Hi Jeremy,
You just might want to use the command line tool flirt_average. This
takes care of most of the things you mentioned and gives pretty good
results. It also allows all options for flirt.
By combining two images you increase the SNR of the image, thus it is
good to combine images.
If you use the same modality and the same subject it is not really
necessary to extract the brain. However, to simplify things you can run
bet and create a binary brain mask, that you could use as weight (flirt
options refweight and inweight).
As cost function I would recomend normalized correlation, because you
have the same modality. However, I haven't notice much difference than
using correlation ratio.
Using sinc interpolation in my opinion does not improve the quality
much, but increases computational time quiet a bit, thus I would
recommend trilinear.
A thin the flirt_average script is not doing is the normalization of the
single scans before averaging. This step might be usefull when there is
a difference in image intensities. Just change the last line of the
script for example to:
fslmaths $output -inm 1000 -Tmean $output
Good luck,
wolf
Jeremy R. Gray wrote:
> Hi FSL'ers,
>
> I'm new to FSL (really liking it so far). I'm hoping for advice on the best
> approach to combining two MPRAGE images from the same subject. This is for
> 100+ subjects, and so I will script it. the idea is to end up with one
> higher-quality image to use in structural analyses. one image is from the
> start of the scan session, and the other from the end (~1.25 hours later).
>
> flirt seems like the way to go, so I searched the archives and the flirt
> lecture notes from the web (pdf), but did not see something on combining
> MPRAGES. my apologies if I missed it.
>
> one question is:
> - is it always better to combine two images? presumably there could be
> pathological cases (e.g., lots of movement resulting in a blurry image)
> where a single good MPRAGE is better than combining one good and one bad --
> so is there a way to tell that you are in such a situation (especially for a
> script to tell this)? just inspect afterwards?
>
> using flirt seems straightforward:
> - prior to flirt, run bet -B on each image (= my interpretation of flirt
> lecture slide #45). but maybe for having the same sequence, the non-brain
> stuff will actually help the alignment? and maybe doing bet on the combined
> image will give a better extraction (for having a higher-quality input)?
>
> - just pick one image to use as the reference, "better quality" should be
> moot with 2 MPRAGEs (except in pathological cases)
>
> - a rigid body 6-parameter model seems fine because the images are from the
> same subject, same scanner, same day. is there any possible advantage to
> more df for my situation?
>
> - search option = "already virtually aligned" is probably fine
>
> - cost function: correlation ratio is the default in the GUI. however, I've
> heard that normalized mutual information is very good, in particular is
> robust to small non-brain bits left over from brain extraction. any reason
> not to use NMI (especially if I do bet prior to flirt)?
>
> - trilinear interpolation (= default) -- any advantage to sinc?
>
> thanks much,
>
> --Jeremy
>
>
> /*-------------------------------------------------------------
> Jeremy R. Gray, PhD
> Assistant Professor, Yale University
> Dept. of Psychology & Interdepartmental Neuroscience Program
> mail Box 208205, New Haven, CT 06520-8205 USA
> office SSS 212
> http://maps.google.com/maps?q=1+Prospect+St,New+Haven
> phone 203-432-9615 (office)
> fax 203-432-7172 (include Attn J. Gray)
> web http://www.yale.edu/scan/
> -------------------------------------------------------------*/
>
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