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The NIfTI qform matrix is actually stored internally as a quaternion (and 3 translations); this representation is fundamentally incapable of representing non-orthonormal transformations. So if the sform matrix is non-orthonormal, it is mathematically impossible for the qform transformation to match it.
The Insight ToolKit (ITK) does not support rhomboidal images. While this may have changed, early versions of ITK always gave precedence to the QForm (presumably because the constrained QForm can not represent rhomboidal images), while most other tools chose between the SForm and QForm by selecting the higher qform_code versus sform_code (and giving precedence to the SForm in the case of ties). This meant that the starting estimates for ITK based tools like ANTS were often very different from other NIfTI tools like SPM and FSL.
Yes. BTW, the error message appears in the commit ENH: Prefer to use sform over qform when both are set.I have checked, older versions of my app (uses ITK IO for Nifti), like Slicer, can open the nii file:Spacing: [0.865759, 0.865759, 0.796]Origin: [54.9757, 54.9757, -37.412]Direction:-1 0 00 -1 00 0 1
The image header for NIFTI has two separate ways to represent positional information in a viewer. Some programs (ITK-SNAP) prefer to edit the qform and others prefer to edit the sform (SPM, FSL), but these choices have evolved over the years along with what happens to the other matrix when the preferred one gets edited (set the other to 0s, match the other to the preferred, leave the other as it was). ITK-SNAP sets the sform to 0s, a potential problem for other viewers. The following tools can help: sqdiff.sh tells you whether the sform and qform of an image differ. sqdiff_wrap.sh will run sqdiff on every image it finds in subject subdirectories (sub*) of the current directory. q2s.sh copies the qform to the sform. s2q.sh copies the sform to the qform. All are based on the fsl tool fslorient.
Because the sform and qform are stored differently, they have different levels of precision. It is possible to copy the sform to the qform and still find that they are reported to be a bit different by sqdiff.sh. If you copy the qform to the sform, however, any differences will be completely removed.
sqdiff.sh compares the sform and qform. You see results if they are different. In the example above, ITK-SNAP has set the sform to 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 which is quite different that the qform!
To make the sform and qform match (a very good idea), you can run either q2s.sh or s2q.sh. After generating a mask with ITK-SNAP, you can see that the sform has been zeroed out, so we want to copy the qform to the sform:
To provide some context here, the qform and sform are 6 and 12 degrees-of-freedom alignment matrices. The qform is intended to encode scanner space, and the 6 DoF are 3D rotations and translations. The sform is intended to allow the same data to inhabit a second space, and this can be rotated, translated, scaled and sheared. The idea is that you could preserve the original data as retrieved by the scanner while still producing an alignment to another image, within the limitations of affine transformations. The standard specifies that if the sform is defined (has a non-zero sform_code), then it should be preferred to the qform for determining the alignment of the image, as it is more flexible and the result of analysis, while the qform is ostensibly written once at the initial NIfTI creation.
Moreover, while most tools respect the sform, per the standard, ANTs in particular ignores it and strictly uses the qform. Therefore, because we want to mix and match transformations calculated by ANTs, FSL and FreeSurfer, it makes things dramatically simpler to make sure the transforms match.
On one subject, this test returnsprint("Equivalent:", np.allclose(qform, new_qform)) Equivalent: TrueI will try it on everyone and I will take a stab at addressing your proposal on github (although this is my first time trying such a thing, it seems very doable).
The NIfTI format specifies two (out of three) methods to ensure that the orientation of the data in a NIfTI file is properly interpreted by neuroimaging software. Both methods in effect specify an affine transformation matrix that maps voxel i,j,k coordinates to RAS+ (left-to-right, posterior-to-anterior, inferior-to-superior) world coordinates. One method (method #2, qform) is based on a rotation matrix (stored as a quaternion), scaling values and a translation vector; this method is mainly used to map voxel coordinates to x,y,z coordinates in scanner world space (or to another aligned data set). The other method (method #3, sform) uses a full 12-parameter affine matrix that maps voxel coordinates to x,y,z MNI-152 or Talairach space, which also use a RAS+ coordinate system. If a data set is already transformed in MNI or Talairach space, the transformation matrix is simply the identity matrix (eventually with 90/180 degree roations and axis flips to reorient coordinate axes) combined with potential scaling and translation values. A third method is available that only supports scaling the data (using the NIfTI pixdim values) without defining a coordinate system; this method is not recommended and only included in the NIfTI specification for compatibility with the older Analyze 7.5 file format.
Both affine transformation matrices of method #1 and #2 can be present in the same NIfTI file. In order to know which transformation is valid, the NIfTI header contains a value for each transformation type, the qform_code and the sform_code. If one (or both) codes contain a value > 0, the respective transformation is valid and can be used. If both codes are 0, only the non-recommended third method (using only scaling transformations) is available. The two forms were introduced so that two transformations could be defined simultaneously (e.g. one transformation to align the data to scanner space and one transformation to align the data to normalized space) but in practice most imaging software keep the two transformations identical or use only one. The non-zero qform/sform code specifies the target transformation RAS+ space as follows: 2b1af7f3a8