FSLers,
I stumbled upon a difference in some of my data I wasn't expecting. I have
a set of cases processed through FSL 4.0.1/FEAT 5.91 and some separate data
through FSL 4.1.0/FEAT 5.98. The 4.0.1 data is 4D grand mean scaled to
10,000 using the "fslmaths -ing 10000" command, while the 4.1.0 data is
not, however for the couple cases I looked at they typically have 4D means
of around 7500-8000. Is the 4.1.0 data scaled to a different pre-set
constant? It looks like there are some other behind the scenes changes as
well in the masking/betting. I am NOT trying to combine these two datasets
together, just trying to understand how the 4D normalization is working in
the 4.1.0 data. Thanks for any info!
Chris Bell
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