AFNI_24.3.06:linux_ubuntu_24_64}
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