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I'd rather you post this to the FSL list so that others can help and benefit from any answers. I'm not quite sure what you are trying to do, so it would be good if you gave more clarification on what you are trying to do. Peace, Matt. _____ From: Crystal Zhou [mailto:] Sent: Friday, June 22, 2012 2:56 PM To: [log in to unmask] Subject: Re: Averaging ProbtrackX DTI Hello Matt, Sorry - to clarify; what I'm inquiring about is that, my understanding is after doing all of these, the ROIs are now in diffusion space, but I'm not sure how to proceed to average the probtracks across different participants together. Thanks! Crystal On Fri, Jun 22, 2012 at 1:49 PM, Crystal Zhou <[log in to unmask]> wrote: Hello Matt, Sorry to email you personally; I was wondering what the next step is after all of the steps below are done. How would one view the finished product in FSL View? Thanks! Crystal ------------------------------------------------------ From: https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=FSL;f81fdae8.0911 Create Transforms: Create affine transform between FA and Template FA using FLIRT (lets call this diff2standard.mat), also output the linearly transformed FA map in the template space (lets call this data_FA2standard_affine.nii.gz) Create nonlinear transform between data_FA2standard_affine.nii.gz and the template FA (lets call this diff2standardwarp.nii.gz) Invert Transforms: Use convert_xfm -omat standard2diff.mat -inverse diff2standard.mat Use invwarp -w diff2standardwarp.nii.gz -o standard2diffwarp.nii.gz -r <native diffusion space file, e.g. nodif_brain_mask> Move ROIs from Standard Space to Structural Space: applywarp -i <ROI in standard space> -r <native diffusion space file, e.g. data_FA> -o <ROI in native space> -w standard2diffwarp.nii.gz --postmat=standard2diff.mat --interp=nn To test, you can do the following test to verify that you did everything correctly: applywarp -i <data_FA in diffusion space> -r <template FA> -o <data_FA in standard space> --premat=diff2standard.mat -w diff2standardwarp.nii.gz --interp=trilinear applywarp -i < data_FA in standard space > -r <native diffusion space file, e.g. data_FA> -o <data_FA in diffusion space 2> -w standard2diffwarp.nii.gz --postmat=standard2diff.mat --interp=trilinear The output image <data_FA in diffusion space 2> should line up exactly with the original image <data_FA in diffusion space> as you will have transformed the FA into standard space and then back again into diffusion space. Note that I use trilinear interpolation instead of nearest neighbour because the FA is an image with continuous values. Peace, Matt.