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You probably want to use TBSS to get around registration issues that arise when you compare FA values across different subjects... You may want to have a look at the manual: www.fmrib.ox.ac.uk/fsl/tbss Saad. On 18 Jan 2008, at 16:45, Jiansong Xu wrote: > > Thanks again. See below. > >> >> >> fslstats can get you pretty far in analyzing your FA values after >> masking, but I like to bring the image into matlab. What are you >> looking to do for your FA analysis? > > I'm not sure yet. The basic idea is that we have two groups. One > is control, and the other is patients. We define the ROIs, then I > will extract the mean FA values in each ROI, and put these values > into SPSS for t-test. Is this idea too naive? > > Best > > Jiansong > > > > >> >> >> ted >> >> On Jan 18, 2008 11:04 AM, Jiansong Xu <[log in to unmask]> wrote: >> Ted: >> >> Thanks a lot. My bvales look Ok without any manipulation after >> conversion by using MRIconvert. They are similar to the numbers in >> the following tutorial ( http://www.sph.sc.edu/comd/rorden/ >> workshop/fsl/dti/). >> >> Can I use featqurey to extract the FA values? I was told that we >> can use featquery to get BOLD signal changes in ROI analysis of >> functional images. >> >> Best Regards. >> >> >> On Jan 18, 2008, at 10:43 AM, Ted Yanagihara wrote: >> >>> >>> >>> On Jan 18, 2008 10:02 AM, Jiansong Xu <[log in to unmask]> wrote: >>> Dear Friends: >>> >>> I'm learning how to analyze DTI data with FSL(FDT), and I'm >>> wondering >>> if any one can make comments about my procedures described below. >>> >>> My DTI data were acquired with a Simens Trio 3T scanner. 32 >>> directions. b=1000 >>> >>> (I) Use MRIconvert to convert the DICOM data into NIFTI format for >>> DTI. The conversion created >>> 1. one textile file with bvalues >>> 2. one textile file with bvecs >>> 3. one image file with b0 >>> 4. 32 image files with b1000 >>> >>> My question here is: Do I need to do any thing with the number in >>> the >>> bvalues and bvecs file before using the two files, e.g., normalize? >>> >>> With MRIconvert you need to change all the bvalues except the >>> first one from zero to 1000. I believe the program does not do >>> this for you, so you probably have 32 zeros in the original >>> bvalue file. Depending on your scanner, you may need to flip the >>> signs in a row of your bvecs. You will have to check the output >>> after fitting the tensors. There are a few posts on this list >>> about this if you need help with it, I ran into the same problem >>> a while back. >>> >>> >>> (II) Use fslmerge to merge all image files into 4D file. The 4D file >>> has 33 images, and the b0 image is the first one. Now I remove >>> all 3D >>> image files from the directory, so that the directory has 3 files >>> left, one for bvalues, one for bvecs, one for 4D images. >>> >>> (III) Rename the three files, so that their names are: set00_bvalus, >>> set00_bvecs, set00_data.nii.gz >>> My question here is: how strict is this rule for file naming? >>> >>> (IV) Use FDT to do Eddy current correction. The input file is >>> set00_data.nii.gz, the output is set00_corr.nii.gz >>> >>> (V) Use BET to create binary mask. The input file is >>> set00_corr.nii.gz >>> >>> (VI) Use DTIFIT Reconstruct diffusion tensors to create FA >>> image. The >>> input file is set00_corr.nii.gz. >>> >>> Sorry, I am not familiar with this naming system and I don't know >>> if bedpostX will recognize those files automatically, but I >>> believe it would be easier if you used the following convention. >>> Otherwise, you could specify the individual files using the fdt GUI. >>> >>> bvecs >>> bvals -Remember to change those zeros to 1000s >>> data.nii.gz -This is your eddy current corrected diffusion image >>> nodif_brain_mask.nii.gz -This is the mask from the BETed no >>> diffusion image >>> >>> >>> >>> Now I get dti_FA.nii.gz file. Is this file have the FA values? >>> >>> Yes, this is your FA map for that subject. You can open it in >>> FSLview and see the FA intensities at each voxel. You can check >>> this by looking at the ventricles, which should be close to zero, >>> and the corpus callosum, which should be in the 0.7-0.8 range. >>> >>> >>> >>> If I want to do ROI analysis, how can I extract the FA values after >>> the ROI is defined, which FSL should I use? >>> >>> Draw a binary mask in FSLview and then multiply it by your FA >>> image. This will zero all the voxels in the FA image that are not >>> included in your mask. The command would be something like this: >>> fslmaths FA_image -mul mask_image output_name >>> >>> You can then do various things with the output, such as find the >>> mean FA value: fslstats output_name -M >>> >>> >>> Your comments are highly appreciated. >>> >>> Jiansong >>> >>> Good Luck! >>> >>> ted >> >> > ------------------------------------------------------------------------ --- Saad Jbabdi, Postdoctoral Research Assistant, Oxford University FMRIB Centre FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK +44 (0) 1865 222545 (fax 222717) [log in to unmask] http://www.fmrib.ox.ac.uk/~saad ------------------------------------------------------------------------ ---