Dear Xiujuan,
> I was using fnirt and it took many hours (>6) to register two
> images. Is it a
> normal run time or did I do something wrong? The input images have
> a voxel
> dimension of 128x160x128, and I used the default parameter
> settings. The
> images were affine-aligned already, so I didn't do it again. The
> log file is
> attached. How can I improve the efficiency besides cropping the
> input images
> to a smaller size and specifying a subsampling of 2 at the lowest
> level? Thanks!
It seems you have run it with the "default default" parameters. I
would instead recommend you to start with one of the configuration
files (e.g. the T1->MNI152 one) and then make changes to that for
your specific case.
As for execution time it does sound much. One thing to look out for
is if it starts to page/swap or not. If your machine is able to hold
everything in RAM, rather than having to swap things back and forth
to disc, things will be much smoother. The things I would suggest to
do is
1. Specify subsampling 2 at lowest level. You do not really need a
resolution higher than 2mm in the images to estimate warps with 10mm.
The 2-3mm image resolution you get from a subsampling of 2 is more
than sufficient. You should also be aware that this does NOT mean
that your results will have a 2mm resolution. They will have the
original resolution and will be in the space of the image you
specifies as --ref.
2. Crop the image you use as --ref. Make sure that the image-matrix
is "tight" around the brain in the image you use as --ref. Have a
look at the MNI152 images to get an idea of what I mean by "tight".
3. Use --splineorder=2.
This will have an impact both on the amount of calculations that are
performed, and on the RAM needed. If you
4. Use --numprec=double.
This will have an impact on the RAM needed.
Good luck Jesper
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