This depends on what you want to acchieve, Currently PyRadiomics requires you to provide a mask, always. However, if you want to extract from the whole image, you can easily generate a ‘full’ mask in python:
import SimpleITK as sitk
import numpy as np
im = sitk.ReadImage('path/to/image.nrrd')
ma_arr = np.ones(im.GetSize()[::-1]) # reverse the order as image is xyz, array is zyx
ma = sitk.GetImageFromArray(ma_arr)
ma.CopyInformation(im) # Copy geometric info
from radiomics.featureextractor import RadiomicsFeatureExtractor
extractor = RadiomicsFeatureExtractor('path/to/params.yml')
features = extractor.execute(im, ma)
Be aware that this gives features about the texture of the entire image! i.e. a single value per image, for the entire image. If you want more local information, try using voxel-based radiomics:
extractor.execute(im, ma, voxelBased=True)
Be aware that this process will take some time as features are calculated for each voxel!