Normalize Pyradiomics features by the number of pixels (Volume)

Hey guys,
I am extracting radiomics from several different volume ROIS. I am afraid the ROI volume affects my evaluation, since many radiomic features are not divided by the number of pixels. I did even read an article speaking about the bias caused by volume yet present in many features.
I believe a reasonable solution would be to divide those non-volume-normalized features by the number of pixels.

What do you guys think?

ARTICLE: Radiomics features of the primary tumor fail to improve prediction of overall survival in large cohorts of CT- and PET-imaged head and neck cancer patients, by Rachel B. Ger. 2019.