Hi
I want to inquire about header differences between SPM and FSL.
My questions are
1) SPM and FSL seem to be translated 1 voxel in each axis relative to
each other. Are these just 2 different but valid ways of treating the
set of coordinates stored in the NIFTI header?
2) I'm not sure I understand (actually I'm sure I don't understand)
the differences between the qform and sform information). In one
volume made by SPM the sform info is translated by 1 voxel in each
axis from the SPM matrix. But the qform is rotated relative to the
sform and spm matrix (pi/2 radians along the y and z axes and then
flipped along the x axis. In another volume (from the ADNI database)
the fsl sform is all zeros while the qform is the same as the spm
matrix but translated by 1 voxel. Why the differing relationships
between sform and qform in different volumes and how should this be
interpreted.
The details on the matrices are below
Volume made by converting dicom to NIFTI in SPM5
SPM matrix
0.0601 -0.0199 0.9980 -95.4718
-0.9248 0.3751 0.0632 50.4595
0.3756 0.9268 -0.0041 -168.5254
0 0 0 1.0000
using fslhd it returns for the sform (fsl says this is a NIFTI-1+ file)
0.060079 -0.019902 0.997995 -94.433670
-0.924828 0.375106 0.063155 49.972889
0.375611 0.926768 -0.004130 -167.227142
0.000000 0.000000 0.000000 1.000000
Inverting the matrices into voxel space shows they are translated by 1
voxel from eachother (fsl is +1 voxel in each axis)
The qform matrix matrix is
0 0 1.0000 -91.8086
-1.0000 0 0 150.2038
0 1.0000 0 -123.1709
0 0 0 1.0000
-----------------------------------------------------------------------------
Volume from the ADNI database
SPM5 returns
1.2000 0 0 147.2850
0 1.0000 0 156.5267
0 0 1.0000 383.0000
0 0 0 1.0000
but fsl returns for the sform (again this is a NIFTI-1+ file)
0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000
and for the qform
1.199997 0.000000 0.000000 148.484955
0.000000 1.000000 0.000000 157.526672
0.000000 0.000000 1.000000 384.000000
0.000000 0.000000 0.000000 1.000000
thanks for any insight.
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Darren Gitelman
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