[Camino-users] error when splitting tensor components with shredder

[Alessandro Calamuneri]

Hi all,
I would like to obtain tensor components computed with using modelfit and
nldt_pos as algorithm. Everything seems to work properly, as I can also
correctly visualize results using e.g. pdview.
But when I want to split this file to obtain single components I eot stuck:
here is my code

for  ((i=0;i<8;i=i+1));do
#splitting tensor into its components
shredder $((i*8)) 8 56 < dti.Bdouble > DT_comp${i}.img
#creating proper header
analyzeheader -voxeldims 1.75 1.75 2 -datadims 128 128 74 -datatype double
> DT_comp${i}.hdr
done

If I have correclty understood,my output should be

DT_comp0.img which contains exitcode
DT_comp1.img which contains log of unweighted signal
DT_comp2.img which is DT_xx
DT_comp3.img which is DT_xy
DT_comp4.img which is DT_xz
DT_comp5.img which is DT_yy
DT_comp6.img which is DT_yz
DT_comp7.img which is DT_zz

Now, to check if my assumptions are correct I go back to tensor by means of
nii2dt function (before doing that I merge volumes using fslmerge)

fslmerge -t tensor DT_xx.nii DT_xy.nii DT_xz.nii DT_yy.nii DT_yz.nii
DT_zz.nii

so

nii2dt -inputfile tensor.nii.gz > dt.Bdouble

eventually I calculate fa

cat dt.Bdouble | fa | voxel2image -outputroot my_fa -header tensor.nii.gz

But when I look at the results fa map is totally wrong as the fa values are
in the range [.9 1.2], which is impossible of course.

I also tried using linear option and addingo lns0 and mask (inverting
endianness as described for mask output of bet2 function) as well .In this
last case the code was

nii2dt -inputfile tensore.nii.gz -bgmask mask.img -lns0 DT_comp1.img >
dt.Bdouble

but with no amelioration at all.

Where am I wrong? Is the position of tensor components wrong?
Is the reconstruction back to camino tensor wrong?
Is shredder badly used?
Is it a problem of mask endianness?


Hope you can help me,

Best,
Alessandro
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