Dear SPM users,
the seemingly simple question is if a normalization of functional images (EPI)
will be more accurate using the following steps:
1) the structural image (usually T1) is co-registered to the mean EPI
2) normalization parameters are determined for the T1 (via unified
segmentation) and
3) normalization parameters are applied to EPI time series
The alternative would be to apply the unified segmentation procedure directly
to the mean EPI which provides normalization parameters for the time series.
Some people (usually neuroscientists) argue that the first procedure is more
accurate since the T1 provides much more spatial details (good contrast
between GM, WM and CSF) which improve the normalization.
Other people (usually MR physicists) argue that the distortions of the two
modalities (T1 weighted images vs. T2* weighted images) are quite different.
Therefore, good normalization parameters for the structural image are not
necessarily helpful in order to transform EPI images into standard MNI space
in the best possible way.
Is this debate still a "matter of taste" or is there any study that already
addressed this issue (which I am not able to find...)? I am aware of the
study by Crinion and colleagues (Neuroimage 2007) which addressed a related
but still different question. Are there any estimates of displacement using
the procedures described above?
Thanks a lot for your comments,
Thilo
--
Thilo Kellermann
RWTH Aachen University
Department of Psychiatry, Psychotherapy and Psychosomatics
JARA Translational Brain Medicine
Pauwelsstr. 30
52074 Aachen
Germany
Tel.: +49 (0)241 / 8089977
Fax.: +49 (0)241 / 8082401
E-Mail: [log in to unmask]
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