Hi Ce,
all of what you want to achieve can be done using functonality within
Matlab and spm in a pretty straigtforward way, once you know the
functions to call. I would recommend the following:
> 1) Threshold the T-map.
Use spm_select (potentially with a 'list' syntax to automatically find
your images of interest), then spm_vol, then spm_read_vols, then spm_u,
spm_uc_FDR, or spm_uc to find your threshold, and apply that to the
matrix generated by spm_read_vols.
> 2) Identify the coordinates of all local maximas on the thresholded map.
My favorite function for that is findn, available on the Mathworks file
exchange. It gives you x, y, and z coordinates of any non-zero voxel in
a matrix.
> 3) For each local maxima, locate the coordinates of the activated voxels
> that fall within the same cluster as the current local maxima.
You can use spm_bwlabel to this effect, which generates clusters from a
thresholded map.
> 4) Generate a mask of the result of step 3.
You can use the first output of spm_bwlabel for that, too, potentially
using Matlab's ismember function to find which voxels belong to which
cluster.
Hope this helps,
Marko
--
____________________________________________________
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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