Nibabel load bottlenecking

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1

I’ve been profiling some code, where a processing bottleneck occurs (method 'decompress' of 'zlib.Decompress' objects}). I believe this is from my nibabel.load command for loading large resting state nifti files (1.2G; shape=(88, 88, 60, 1130)). Loading one file can take 8-11 seconds, and I’m attempting to load multiple files per subject, across many subjects in a dataset. To save time and memory, I’d like to simply load a single volume, but haven’t been able to do so. My code is as follows:

import nibabel as nib
img_vol = nib.load('rsfMRI.nii.gz').dataobj[..., -1]

I was wondering if there’s a way to speed this loading process in nibabel, or if this is to be expected given the large file sizes?

2

Just realized that the issue is due to selecting the last volume. Faster solution is to take the first volume (or an earlier on in general).

img_vol = nib.load('rsfMRI.nii.gz').dataobj[..., 0]

3

If you have indexed-gzip installed, you will dramatically speed up slicing the image. It does this automatically with no configuration needed.

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