AFNI program: 3dBlurInMask
Output of -help
Usage: ~1~
3dBlurInMask [options]
Blurs a dataset spatially inside a mask. That's all. Experimental.
OPTIONS ~1~
-------
-input ddd = This required 'option' specifies the dataset
that will be smoothed and output.
-FWHM f = Add 'f' amount of smoothness to the dataset (in mm).
**N.B.: This is also a required 'option'.
-FWHMdset d = Read in dataset 'd' and add the amount of smoothness
given at each voxel -- spatially variable blurring.
** EXPERIMENTAL EXPERIMENTAL EXPERIMENTAL **
-mask mmm = Mask dataset, if desired. Blurring will
occur only within the mask. Voxels NOT in
the mask will be set to zero in the output.
-Mmask mmm = Multi-mask dataset -- each distinct nonzero
value in dataset 'mmm' will be treated as
a separate mask for blurring purposes.
**N.B.: 'mmm' must be byte- or short-valued!
-automask = Create an automask from the input dataset.
**N.B.: only 1 masking option can be used!
-preserve = Normally, voxels not in the mask will be
set to zero in the output. If you want the
original values in the dataset to be preserved
in the output, use this option.
-prefix ppp = Prefix for output dataset will be 'ppp'.
**N.B.: Output dataset is always in float format.
-quiet = Don't be verbose with the progress reports.
-float = Save dataset as floats, no matter what the
input data type is.
**N.B.: If the input dataset is unscaled shorts, then
the default is to save the output in short
format as well. In EVERY other case, the
program saves the output as floats. Thus,
the ONLY purpose of the '-float' option is to
force an all-shorts input dataset to be saved
as all-floats after blurring.
** NEW IN 2021 **
-FWHMxyz fx fy fz = Add different amounts of smoothness in the 3
spatial directions.
** If one of the 'f' values is 0, no smoothing is done
in that direction.
** Here, the axes names ('x', 'y', 'z') refer to the
order of storage in the dataset, as can be seen
in the output of 3dinfo; for example, from a dataset
that I happen to have lying around:
Data Axes Orientation:
first (x) = Anterior-to-Posterior
second (y) = Superior-to-Inferior
third (z) = Left-to-Right
In this example, 'fx' is the FWHM blurring along the
A-P direction, et cetera.
** In other words, x-y-z does not necessarily refer
to the DICOM order of coordinates (R-L, A-P, I-S)!
NOTES ~1~
-----
* If you don't provide a mask, then all voxels will be included
in the blurring. (But then why are you using this program?)
* Note that voxels inside the mask that are not contiguous with
any other voxels inside the mask will not be modified at all!
* Works iteratively, similarly to 3dBlurToFWHM, but without
the extensive overhead of monitoring the smoothness.
* But this program will be faster than 3dBlurToFWHM, and probably
slower than 3dmerge.
* Since the blurring is done iteratively, rather than all-at-once as
in 3dmerge, the results will be slightly different than 3dmerge's,
even if no mask is used here (3dmerge, of course, doesn't take a mask).
* If the original FWHM of the dataset was 'S' and you input a value
'F' with the '-FWHM' option, then the output dataset's smoothness
will be about sqrt(S*S+F*F). The number of iterations will be
about (F*F/d*d) where d=grid spacing; this means that a large value
of F might take a lot of CPU time!
* The spatial smoothness of a 3D+time dataset can be estimated with a
command similar to the following:
3dFWHMx -detrend -mask mmm+orig -input ddd+orig
* The minimum number of voxels in the mask is 9
* Isolated voxels will be removed from the mask!
=========================================================================
* This binary version of 3dBlurInMask is compiled using OpenMP, a semi-
automatic parallelizer software toolkit, which splits the work across
multiple CPUs/cores on the same shared memory computer.
* OpenMP is NOT like MPI -- it does not work with CPUs connected only
by a network (e.g., OpenMP doesn't work across cluster nodes).
* For some implementation and compilation details, please see
https://afni.nimh.nih.gov/pub/dist/doc/misc/OpenMP.html
* The number of CPU threads used will default to the maximum number on
your system. You can control this value by setting environment variable
OMP_NUM_THREADS to some smaller value (including 1).
* Un-setting OMP_NUM_THREADS resets OpenMP back to its default state of
using all CPUs available.
++ However, on some systems, it seems to be necessary to set variable
OMP_NUM_THREADS explicitly, or you only get one CPU.
++ On other systems with many CPUS, you probably want to limit the CPU
count, since using more than (say) 16 threads is probably useless.
* You must set OMP_NUM_THREADS in the shell BEFORE running the program,
since OpenMP queries this variable BEFORE the program actually starts.
++ You can't usefully set this variable in your ~/.afnirc file or on the
command line with the '-D' option.
* How many threads are useful? That varies with the program, and how well
it was coded. You'll have to experiment on your own systems!
* The number of CPUs on this particular computer system is ...... 1.
* The maximum number of CPUs that will be used is now set to .... 1.
=========================================================================
++ Compile date = Oct 10 2024 {AFNI_24.3.02:linux_ubuntu_24_64}
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