Dear All,
for a simulation I would like to select a real t-map and then re-create
sham t-maps with similar signal intensities (but different normal
distributions) and spatial coherence.
I can of course easily generate such distributions using Matlab's rand,
randn, and random functions, but the problem is that the values of
course go to hell when I then smooth the images when I want to introduce
a similar spatial coherence pattern as in the real image. I have tried
rescaling to the original distribution after smoothing as well as
estimating the distribution from unsmoothed maps, but each approach has
distinct disadvantages. Has anyone tried something like this before and
would be willing to share some wisdom?
Thanks,
Marko
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PD Dr. med. Marko Wilke
Facharzt für Kinder- und Jugendmedizin
Leiter, Experimentelle Pädiatrische Neurobildgebung
Universitäts-Kinderklinik
Abt. III (Neuropädiatrie)
Marko Wilke, MD, PhD
Pediatrician
Head, Experimental Pediatric Neuroimaging
University Children's Hospital
Dept. III (Pediatric Neurology)
Hoppe-Seyler-Str. 1
D - 72076 Tübingen, Germany
Tel. +49 7071 29-83416
Fax +49 7071 29-5473
[log in to unmask]
http://www.medizin.uni-tuebingen.de/kinder/epn/
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