Hello there,
I am looking for some more info on the usage of the very nice fslmaths
tool than it is displayed on the console by the help option. Is there
a detailed document about this?
It seems that they all do some things around each voxel in a file, but
they are otherwise grouped into several groups of tasks, some of which
are a bit puzzling to me.
1. To be more specific, consider the filtering group, where i used the
command like:
fslmaths aFile -kernel box 7 -fmean outFile
I think i am taking, around each voxel, a 7x7x7 box centered at that
voxel, and i believe i am placing the arithmetic mean value in the
image, at that voxel. (loop over all voxels implied)
I am, however puzzled by the meaning of 'kernel weighted' coupled with
'(conventionally used with gauss kernel)' and also by the
'un-normalised' attribute present in the -fmeanu option. What does
this mean? :)
(i suppose kernel-weighted simply means in this case that only the
voxels in the 7x7x7 box are included, i.e. treating the averaging
process as a convolution with a 7x7x7 uniform box function as a
symmetric kernel, which is, basically, 1/7^3 * chi_box (the
'charactersitic function of the box'). Where does the additional
'gauss kernel' fit into this picture? And how about the
edge-effects in the option below?)
2. As an extension, suppose i wanted to compute, for a single volume
image aFile as above, the estimated variance around each voxel over a
7x7x7 box as above. Then, since for a sample of size n, this can be
computed as
estVar = n/(n-1) * (<SqVals> - <Vals>^2) ,
i would have to:
- square aFile
- take average over the same box of the squares -> aveSqVals.nii
- take average of aFile
- square it -> sqAveVals.nii
- subtract the latter from the former and multiply the result
with n/(n-1), where n=7*7*7=343.
Thank you for your help and patience with me,
Silviu
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