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Thank you so much for making the code public! I tried to reproduce your results using the CRL atlas dataset. But found that I need to enter a larger parameter than the actual thickness to get the full volume.
I used the following code to get to the thickness of the data as [0.8,0.8,0.8]. img = nib.load(nii_file) #turn into numpy data = img.get_fdata() affine = img.affine resolution = affine.diagonal()[:3]
I have noticed that the results I get are similar to those in 'Cannot reproduce results on FeTA using your slicing strategy' (a closed issue). Could you clarify what are the limitations of the thickness parameter?
Hi NeSVoR team,
Thank you so much for making the code public! I tried to reproduce your results using the CRL atlas dataset. But found that I need to enter a larger parameter than the actual thickness to get the full volume.
I used the following code to get to the thickness of the data as [0.8,0.8,0.8].
img = nib.load(nii_file)
#turn into numpy
data = img.get_fdata()
affine = img.affine
resolution = affine.diagonal()[:3]
I used the following command for SVR:
nesvor reconstruct
--input-stacks .../STA33.nii.gz .../STA33.nii.gz .../STA33.nii.gz
--thicknesses 0.8 0.8 0.8
--output-volume .../3316.nii.gz
--bias-field-correction
--output-resolution 0.8
However, I got an incomplete volume:
If I change the command to
--thicknesses 1.4 1.4 1.4
I can then get the full volume:
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