Perfect, thank you
On 17 January 2018 at 18:52, Timothy Coalson <tsc...@mst.edu> wrote:
> Inline comments.
>
> Tim
>
> On Mon, Jan 15, 2018 at 12:43 PM, 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?
>>
>
> You are close, and the issue might only be terminology, and Matt mostly
> covered it. Surface registration doesn't change the shape of the brain,
> but group averaging surfaces does change the shape - group average surfaces
> don't look like a normal brain, they are much smoother. I wouldn't call it
> "anatomical correspondence" between the HCP average surface and the
> subject, because to me that implies that the coordinates of the surfaces
> line up (which they won't). The thing that is usually most important is
> what registration was used to generate the registered sphere - in this
> case, it sounds like you used the freesurfer-generated registered sphere,
> so your registration type is freesurfer. This determines what kind of
> correspondence you have across subjects processed the same way (for group
> analysis).
>
> Both midthickness-current-out and midthickness-new-out will align with the
> same volume files, the only difference between them is in how they fit
> triangles to the contour of the surface (how many triangles, how they are
> numbered, how much they vary in size...). Specifically,
> midthickness-new-out will have the same number of triangles, with each
> triangle in a corresponding location, across all subjects you do this
> procedure with, so you can therefore combine vertexwise data across such
> subjects. Additionally, because you used our atlas resampling from
> freesurfer to fs_LR, you are now set up to compare across hemispheres, or
> to HCP data, without much additional effort.
>
>
>> 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
>>>>
>>>>
>>>> _______________________________________________
>>>> HCP-Users mailing list
>>>> HCP-Users@humanconnectome.org
>>>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>>>>
>>>> _______________________________________________
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>>>>
>>>
>>>
>>
>
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