The conversion was done like this:

wb_command -gifti-label-to-roi
../../MNINonLinear/fsaverage_LR32k/102816.L.aparc.a2009s.32k_fs_LR.label.gii
L.STS.func.gii -name S_temporal_sup
surf2surf  -i
../../MNINonLinear/fsaverage_LR32k/102816.L.white.32k_fs_LR.surf.gii -o
L.STS.fsl_MNI_new.asc --outputtype=ASCII  --values=L.STS.func.gii

Is this what you were referring to?

-Maarten

On Sun, Jul 19, 2015 at 10:20 PM, Glasser, Matthew <[email protected]>
wrote:

>  The --onewaycondition flag doesn’t seem sensible with matrix3.  Also I
> don’t know what your command was for doing the conversion.  Here is the
> probtrackx2 call that didn’t make it onto the list:
>
>  probtrackx2 -x L.STS.fsl_MNI_new.asc --onewaycondition --omatrix3
> --target3=L.STS.fsl_MNI_new.asc
> --lrtarget3=brainmap_HCP/brainmap_filelist.txt -P 100 --forcedir
> --dir=./test_surf_track_STS_brainmap_seedspace -s
> ../Diffusion.bedpostX/merged -m nodif_brain_mask.nii.gz
> --seedref=../../MNINonLinear/T1w_restore.nii.gz -V 2 --opd --pd
> --distthresh3=2 --xfm=../../MNINonLinear/xfms/standard2acpc_dc.nii.gz
> --invxfm=../../MNINonLinear/xfms/acpc_dc2standard.nii.gz
>
>
>  Peace,
>
>
>  Matt.
>
>   From: Maarten Vaessen <[email protected]>
> Date: Sunday, July 19, 2015 at 12:03 PM
> To: Matt Glasser <[email protected]>
> Cc: "[email protected]" <[email protected]>
> Subject: Re: FW: [HCP-Users] tractography
>
>   In this case: seed region to whole brain connectivity. The STS seed is
> mainly for testing purposes (not as many seed points as the whole WM), the
> final analysis will use all WM voxels as seeds though. In fact,when I run
> the analysis with WM as the seed the results look equally strange: only
> connectivity to what appears to be the right inferior posterior cortex.
> Could this be an issue with the seed-space to dti-space parameters?
>
>  -M
>
> On Sun, Jul 19, 2015 at 5:31 PM, Glasser, Matthew <[email protected]
> > wrote:
>
>>  What is it that you are trying to achieve?  Usually one uses a seed of
>> all white matter voxels with matrix3.
>>
>>  Peace,
>>
>>  Matt.
>>
>>   From: Maarten Vaessen <[email protected]>
>> Date: Sunday, July 19, 2015 at 3:41 AM
>> To: Matt Glasser <[email protected]>
>> Subject: Re: [HCP-Users] tractography
>>
>>   Hi Matthew,
>>
>>  I tried to use the file you suggested, and I can convert the .dot
>> without problem. However, the results don't make any sense, so I think
>> there might be something wrong in my processing pipeline. Would you mind
>> having a quick look at it and see if I do something wrong?
>> Attached is the pipeline and a screenshot from the matrix as loaded in
>> MATLAB.
>> As you can see from the screenshot, there is only very limited number of
>> none zeros. And weirdest of all, they appear at column indices which are
>> probably somewhere in the right hemisphere (seed is in the left).
>>
>>  Thanks,
>>
>>  -Maarten
>>
>> On Wed, Jul 15, 2015 at 6:20 PM, Glasser, Matthew <
>> [email protected]> wrote:
>>
>>>  You should be able to use this file:
>>>
>>>
>>> https://github.com/Washington-University/Pipelines/blob/master/global/templates/91282_Greyordinates/91282_Greyordinates.dscalar.nii
>>>
>>>  Peace,
>>>
>>>  Matt.
>>>
>>>   From: <[email protected]> on behalf of Maarten
>>> Vaessen <[email protected]>
>>> Date: Wednesday, July 15, 2015 at 4:44 AM
>>> To: "[email protected]" <[email protected]>
>>> Subject: Re: [HCP-Users] tractography
>>>
>>>   Hello,
>>>
>>>
>>> I followed the guide lines below to create a dense connectome with 
>>> probtrackx. I was just wondering how to proceed with converting the .dot 
>>> file from probtrackx to cifti using wb_command -probtrackx-dot-convert (for 
>>> visualisation in wb_view). Specifically, what cifti file can I use as input 
>>> for the -row-cifti option? So, what files released with the HCP data 
>>> contain the correct brainmap?
>>>
>>>
>>> Thx
>>>
>>>
>>> -Maarten
>>>
>>>
>>>
>>>
>>>
>>> _______________________________________________________________
>>>
>>> Hi
>>>
>>> You need to create such a file that contains the 90k grayordinates. To 
>>> ensure
>>> consistency we do that in MNI 2mm space:
>>>
>>> - First create surface files in an FSL friendly format. Use the 32k 
>>> surfaces,
>>> as the vertices are ~2mm apart.
>>> Left Surface:
>>> surf2surf -i
>>> $Subject/MNINonLinear/fsaverage_LR32k/${Subject}.L.white.32k_fs_LR.surf.gii 
>>> -o
>>> white.L.asc --outputtype=ASCII
>>> --values=$Subject/MNINonLinear/fsaverage_LR32k//${Subject}.L.atlasroi.32k_fs_LR.shape.gii
>>>
>>> Right Surface:
>>> surf2surf -i
>>> $Subject/MNINonLinear/fsaverage_LR32k/${Subject}.R.white.32k_fs_LR.surf.gii 
>>> -o
>>> white.R.asc --outputtype=ASCII
>>> --values=$Subject/MNINonLinear/fsaverage_LR32k//${Subject}.R.atlasroi.32k_fs_LR.shape.gii
>>>
>>> - Then extract the volume subcortical files from e.g.
>>> $Subject/MNINonLinear/ROIs/Atlas_Rois.2.nii.gz, let’s say as
>>> CIFTI_Structure_{Name}.nii.gz, using e.g. fslmaths or your favourite tool 
>>> for
>>> ROI extraction. You should get 19 of these NIFTI files. (You can obviously 
>>> use
>>> your favourite subcortical parcellation here, but if you want consistency 
>>> with
>>> the CIFTI standard grayordinates, you need to resample the final results, 
>>> the
>>> file above ensures consistency).
>>>
>>> - Put all the filenames in a text file in the following sequence, to ensure
>>> consistency with the rest of the CIFTIs:
>>>
>>> white.L.asc
>>> white.R.asc
>>> CIFTI_STRUCTURE_ACCUMBENS_LEFT.nii.gz
>>> CIFTI_STRUCTURE_ACCUMBENS_RIGHT.nii.gz
>>> CIFTI_STRUCTURE_AMYGDALA_LEFT.nii.gz
>>> CIFTI_STRUCTURE_AMYGDALA_RIGHT.nii.gz
>>> CIFTI_STRUCTURE_BRAIN_STEM.nii.gz
>>> CIFTI_STRUCTURE_CAUDATE_LEFT.nii.gz
>>> CIFTI_STRUCTURE_CAUDATE_RIGHT.nii.gz
>>> CIFTI_STRUCTURE_CEREBELLUM_LEFT.nii.gz
>>> CIFTI_STRUCTURE_CEREBELLUM_RIGHT.nii.gz
>>> CIFTI_STRUCTURE_DIENCEPHALON_VENTRAL_LEFT.nii.gz
>>> CIFTI_STRUCTURE_DIENCEPHALON_VENTRAL_RIGHT.nii.gz
>>> CIFTI_STRUCTURE_HIPPOCAMPUS_LEFT.nii.gz
>>> CIFTI_STRUCTURE_HIPPOCAMPUS_RIGHT.nii.gz
>>> CIFTI_STRUCTURE_PALLIDUM_LEFT.nii.gz
>>> CIFTI_STRUCTURE_PALLIDUM_RIGHT.nii.gz
>>> CIFTI_STRUCTURE_PUTAMEN_LEFT.nii.gz
>>> CIFTI_STRUCTURE_PUTAMEN_RIGHT.nii.gz
>>> CIFTI_STRUCTURE_THALAMUS_LEFT.nii.gz
>>> CIFTI_STRUCTURE_THALAMUS_RIGHT.nii.gz
>>>
>>>
>>> - You can then use such a file in FSL probtrackx2 as a seed (for Matrix1) 
>>> or as
>>> a target3 (for Matrix3). Notice that running a single probtrackx2 command 
>>> with
>>> all these seed locations and with many samples per location will require 
>>> huge
>>> processing power and memory. In practice, we run multiple probtrackx2 in
>>> parallel, by splitting and parallelising the computation by using the 
>>> --rseed
>>> option in probtrackx2 and using a small number of samples --nsamples per
>>> instance. I.e. instead of running one command, which will attempt to 
>>> propagate
>>> 5000 curves per seed, we can run e.g. 100 instances of the above commands,
>>> using --nsamples=50 and --rseed=i, i=1..100. Results can then be combined 
>>> using
>>> fdt_matrix_merge (which however also needs quite a lot of memory to produce 
>>> the
>>> final dense connectomes, but at least it is one final process).
>>>
>>> - Another approach for parallelisation would be to split the seed locations 
>>> and
>>> merge the final matrices. There is no solution that fits all systems, you
>>> should try and find the best approach depending on your computing resources.
>>>
>>> Hope this helps
>>> Stam
>>>
>>>
>>>
>>>
>>>
>>> On 19 May 2015, at 01:01, David R. Haynor 
>>> <[email protected]<mailto:[email protected] <[email protected]>>>
>>> wrote:
>>>
>>> hi HCP,
>>>
>>> we are trying to do tractography using FSL and HCP data.  i have some 
>>> questions
>>> -- i suspect they have been answered already, but couldn't find those 
>>> answers:
>>>
>>> 1. is there a file containing the grayordinate coordinates in the diffusion
>>> space for a particular subject, both subcortical voxels and cortical 
>>> vertices?
>>>
>>> 2. if i want to use some cortical and subcortical voxels from the list of
>>> grayordinates as targets, do i have to run probtrackx2 twice (i.e. once for 
>>> the
>>> cortical surface vertices and once for the subcortical voxels), or can i 
>>> run it
>>> just once?
>>>
>>> 3. where is the label file for the grayordinate vertices/voxels for a given
>>> subject?
>>>
>>> thanks in advance.
>>>
>>> -dh
>>> _______________________________________________
>>> HCP-Users mailing 
>>> [email protected]<mailto:[email protected] 
>>> <[email protected]>>http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>>>
>>>
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>>> HCP-Users mailing 
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