When I compare the thickness measure among subjects, I have to resample and
smooth the thickness, so that each data have the same number of vertices and
which are in correspondence with one another across subjects.
Now I have .curv files or .sulc files for each subject and would like to make
group analysis for these datasets. To compare the curvature and sulc
measures, can I follow the same procedures as above ( ie I repeat the
resampling and smoothing steps as I do for thickness)? If yes, how should I
choose FWHM？
By the way, could you recommend me relevant papers that calculates the
following indices :
k1 maximum curvature
k2 minimum curvature
K Gaussian = k1*k2
H Mean = 0.5*(k1+k2)
C Curvedness = sqrt(0.5*(k1*k1+k2*k2))
S Sharpness = (k1 - k2)^2
BE Bending Energy = k1*k1 + k2*k2
SI Shape Index = atan((k1+k2)/(k2-k1))
FI Folding Index = |k1|*(|k1| - |k2|)
.sulc,
.curv
So that I can get a better understanding of what the above measures reflects.
Thanks a lot!
yczhang
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