Hello Experts,
I am still using SPM 2. I was trying to normalize the PET data (data for Alzheimer's disease F18 compound) to a PET template, I used "write to normalize" option and used all the default settings, though the normalization is good the intensity in some of the brain areas is underestimated or overestimated. I thought of using the "parameter estimations" option.
In this I use "no weighting" and then "high regularization", this time the spatial fitting us good (same like the earlier), but the regional assessment is better. That means the values in the regions are as per expected. By regional assessment I mean the images for Healthy control provides less intense values in grey matter and the AD patient images shows high intensity in the grey matter. So I conclude that once I use high regularization the quantification closely resemble the qualitative read.
But I would like to know what exactly High regularization does and is it a better approach ?
Thank you.
Best Regards,
--
Abhinay D. Joshi
Drexel Hill, PA
Cellular:-817-995-3962
