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Oct 12, 2016 09:10 PM | Tanmay Nath
Motion parameters
Hi,
I was wondering if there is a way to extract the amount of motion corrected by DTIPrep. I mean what is the resultant motion of the QCed subjects. I do have the QC report, but i cannot find the motion parameters in it. Also how does it correct this motion? Is it only that DTIPrep does an affine transformation of each directions with the baseline?
Thanks
I was wondering if there is a way to extract the amount of motion corrected by DTIPrep. I mean what is the resultant motion of the QCed subjects. I do have the QC report, but i cannot find the motion parameters in it. Also how does it correct this motion? Is it only that DTIPrep does an affine transformation of each directions with the baseline?
Thanks
Oct 13, 2016 12:10 PM | Martin Styner
RE: Motion parameters
Yes, it does stores the (affine) motion information (that was
detected and corrected by the motion correction step) in the
xml-report. Per DWI you will find there the full
transformation matrix (in case you want to use that), plus 2
summary features for the overall translation and the overall
rotation. The entries are labeled as TranslationNorm and
Angle.
here is the info, how these are computed
Angle = combined angle, this is the single total rotation around the best fitting rotation axis (so not one of the coordinate axes x, y, z) needed to represent the motion. This is actually not extracted from the affine transform, but simpler by looking at the angle between the gradient direction before the motion correction and after (which is very simple to extract).
Translation = norm/length of the translation vector = sqrt(tx*tx + ty*ty + tz*tz), the translation vector is easily extracted from the Affine transform
The affine transform is to the average baseline (by default computed via iterative unbiased averaging), see also:
Kreilkamp BAK, Zacà D, Papinutto N, Jovicich J. Retrospective head motion correction approaches for diffusion tensor imaging: Effects of preprocessing choices on biases and reproducibility of scalar diffusion metrics. J Magn Reson Imaging. 2015 Jun 7.
Martin
here is the info, how these are computed
Angle = combined angle, this is the single total rotation around the best fitting rotation axis (so not one of the coordinate axes x, y, z) needed to represent the motion. This is actually not extracted from the affine transform, but simpler by looking at the angle between the gradient direction before the motion correction and after (which is very simple to extract).
Translation = norm/length of the translation vector = sqrt(tx*tx + ty*ty + tz*tz), the translation vector is easily extracted from the Affine transform
The affine transform is to the average baseline (by default computed via iterative unbiased averaging), see also:
Kreilkamp BAK, Zacà D, Papinutto N, Jovicich J. Retrospective head motion correction approaches for diffusion tensor imaging: Effects of preprocessing choices on biases and reproducibility of scalar diffusion metrics. J Magn Reson Imaging. 2015 Jun 7.
Martin
Oct 14, 2016 12:10 AM | Tanmay Nath
RE: Motion parameters
Thank you for the reply.
I read the paper carefully, but have the following questions:
Thank you
Tanmay
I read the paper carefully, but have the following questions:
- I cannot differentiate between the eddy current and head motion correction algorithm for FSL and DTIPrep.
- I do not understand the difference between the trilinear interpolation and 3d linear interpolation as reported in the table 1 of Kreilkamp et.al. paper
Thank you
Tanmay