I have been reading about texture analysis and feature extraction in T1-weighted MR images in case of the presence of tumor, multiple sclerosis or even for Alzheimer disease. This is very resonable since the presence of such maladies induces some textural changes in the brain.
I would like then to know if textural analysis would be important for extracting features from brain T1-weighted MR images for aging study.
To be more clear, I have different images for a subject that have been acquired at different intervals of its life. In addition to features such as GM and WM volumes, cortical thickness, etc ..., I would like to know if textural features can be extraxted from the images. Would they be meaningful in our study? Or in other words, do the microchanges in the brain due to aging appear on the macroscale on the T1-weighted images and thus induce textural changes in the brain regions?
Thank you
I like this question and am curious about whether some references will come up in this discussion. In any case, in my opinion, the idea is valid and worth pursuing.
Even at high fields, the spacial resolution achievable is probably a few tens of micrometers (edge length of a minimum cubic voxel) which may be too low, but maybe not (I am not a medical expert). In any case, texture analysis makes sense to me, conceptually and also as software feasibility.
Thank you for your feedbacks. As I was looking into the literature of brain aging , I noticed that only parameters studied are related to volumes and thicknesses of different regions and nothing mentioned concerning textural features and changes. I haven't found, until now, a literature that confirms textural analysis as useful or non-useful for the aging study. I think it is worth the trial.
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