or, more accurately, I would like to ask if my understanding of the surface
registration, conversions and wb_command steps is correct.
Thanks,
Sean
On 15 January 2018 at 13:43, Seán Froudist Walsh <froud...@tcd.ie> wrote:
> Dear Matt and Tim,
>
> Thanks for your help.
>
> I moved the midthickness-new-out surface from the wb_shortcuts
> -freesurfer-resample-prep command back into the FreeSurfer volume space,
> by converting from RAS to voxel coordinates. This surface seemed to line up
> perfectly with the orig.nii anatomical in conformed FreeSurfer space. When
> I overlay the group average (s1200) myelin map on the midthickness-new-out
> surface it looks like it lines up great with the gyri/sulci.
>
> From this I understand that the surface mesh is overlaid in such a way as
> to impose anatomical correspondence between the native and HCP average
> brains, but the midthickness-new-out surface is still aligned with the
> native (conformed) brain. Is this correct?
>
> I managed to get the Nearest-Neighbour-like mapping I wanted done in
> Matlab. When I display this on the group average surfaces, it also looks
> pretty good. I just want to check that the workbench steps I have taken are
> correct.
>
> Best wishes,
>
> Sean
>
> On 3 January 2018 at 17:19, Timothy Coalson <tsc...@mst.edu> wrote:
>
>> The fs_LR 32k spheres use a resolution (vertex spacing) that is suitable
>> for 2mm fMRI data, but it sounds like you are using structural-resolution
>> voxels. As Matt says, I would put the fs_LR surface into your volume
>> space, and do only a single mapping, because nearest neighbor or enclosing
>> voxel mapping is extremely lossy - additionally, I would use the 164k
>> spheres instead.
>>
>> Other forms of resampling, meant for continuous data, are not as lossy
>> because they can approximate the underlying function, but "voxel identity"
>> is not a continuous function. I don't know exactly what you are doing, but
>> I would suggest mapping the data that *is* continuous onto fs_LR registered
>> surfaces, and then re-posing your "element identity" as vertex indices,
>> rather than T1w voxels. If this doesn't let you do what you want, then
>> maybe you can do per-subject independent volume analysis, and then map the
>> results of that onto the individual's surface before combining across
>> subjects?
>>
>> If you want to explain your bigger-picture goal, we might have other
>> useful suggestions.
>>
>> Tim
>>
>>
>> On Wed, Jan 3, 2018 at 11:58 AM, Glasser, Matthew <glass...@wustl.edu>
>> wrote:
>>
>>> I think I would probably resample the subject’s own FS_LR registered
>>> surfaces into the FreeSurfer space (an exact transformation) and then do a
>>> single mapping from volume to surface. You would need to figure out the
>>> affine matrix that describes this transform.
>>>
>>> Peace,
>>>
>>> Matt.
>>>
>>> From: <hcp-users-boun...@humanconnectome.org> on behalf of Seán
>>> Froudist Walsh <froud...@tcd.ie>
>>> Date: Wednesday, January 3, 2018 at 10:29 AM
>>> To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
>>> Subject: [HCP-Users] volume to average surface with Nearest Neighbour
>>> interpolation
>>>
>>> Dear HCP experts,
>>>
>>> I am interested in mapping individual voxels in a subject's FreeSurfer
>>> conformed space (orig.nii) onto the HCP template (fsaverage_LR) while
>>> maintaining the original voxel values.
>>>
>>> All of the voxels lie within the LH cortical ribbon in the (conformed)
>>> volume space. There are 186 voxels with non-zero values that act as unique
>>> identifiers, with all other voxels having a value of zero.
>>>
>>> I have prepared the native FreeSurfer to HCP transformations, then
>>> performed volume-to-surface mapping of the sample data, and finally applied
>>> the FreeSurfer-to-HCP transform to the sample data. I have tried to
>>> identify the options that perform something like Nearest Neighbour
>>> assignment, as I need to maintain the original values as identifiers. The
>>> problem I am facing is that volume-to-surface mapping as done below reduces
>>> the number of non-zero voxels/vertices from 186 to 94, and the
>>> Freesufer-to-HCP resampling reduces the number of non-zero vertices further
>>> from 94 to 13 non-zero points.
>>>
>>> I would greatly appreciate your guidance as to the best way to achieve
>>> my desired goal of obtaining all 186 vertices with their original values
>>> onto the HCP template. Should I map each voxel to the closest voxel on the
>>> FreeSurfer WM surface, or something similar?
>>>
>>> The commands I used are shown below.
>>>
>>> Many thanks,
>>>
>>> Sean
>>>
>>> wb_shortcuts -freesurfer-resample-prep lh.white.surf.gii
>>> lh.pial.surf.gii lh.sphere.FSave.reg.surf.gii HCP_S1200_GroupAvg_v1/standard
>>> _mesh_atlases/resample_fsaverage/fs_LR-deformed_to-fsaverage.L.sphere.32k_fs_LR.surf.gii
>>> lh.midthickness.surf.gii
>>> ${current_subject}.l.midthickness.32k_fs_LR.surf.gii
>>> lh.sphere.HCP.reg.surf.gii
>>>
>>> and then created a volume-to-surface mapping, while maintaining the
>>> original voxel/vertex values using
>>>
>>> wb_command -volume-to-surface-mapping '
>>> {current_subject}_samples_LH_cortex.nii.gz
>>> lh.midthickness.surf.gii samples_native.shape.gii -enclosing
>>>
>>>
>>>
>>> and then applied the transform using
>>>
>>> wb_command -metric-resample samples_native.shape.gii
>>> lh.sphere.HCP.reg.surf.gii HCP_S1200_GroupAvg_v1/standard
>>> _mesh_atlases/resample_fsaverage/fs_LR-deformed_to-fsaverage
>>> .L.sphere.32k_fs_LR.surf.gii BARYCENTRIC -largest {current_subject}
>>> _samples_HCP.shape.gii
>>>
>>>
>>> _______________________________________________
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>>> HCP-Users@humanconnectome.org
>>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>>>
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>>> HCP-Users@humanconnectome.org
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>>>
>>
>>
>
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