Hi - you could scale the values just using avwmaths, but I doubt this will
make any difference. What matters is the ratio of contrast (between
different tissue types) to the noise levels.
So it is most likely that your poorer results are due to very low CNR in
the data - if you'd like to email me directly a compressed example image
we could take a quick look.
Cheers.
On Thu, 2 Dec 2004, Lee, Sang wrote:
> I have a question....
> I'm trying to segment CSF, Gray, and White matter of brain using BET and
> FAST.
> I found out that result of some data set doesn't look good as others.
> After FAST procedure, alot of gray matter pixels are separated to be CSF
> pixels. I did pixel value analysis on these data sets, and i found out that
> pixel intensity of these data sets are very low (e.g. CSF=10, GM=20, WM=40).
> Those with good results have much higher intensities (e.g. CSF=100, GM=200,
> WM=400).
> Is there a way still segment brain volume correctly on those data sets with
> low pixel intensities?
> I'm assuming that if somehow i can scale the pixel values by factor of 10
> then i'll have intensity similar to "good-result" producing data sets. Is
> there a way for me to scale the images?
>
> Thanks.
>
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Stephen M. Smith DPhil
Associate Director, FMRIB and Analysis Research Coordinator
Oxford University Centre for Functional MRI of the Brain
John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK
+44 (0) 1865 222726 (fax 222717)
[log in to unmask] http://www.fmrib.ox.ac.uk/~steve
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