Hi all, how to functionally ranked the voxel according to their T values.
You could use Python code as below. You can also apply masks to only consider voxels inside a specific region. Below I apply a very simple mask: excluding voxels less than or equal to zero. However, this masking step could just as well refer to a region of interest image (where the region of interest had positive values).
import os import numpy as np import nibabel as nib fnm = 'spmMotor.nii.gz' img = nib.load(fnm) data = img.get_fdata() print("Intensity range: %g..%g"% (np.amin(data), np.amax(data))) print("1st percentile: %g"% (np.percentile(data, 1))) print("99th percentile: %g"% (np.percentile(data, 99))) datapos = data[data>0] print("1st percentile of positive values: %g"% (np.percentile(datapos, 1))) print("99th percentile of positive values: %g"% (np.percentile(datapos, 99)))
If you use the sample spm included with MRIcroGL you will get:
Intensity range: -6.86236..12.1565 1st percentile: -1.58045 99th percentile: 2.97615 1st percentile of positive values: 0.0211246 99th percentile of positive values: 5.81193
Thanks for you repaly.