Hi,
I read an article entitled "Resolving the Brainstem Contributions to Attentional Analgesia" in J Neurosci and here have a question about DARTEL. My prior understanding is that DARTEL enhances intersubject registration and thus improves localization and sensitivity in analyses. Usually, DARTEL contains the following steps:
(1). Segment: it produces tissue class images, i.e., c1*.img and c2*.img.
(2). Initial import: it produces rigidly transformed tissue class images, i.e., rc1*.img and rc2*.img.
(3). Run DARTEL: it produced template_6.nii that parameterizes affine transformation, and a single u_rc1*.nii that parameterizes the nonlinear deformations.
I can then use template_6.nii and u_rc1*.nii to, e.g. normalize EPI into MNI space.
But this paper did not use DARTEL for normalization, but use it to produce brainstem masks. In Methods:
"To aid identification of brainstem nuclei, a gray matter probability map was constructed using the DARTEL spatial normalization technique available in SPM8. Briefly, T2-weighted volumetric data were segmented using the VBM8 toolbox into gray, white, CSF, and other tissue types, and the segmented gray matter maps registered to one another using the DARTEL algorithm. The final result is a probabilistic template specific to the study group, which was then transformed into the space of the MNI atlas. With the threshold for the probabilistic map set at p 0.7 (i.e., at least 70% gray matter), masks were defined for the PAG, RVM, and LC taking advantage of the inherent high contrast between the gray and white matter structures of the brainstem (see Fig. 2). These were validated with reference to anatomical sections on a human brainstem atlas (Naidich et al., 2009)."
My question is, how can I create a probabilistic template (also called "a probabilistic gray matter atlas" in the figure legend of Fig. 2) for the following thresholding at 0.7 and confirmation by a brainstem atlas? Is this exactly template_6.nii? Also, why they used T2-weighted but not T1-weighted images?
Thank you.
Mike
|