I am using @auto_tlrc to convert my resting-state fMRI data to MNI152. After that, about 1/3 of the files get really huge. The input data is 610MB. The shape of nii file is [100 100 80 200]. The output data is 3.71GB, with shape [161 191 151 200]. The others (2/3 participants’ files) are 138.3MB, with shape [54 64 50 200]. I wonder which one is correct. Dose files usually get larger after the convert or smaller?
That is simply because of the the larger box of the result.
161x191x151 / (10010080) ~= 5.8, and 610 * 5.8 = 3538.
I don’t think that @auto_tlrc has any ability to specify a master output grid. But it would be possible to extract the warp and apply it with 3dAllineate instead, which does have a -master option for the output grid.
Are the voxels really 1mm isotropic? What was the original voxel size?
Hi Rick,
Thank you for your reply. The orignal rs file size is [80 80 45 200], voxel: 3 mm x 3 mm x 3 mm, 200 volumes.
Maybe I need to set -dxyz 3 in this case?
That is what we tend to do, stay close to the original voxel size. When processed with afni_proc.py, the output is (by default, at least) isotropic based on the minimum voxel dimension, truncated to 3 significant bits. Here, 3mm is already truncated, and would be used for the result.
Going from 3mm^3 to 1mm^3 is a factor of 27 in data storage, that would make a big difference. Using 3mm would not be as pretty, but it would be more honest to the data, in some sense.
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National Institute of Mental Health (NIMH) is part of the National Institutes of
Health (NIH), a component of the U.S. Department of Health and Human
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