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closeMRI Spatial Normalization and Tissue Classification
Posted by LuisIbanez on 29 Dec 2007 at 14:12 GMT
To the authors:
Could you please elaborate on the technique(s) that you used for spatial normalization ?
I'm assuming that you may have had to register all the brains to a single subject, or to build a brain atlas. If so, I would be interested learning more about how you performed this registration.
For example, did you used rigid, affine or deformable(non-linear) transforms ?
I would also be interested in more details regarding the segmentation technique that you used for tissue classification (WM, GM, CSF).
The statistical significance of your findings should be scaled relative to the reliability of the registration and segmentation techniques that led to the identification of the gray matter tissue.
I would appreciate your comments,
Regards,
Luis Ibanez
Senior Research Engineer
Kitware Inc.
RE: MRI Spatial Normalization and Tissue Classification
ogranert replied to LuisIbanez on 18 Sep 2009 at 08:53 GMT
Dear Luis Ibanez,
Thank you very much for your interest. We have performed the image processing with the SPM2 software package as provided by the Wellcome Trust Centre for Neuroimageing. The SPM software is open source and is provided as a Matlab toolbox. The files can be downloaded from the following website:
http://www.fil.ion.ucl.ac...
There is a lot of documentation freely available that describes the segmentation procedure and the algorithm used for registration and tissue classification.
For example you can look into the SPM wikibook:
http://en.wikibooks.org/w...
or read the SPM5 manual (which uses a slightly modified segmentation procedure)
http://www.fil.ion.ucl.ac...
If you are really interested in the details you should look into the SPM2 source code.
We are aware of the criticism and discussions related to the VBM method (see section "General technical references" in the wikipedia article about VBM: http://en.wikipedia.org/w...).
However, in our opinion the critical papers about VBM always miss some of the processing steps (e.g. the segmentation step) and may therefore come to misleading conclusions.
Best regards,
Oliver Granert