# 3dmerge¶

```
Program 3dmerge
This program has 2 different functions:
(1) To edit 3D datasets in various ways (threshold, blur, cluster, ...);
(2) To merge multiple datasets in various ways (average, max, ...).
Either or both of these can be applied.
The 'editing' operations are controlled by options that start with '-1',
which indicates that they apply to individual datasets
(e.g., '-1blur_fwhm').
The 'merging' operations are controlled by options that start with '-g',
which indicate that they apply to the entire group of input datasets
(e.g., '-gmax').
----------------------------------------------------------------------
Usage: 3dmerge [options] datasets ...
Examples:
1. Apply a 4.0mm FWHM Gaussian blur to EPI run 7.
3dmerge -1blur_fwhm 4.0 -doall -prefix e1.run7_blur run7+orig
* These examples are based on a data grid of 3.75 x 3.75 x 3.5, in mm.
So a single voxel has a volume of ~49.22 mm^3 (mvul), and a 40 voxel
cluster has a volume of ~1969 mm^3 (as used in some examples).
2. F-stat only:
Cluster based on a threshold of F=10 (F-stats are in sub-brick #0),
and require a volume of 40 voxels (1969 mm^3). The output will be
the same F-stats as in the input, but subject to the threshold and
clustering.
3dmerge -1clust 3.76 1969 -1thresh 10.0 \
-prefix e2.f10 stats+orig'[0]'
3. F-stat only:
Perform the same clustering (as in #2), but apply the radius and
cluster size in terms of cubic millimeter voxels (as if the voxels
were 1x1x1). So add '-dxyz=1', and adjust rmm and mvul.
3dmerge -dxyz=1 -1clust 1 40 -1thresh 10.0 \
-prefix e3.f10 stats+orig'[0]'
4. t-stat and beta weight:
For some condition, our beta weight is in sub-brick #4, with the
corresponding t-stat in sub-brick #5. Cluster based on 40 voxels
and a t-stat threshold of 3.25. Output the data from the beta
weights, not the t-stats.
3dmerge -dxyz=1 -1clust 1 40 -1thresh 3.25 \
-1tindex 5 -1dindex 4 \
-prefix e4.t3.25 stats+orig
5. t-stat mask:
Apply the same threshold and cluster as in #4, but output a mask.
Since there are 5 clusters found in this example, the values in
the mask will be from 1 to 5, representing the largest cluster to
the smallest. Use -1clust_order on sub-brick 5.
3dmerge -dxyz=1 -1clust_order 1 40 -1thresh 3.25 \
-prefix e5.mask5 stats+orig'[5]'
Note: this should match the 3dclust output from:
3dclust -1thresh 3.25 -dxyz=1 1 40 stats+orig'[5]'
----------------------------------------------------------------------
EDITING OPTIONS APPLIED TO EACH INPUT DATASET:
-1thtoin = Copy threshold data over intensity data.
This is only valid for datasets with some
thresholding statistic attached. All
subsequent operations apply to this
substituted data.
-2thtoin = The same as -1thtoin, but do NOT scale the
threshold values from shorts to floats when
processing. This option is only provided
for compatibility with the earlier versions
of the AFNI package '3d*' programs.
-1noneg = Zero out voxels with negative intensities
-1abs = Take absolute values of intensities
-1clip val = Clip intensities in range (-val,val) to zero
-2clip v1 v2 = Clip intensities in range (v1,v2) to zero
-1uclip val = These options are like the above, but do not apply
-2uclip v1 v2 any automatic scaling factor that may be attached
to the data. These are for use only in special
circumstances. (The 'u' means 'unscaled'. Program
'3dinfo' can be used to find the scaling factors.)
N.B.: Only one of these 'clip' options can be used; you cannot
combine them to have multiple clipping executed.
-1thresh thr = Use the threshold data to censor the intensities
(only valid for 'fith', 'fico', or 'fitt' datasets)
(or if the threshold sub-brick is set via -1tindex)
N.B.: The value 'thr' is floating point, in the range
0.0 < thr < 1.0 for 'fith' and 'fico' datasets,
and 0.0 < thr < 32.7 for 'fitt' datasets.
-2thresh t1 t2 = Zero out voxels where the threshold sub-brick value
lies between 't1' and 't2' (exclusive). If t1=-t2,
is the same as '-1thresh t2'.
-1blur_sigma bmm = Gaussian blur with sigma = bmm (in mm)
-1blur_rms bmm = Gaussian blur with rms deviation = bmm
-1blur_fwhm bmm = Gaussian blur with FWHM = bmm
-1blur3D_fwhm bx by bz =
Gaussian blur with FWHM (potentially) different in each
of the 3 spatial dimensions. Note that these dimensions
are in mm, and refer to the storage order of the dataset.
(See the output of '3dinfo datasetname' if you
don't know the storage order of your input dataset.)
A blur amount of 0 in a direction means not to apply
any blurring along that axis. For example:
-1blur3D_fwhm 4 4 0
will do in-plane blurring only along the x-y dataset axes.
-t1blur_sigma bmm= Gaussian blur of threshold with sigma = bmm(in mm)
-t1blur_rms bmm = Gaussian blur of threshold with rms deviation = bmm
-t1blur_fwhm bmm = Gaussian blur of threshold with FWHM = bmm
-1zvol x1 x2 y1 y2 z1 z2
= Zero out entries inside the 3D volume defined
by x1 <= x <= x2, y1 <= y <= y2, z1 <= z <= z2 ;
N.B.: The ranges of x,y,z in a dataset can be found
using the '3dinfo' program. Dimensions are in mm.
N.B.: This option may not work correctly at this time, but
I've not figured out why!
CLUSTERING
-dxyz=1 = In the cluster editing options, the spatial clusters
are defined by connectivity in true 3D distance, using
the voxel dimensions recorded in the dataset header.
This option forces the cluster editing to behave as if
all 3 voxel dimensions were set to 1 mm. In this case,
'rmm' is then the max number of grid cells apart voxels
can be to be considered directly connected, and 'vmul'
is the min number of voxels to keep in the cluster.
N.B.: The '=1' is part of the option string, and can't be
replaced by some other value. If you MUST have some
other value for voxel dimensions, use program 3drefit.
The following cluster options are mutually exclusive:
-1clust rmm vmul = Form clusters with connection distance rmm
and clip off data not in clusters of
volume at least vmul microliters
-1clust_mean rmm vmul = Same as -1clust, but all voxel intensities
within a cluster are replaced by the average
intensity of the cluster.
-1clust_max rmm vmul = Same as -1clust, but all voxel intensities
within a cluster are replaced by the maximum
intensity of the cluster.
-1clust_amax rmm vmul = Same as -1clust, but all voxel intensities
within a cluster are replaced by the maximum
absolute intensity of the cluster.
-1clust_smax rmm vmul = Same as -1clust, but all voxel intensities
within a cluster are replaced by the maximum
signed intensity of the cluster.
-1clust_size rmm vmul = Same as -1clust, but all voxel intensities
within a cluster are replaced by the size
of the cluster (in multiples of vmul).
-1clust_order rmm vmul= Same as -1clust, but all voxel intensities
within a cluster are replaced by the cluster
size index (largest cluster=1, next=2, ...).
-1clust_depth rmm vmul= Same as -1clust, but all voxel intensities
are replaced by the number of peeling operations
needed to remove them from the cluster.
That number is an indication of how deep a voxel
is inside a cluster
-isovalue = Clusters will be formed only from contiguous (in the
rmm sense) voxels that also have the same value.
N.B.: The normal method is to cluster all contiguous
nonzero voxels together.
-isomerge = Clusters will be formed from each distinct value
in the dataset; spatial contiguity will not be
used (but you still have to supply rmm and vmul
on the command line).
N.B.: 'Clusters' formed this way may well have components
that are widely separated!
* If rmm is given as 0, this means to use the 6 nearest neighbors to
form clusters of nonzero voxels.
* If vmul is given as zero, then all cluster sizes will be accepted
(probably not very useful!).
* If vmul is given as negative, then abs(vmul) is the minimum number
of voxels to keep.
The following commands produce erosion and dilation of 3D clusters.
These commands assume that one of the -1clust commands has been used.
The purpose is to avoid forming strange clusters with 2 (or more)
main bodies connected by thin 'necks'. Erosion can cut off the neck.
Dilation will minimize erosion of the main bodies.
Note: Manipulation of values inside a cluster (-1clust commands)
occurs AFTER the following two commands have been executed.
-1erode pv For each voxel, set the intensity to zero unless pv %
of the voxels within radius rmm are nonzero.
-1dilate Restore voxels that were removed by the previous
command if there remains a nonzero voxel within rmm.
The following filter options are mutually exclusive:
-1filter_mean rmm = Set each voxel to the average intensity of the
voxels within a radius of rmm.
-1filter_nzmean rmm = Set each voxel to the average intensity of the
non-zero voxels within a radius of rmm.
-1filter_max rmm = Set each voxel to the maximum intensity of the
voxels within a radius of rmm.
-1filter_amax rmm = Set each voxel to the maximum absolute intensity
of the voxels within a radius of rmm.
-1filter_smax rmm = Set each voxel to the maximum signed intensity
of the voxels within a radius of rmm.
-1filter_aver rmm = Same idea as '_mean', but implemented using a
new code that should be faster.
The following threshold filter options are mutually exclusive:
-t1filter_mean rmm = Set each correlation or threshold voxel to the
average of the voxels within a radius of rmm.
-t1filter_nzmean rmm = Set each correlation or threshold voxel to the
average of the non-zero voxels within
a radius of rmm.
-t1filter_max rmm = Set each correlation or threshold voxel to the
maximum of the voxels within a radius of rmm.
-t1filter_amax rmm = Set each correlation or threshold voxel to the
maximum absolute intensity of the voxels
within a radius of rmm.
-t1filter_smax rmm = Set each correlation or threshold voxel to the
maximum signed intensity of the voxels
within a radius of rmm.
-t1filter_aver rmm = Same idea as '_mean', but implemented using a
new code that should be faster.
-1mult factor = Multiply intensities by the given factor
-1zscore = If the sub-brick is labeled as a statistic from
a known distribution, it will be converted to
an equivalent N(0,1) deviate (or 'z score').
If the sub-brick is not so labeled, nothing will
be done.
The above '-1' options are carried out in the order given above,
regardless of the order in which they are entered on the command line.
N.B.: The 3 '-1blur' options just provide different ways of
specifying the radius used for the blurring function.
The relationships among these specifications are
sigma = 0.57735027 * rms = 0.42466090 * fwhm
The requisite convolutions are done using FFTs; this is by
far the slowest operation among the editing options.
OTHER OPTIONS:
-nozero = Do NOT write the output dataset if it would be all zero.
-datum type = Coerce the output data to be stored as the given type,
which may be byte, short, or float.
N.B.: Byte data cannot be negative. If this datum type is chosen,
any negative values in the edited and/or merged dataset
will be set to zero.
-keepthr = When using 3dmerge to edit exactly one dataset of a
functional type with a threshold statistic attached,
normally the resulting dataset is of the 'fim'
(intensity only) type. This option tells 3dmerge to
copy the threshold data (unedited in any way) into
the output dataset.
N.B.: This option is ignored if 3dmerge is being used to
combine 2 or more datasets.
N.B.: The -datum option has no effect on the storage of the
threshold data. Instead use '-thdatum type'.
-doall = Apply editing and merging options to ALL sub-bricks
uniformly in a dataset.
N.B.: All input datasets must have the same number of sub-bricks
when using the -doall option.
N.B.: The threshold specific options (such as -1thresh,
-keepthr, -tgfisher, etc.) are not compatible with
the -doall command. Neither are the -1dindex or
the -1tindex options.
N.B.: All labels and statistical parameters for individual
sub-bricks are copied from the first dataset. It is
the responsibility of the user to verify that these
are appropriate. Note that sub-brick auxiliary data
can be modified using program 3drefit.
-quiet = Reduce the number of messages shown
-1dindex j = Uses sub-brick #j as the data source , and uses sub-brick
-1tindex k = #k as the threshold source. With these, you can operate
on any given sub-brick of the inputs dataset(s) to produce
as output a 1 brick dataset. If desired, a collection
of 1 brick datasets can later be assembled into a
multi-brick bucket dataset using program '3dbucket'
or into a 3D+time dataset using program '3dTcat'.
N.B.: If these options aren't used, j=0 and k=1 are the defaults
The following option allows you to specify a mask dataset that
limits the action of the 'filter' options to voxels that are
nonzero in the mask:
-1fmask mset = Read dataset 'mset' (which can include a
sub-brick specifier) and use the nonzero
voxels as a mask for the filter options.
Filtering calculations will not use voxels
that are outside the mask. If an output
voxel does not have ANY masked voxels inside
the rmm radius, then that output voxel will
be set to 0.
N.B.: * Only the -1filter_* and -t1filter_* options are
affected by -1fmask.
* Voxels NOT in the fmask will be set to zero in the
output when the filtering occurs. THIS IS NEW BEHAVIOR,
as of 11 Oct 2007. Previously, voxels not in the fmask,
but within 'rmm' of a voxel in the mask, would get a
nonzero output value, as those nearby voxels would be
combined (via whatever '-1f...' option was given).
* If you wish to restore this old behavior, where non-fmask
voxels can get nonzero output, then use the new option
'-1fm_noclip' in addition to '-1fmask'. The two comments
below apply to the case where '-1fm_noclip' is given!
* In the linear averaging filters (_mean, _nzmean,
and _expr), voxels not in the mask will not be used
or counted in either the numerator or denominator.
This can give unexpected results if you use '-1fm_noclip'.
For example, if the mask is designed to exclude the volume
outside the brain, then voxels exterior to the brain,
but within 'rmm', will have a few voxels inside the brain
included in the filtering. Since the sum of weights (the
denominator) is only over those few intra-brain
voxels, the effect will be to extend the significant
part of the result outward by rmm from the surface
of the brain. In contrast, without the mask, the
many small-valued voxels outside the brain would
be included in the numerator and denominator sums,
which would barely change the numerator (since the
voxel values are small outside the brain), but would
increase the denominator greatly (by including many
more weights). The effect in this case (no -1fmask)
is to make the filtering taper off gradually in the
rmm-thickness shell around the brain.
* Thus, if the -1fmask is intended to clip off non-brain
data from the filtering, its use should be followed by
masking operation using 3dcalc:
3dmerge -1filter_aver 12 -1fm_noclip -1fmask mask+orig -prefix x input+orig
3dcalc -a x -b mask+orig -prefix y -expr 'a*step(b)'
rm -f x+orig.*
The desired result is y+orig - filtered using only
brain voxels (as defined by mask+orig), and with
the output confined to the brain voxels as well.
The following option allows you to specify an almost arbitrary
weighting function for 3D linear filtering:
-1filter_expr rmm expr
Defines a linear filter about each voxel of radius 'rmm' mm.
The filter weights are proportional to the expression evaluated
at each voxel offset in the rmm neighborhood. You can use only
these symbols in the expression:
r = radius from center
x = dataset x-axis offset from center
y = dataset y-axis offset from center
z = dataset z-axis offset from center
i = x-axis index offset from center
j = y-axis index offset from center
k = z-axis index offset from center
Example:
-1filter_expr 12.0 'exp(-r*r/36.067)'
This does a Gaussian filter over a radius of 12 mm. In this
example, the FWHM of the filter is 10 mm. [in general, the
denominator in the exponent would be 0.36067 * FWHM * FWHM.
This is one way to get a Gaussian blur combined with the
-1fmask option. The radius rmm=12 is chosen where the weights
get smallish.] Another example:
-1filter_expr 20.0 'exp(-(x*x+16*y*y+z*z)/36.067)'
which is a non-spherical Gaussian filter.
** For shorthand, you can also use the new option (11 Oct 2007)
-1filter_blur fwhm
which is equivalent to
-1filter_expr 1.3*fwhm 'exp(-r*r/(.36067*fwhm*fwhm)'
and will implement a Gaussian blur. The only reason to do
Gaussian blurring this way is if you also want to use -1fmask!
The following option lets you apply a 'Winsor' filter to the data:
-1filter_winsor rmm nw
The data values within the radius rmm of each voxel are sorted.
Suppose there are 'N' voxels in this group. We index the
sorted voxels as s[0] <= s[1] <= ... <= s[N-1], and we call the
value of the central voxel 'v' (which is also in array s[]).
If v < s[nw] , then v is replaced by s[nw]
otherwise If v > s[N-1-nw], then v is replace by s[N-1-nw]
otherwise v is unchanged
The effect is to increase 'too small' values up to some
middling range, and to decrease 'too large' values.
If N is odd, and nw=(N-1)/2, this would be a median filter.
In practice, I recommend that nw be about N/4; for example,
-dxyz=1 -1filter_winsor 2.5 19
is a filter with N=81 that gives nice results.
N.B.: This option is NOT affected by -1fmask
N.B.: This option is slow! and experimental.
The following option returns a rank value at each voxel in
the input dataset.
-1rank
If the input voxels were, say, 12 45 9 0 9 12 0
the output would be 2 3 1 0 1 2 0
This option is handy for turning FreeSurfer's segmentation
volumes to ROI volumes that can be easily colorized with AFNI.
For example:
3dmerge -1rank -prefix aparc+aseg_rank aparc+aseg.nii
To view aparc+aseg_rank+orig, use the ROI_128 colormap
and set the colorbar range to 128.
The -1rank option also outputs a 1D file that contains
the mapping from the input dataset to the ranked output.
Sub-brick float factors are ignored.
This option only works on datasets of integral values or
of integral data types. 'float' values are typecast to 'int'
before being ranked.
See also program 3dRank
MERGING OPTIONS APPLIED TO FORM THE OUTPUT DATASET:
[That is, different ways to combine results. The]
[following '-g' options are mutually exclusive! ]
-gmean = Combine datasets by averaging intensities
(including zeros) -- this is the default
-gnzmean = Combine datasets by averaging intensities
(not counting zeros)
-gmax = Combine datasets by taking max intensity
(e.g., -7 and 2 combine to 2)
-gamax = Combine datasets by taking max absolute intensity
(e.g., -7 and 2 combine to 7)
-gsmax = Combine datasets by taking max signed intensity
(e.g., -7 and 2 combine to -7)
-gcount = Combine datasets by counting number of 'hits' in
each voxel (see below for defintion of 'hit')
-gorder = Combine datasets in order of input:
* If a voxel is nonzero in dataset #1, then
that value goes into the voxel.
* If a voxel is zero in dataset #1 but nonzero
in dataset #2, then the value from #2 is used.
* And so forth: the first dataset with a nonzero
entry in a given voxel 'wins'
-gfisher = Takes the arctanh of each input, averages these,
and outputs the tanh of the average. If the input
datum is 'short', then input values are scaled by
0.0001 and output values by 10000. This option
is for merging bricks of correlation coefficients.
-nscale = If the output datum is shorts, don't do the scaling
to the max range [similar to 3dcalc's -nscale option]
MERGING OPERATIONS APPLIED TO THE THRESHOLD DATA:
[That is, different ways to combine the thresholds. If none of these ]
[are given, the thresholds will not be merged and the output dataset ]
[will not have threshold data attached. Note that the following '-tg']
[command line options are mutually exclusive, but are independent of ]
[the '-g' options given above for merging the intensity data values. ]
-tgfisher = This option is only applicable if each input dataset
is of the 'fico' or 'fith' types -- functional
intensity plus correlation or plus threshold.
(In the latter case, the threshold values are
interpreted as correlation coefficients.)
The correlation coefficients are averaged as
described by -gfisher above, and the output
dataset will be of the fico type if all inputs
are fico type; otherwise, the output datasets
will be of the fith type.
N.B.: The difference between the -tgfisher and -gfisher
methods is that -tgfisher applies to the threshold
data stored with a dataset, while -gfisher
applies to the intensity data. Thus, -gfisher
would normally be applied to a dataset created
from correlation coefficients directly, or from
the application of the -1thtoin option to a fico
or fith dataset.
OPTIONAL WAYS TO POSTPROCESS THE COMBINED RESULTS:
[May be combined with the above methods.]
[Any combination of these options may be used.]
-ghits count = Delete voxels that aren't !=0 in at least
count datasets (!=0 is a 'hit')
-gclust rmm vmul = Form clusters with connection distance rmm
and clip off data not in clusters of
volume at least vmul microliters
The '-g' and '-tg' options apply to the entire group of input datasets.
OPTIONS THAT CONTROL THE NAMES OF THE OUTPUT DATASET:
-session dirname = write output into given directory (default=./)
-prefix pname = use 'pname' for the output dataset prefix
(default=mrg)
NOTES:
** If only one dataset is read into this program, then the '-g'
options do not apply, and the output dataset is simply the
'-1' options applied to the input dataset (i.e., edited).
** A merged output dataset is ALWAYS of the intensity-only variety.
** You can combine the outputs of 3dmerge with other sub-bricks
using the program 3dbucket.
** Complex-valued datasets cannot be merged.
** This program cannot handle time-dependent datasets without -doall.
** Note that the input datasets are specified by their .HEAD files,
but that their .BRIK files must exist also!
INPUT DATASET NAMES
-------------------
This program accepts datasets that are modified on input according to the
following schemes:
'r1+orig[3..5]' {sub-brick selector}
'r1+orig<100..200>' {sub-range selector}
'r1+orig[3..5]<100..200>' {both selectors}
'3dcalc( -a r1+orig -b r2+orig -expr 0.5*(a+b) )' {calculation}
For the gruesome details, see the output of 'afni -help'.
** Input datasets using sub-brick selectors are treated as follows:
- 3D+time if the dataset is 3D+time and more than 1 brick is chosen
- otherwise, as bucket datasets (-abuc or -fbuc)
(in particular, fico, fitt, etc. datasets are converted to fbuc)
** If you are NOT using -doall, and choose more than one sub-brick
with the selector, then you may need to use -1dindex to further
pick out the sub-brick on which to operate (why you would do this
I cannot fathom). If you are also using a thresholding operation
(e.g., -1thresh), then you also MUST use -1tindex to choose which
sub-brick counts as the 'threshold' value. When used with sub-brick
selection, 'index' refers the dataset AFTER it has been read in:
-1dindex 1 -1tindex 3 'dset+orig[4..7]'
means to use the #5 sub-brick of dset+orig as the data for merging
and the #7 sub-brick of dset+orig as the threshold values.
** The above example would better be done with
-1tindex 1 'dset+orig[5,7]'
since the default data index is 0. (You would only use -1tindex if
you are actually using a thresholding operation.)
** -1dindex and -1tindex apply to all input datasets.
++ Compile date = Sep 1 2021 {AFNI_21.2.06:linux_ubuntu_16_64}
```