Dear Michael,
>
> I am co-registering a volume of 70 DWI to an anatomical T1 scan as a step in many processes. To do this, I use fslsplit to divide the images into their separate volumes, then use BET on each individual image (just to brain extract the DWI images, as there is some skull residue on the outside of the images), then coregister each individual image, and then finally put them all back together using FSLmerge.
>
> However, the file outputted is about 8 GB larger than the file I initially inputted at the start of the process (the starting 70-volume DWI is 964 MB, the final 70-volume image after co-registering is 8.99 GB).
>
> I believe the large file size is slowing down the efficiency of other processes (since the image file size is so large), and I was wondering why this was the case and if there were any ways around this issue.
>
this does not sound like a good idea. We don’t recommend registering each dwi individually to the T1 space. We recommend registering all dwi:s and b0:s together (using eddy) and then calculating a single rigid-body transform diffusion->T1. We also do not recommend actually resampling the diffusion data into T1 space, but instead use the tools in Fdt that allows you to define seeds and masks in T1 space while keeping the data in native space.
The reasons for these recommendations is not first and foremost to save space, but to ensure that your bvecs are defined in the same space as your data when doing any processing. But by following those recommendations you will also solve your file size problems.
If you are not familiar with these things I would recommend doing the diffusion and tractography practicals from the FSL course (https://fsl.fmrib.ox.ac.uk/fslcourse/).
Jesper
> Thanks in advance!
>
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