Is there any comprehensive quantitative comparison of volume and surface based (potentially multimodal) registration methods? The best paper I know of (Klein 2010 - http://www.sciencedirect.com/science/article/pii/S105381191000114X) recommended using custom study templates over external templates (like fsaverage or MNI152). The authors could not, however, recommend volume over surface (or other way around) due to resampling errors. Here's the relevant paragraph:
"The resampling tests demonstrate that, for almost every region, the resampling error is too great to distinguish between the performance of top-ranking volume and surface registration methods (SyN, FreeSurfer, and Spherical Demons, all using customized optimal average templates). Based on these results, it may not be possible to directly compare evaluations of these surface and volume registration methods using the present resampling methods, when considering the full surface or full volume or the full extent of their label boundaries." I was wondering if there is some other literature I'm missing that overcomes the aforementioned resampling problems and provides a quantitative comparison between the two registration approaches. Best, Chris On Fri, Aug 12, 2016 at 10:36 AM, Glasser, Matthew <[email protected]> wrote: > Use of diffusion fiber orientation information might indeed improve > volume-based alignment of the white matter and is worth pursuing. > > I don’t think using areal features in the volume will address the core > limitation of volume-based cortical areal registration. This will not > change the fundamental issue of incompatibilities in folding patterns > across subjects creating topological matching issues. This sort of thing > occurs in 2D on the surface as well, though much less frequently, where the > spatial relationships between an area and its neighbors are so different > that one would have to tear the surface to align the areas. When this > happens something like the cortical areal classifier is needed to achieve > correspondence across subjects. For the same reason that topological > incompatibilities are not fixable in 2D on the surface, the more frequent > ones that occur in 3D in the volume will also not be fixable. > > The overall point is that when we compare across subjects, we need to be > sure that we are comparing like with like. If we are not doing that we > aren’t making a valid comparison. > > Peace, > > Matt. > > From: "Horn,Andreas (BIDMC - Neurology)" <[email protected]> > Date: Friday, August 12, 2016 at 8:49 AM > To: Timothy Coalson <[email protected]> > Cc: "Reid, A.T. (Andrew)" <[email protected]>, " > [email protected]" <[email protected]>, Matt > Glasser <[email protected]> > Subject: Re: [HCP-Users] Surface parcellation to volume > > Dear Tim and Matt, > > thank you very much for your detailed and insightful answers. I learned a > lot and agree to nearly everything you said. Especially, I totally agree > that we should not use T1w -> T1w Template nonlinear volumetric warps + > smoothing nowadays anymore. Regarding the sulcus-on-gyrus mismatches for > techniques such as DARTEL/Shoot/ANTs that Matt pointed out, I wonder to > what extent the inclusion of FA and e.g. rs-fMRI eigenvector centrality > maps in multispectral warps could minimize such mismatches. I agree that it > would be nontrivial to add a real connectome (i.e. edges) to the volumetric > deformation problem. And again, I lack empirical data to be able to say how > much impact either method would really have on results – a fair comparison > study would be great and important to the field in my view. On the other > hand, I agree that MSM is an awesome technique and why should we not just > use it since it’s available. > > Best, Andy > > > Am 11.08.2016 um 17:49 schrieb Timothy Coalson <[email protected]>: > > Sorry, I was not precise enough in my language - my earlier comments > should be considered in the context of cortex only (the MMP v1.0 is > cortex-only). > > The "volume-based group-average methods" methods I meant to refer to are > when people analyze the whole brain, including cortical data, by doing some > T1w MNI registration, and then smooth the volumes (to partially make up for > deficiencies in the cortical registration), and then average all signal > across subjects (including cortical), still in the volume. This has a > whole host of problems, but some people persist in doing things this way. > > Other replies inline. > > Tim > > > On Thu, Aug 11, 2016 at 10:03 AM, Horn,Andreas (BIDMC - Neurology) < > [email protected]> wrote: > >> Hi Tim, >> >> Yes, of course it’s compared to an average surface – but isn’t that the >> final goal of brain mapping to somehow define regions within a well-defined >> space? >> > > I would say it is more specific than that - the ideal goal is to define, > for each subject, the locations in each atlas region. In the case of the > HCP MMP v1.0, it only defines cortical regions, in terms of areal features > (for instance, functional connectivity). A group-average cortical surface > has very little of the folding (geometric definition) you will find in any > contributing subject, which makes it a notably inferior method for > transferring cortical data to or from a nonlinear-registered volume > template (we aren't enthusiastic about the MMP cortical data being used as > a volume file, but there are better ways to get there than group average > surfaces). > > >> I totally agree with you and Matt that there are a lot of advantages of >> surface based processing, especially when we are predominantly interested >> in only the cortex. However, I find it a bit too dogmatic to say that >> something is only feasible using surface-based analyses and that >> surface-based approaches are the (only) thing the field should be doing. >> > > Our method of generating the HCP MMP v1.0 relied heavily on the MSMAll > surface registration. It was a very critical step to being able to do what > we did, and I don't know of volume registrations that achieve comparable > areal feature alignment in cortex (and most of the ones that I know people > use only register anatomy, and don't try to use things like functional > connectivity). Perhaps Matt or David have done a more thorough survey of > volume methods for registering areal features in cortex. > > >> Some things are definitely easier using surfaces (since we can reduce the >> 3D problem to a 2D problem by projecting the surface to a sphere). Also, >> it’s much easier to inflate resolution since the data points are >> drastically reduced. However, my feeling is that volume based approaches >> have also improved a lot over the last years with multispectral >> diffeomorphic processes that are often segmentation based, i.e. reduce the >> warping techniques between single subject’s cortices and an average mean to >> a more or less 2-D problem as well. In the end, any warp is a set of >> coordinates projected to another set of coordinates, no matter if doing >> this on a surface or a volume, right? The warp is just sometimes more >> constrained on a surface. >> > > Surface registration also doesn't require changing the anatomical shape of > the cortex in order to enable cross-subject comparisons or group > averaging. This makes it easier to regularize the registration in a way > that is not penalized for an unusual folding pattern. As before, Matt or > David may be in a better position to comment regarding the current state of > the field in volume registration of cortical areal features. > > >> I’d be very interested in good comparison studies that show superior >> results using the most advanced surface-based techniques in comparison to >> most-advanced volume-based techniques (like e.g. multispectral ANTs SyN >> deformations using the OASIS templates or MNI 2009b NLIN series or similar). >> > > This would be an interesting comparison to do (and perhaps include a more > "traditional" volume method as well to put any performance difference in > perspective). > > >> I’d still guess that the surface based approaches would be superior on >> the cortex but I wonder how much impact it would really have. Really >> curious about how you did this in the upcoming Nature Neuroscience article >> and to which volumetric analyses you compared your results. >> > > As I said, my comments were intended in the context of cortex, that is, > where the HCP MMP v1.0 is defined. It is likely that for a future version > including subcortical components, we would use volume registration and > voxel representation for those, as they are not as challenging for volume > registration (don't have cortical folding variability). > > >> Personally, I am interested in deep brain stimulation and small >> subcortical structures like the subthalamic nucleus. This structure is not >> visible on T1 (but T2) and is not represented on tissue probability maps at >> all (there is an enhanced TPM including it by Bogdan Draganski available as >> a side-note). In my view, the surface-based world it not at all ready to >> deal with such structures (correct me if I’m wrong). >> > > As I understand it, most of these structures do not have a sheetlike > nature the way cortex does, and thus we probably would not advocate using > surfaces to represent them. > > >> When assessing connectivity from these structures to the rest of the >> brain, it makes it a lot easier to stick to the volume-based approach (and >> not do volume-to-surface projections at all). Moreover, we are often merely >> interested in connectivity to „motor“, „sensory“, „limbic“ and >> „associative“ regions. It could be seen as methodological over engineering >> to implement volume-to-surface based methods for such trivial >> parcellations. So this could maybe illustrate an example where it is – at >> least in my view – still totally fine to use multispectral volumetric >> deformations for connectometric analyses. >> > > I was not intending to say that subcortical structures should be analyzed > on a surface. > > >> Then, the volumetric version I put up on figshare is really for >> comparative reasons with atlases that used different techniques and are >> available in MNI space. >> > > Using group average cortical surfaces (which lack significant folding > definition) to generate it means it won't align well with any subject's > cortex post-registration (because it doesn't align well with the template's > cortex features), which is what I was trying to say (with the comment about > viewing overlaid on the template slices). Thus, this representation of it > will fall short of other volume atlases in terms of cortical overlap with > the volume template. > > >> I guess this is something many people are interested in. For instance, >> the histological atlas by the Jülich group exhibits anatomical detail and >> has been used by the field by coregistering nonlinear warps to it for >> decades – totally accepting the fact that histology was originally based on >> different brains than used to construct the MNI templates. In my view, we’d >> do nothing else with your averaged anatomy atlas if we would compare our >> results to your map. >> > > Per my other comments, this comparison will be compromised when using any > group-average cortical surface to translate any cortical data between > surface and volume (either direction). > > >> We should be aware of likely mismatches in classifications in the same >> way as we have always been using e.g. the SPM anatomy toolbox or >> comparisons to the Harvard Oxford atlas. Still, such a comparison could be >> helpful (in my view). >> >> I hope we may agree on a few points I raised. Of course, if the >> volumetric MMP version bothers you, I’ll gladly put it offline again. >> > > People obviously want a volume representation of it, despite the caveats > of it being hard to faithfully represent as a volume, and I don't know > whether we have reached a decision on whether there is a method of > generating it that we think is a reasonable approximation. I'll defer to > Matt or David on the question of whether it bothers us. > > >> Best, Andreas >> >> >> -- >> Andreas Horn, MD >> Laboratory for Brain Network Imaging and Modulation >> Berenson-Allen Center for Noninvasive Brain Stimulation >> Department for Neurology, Beth Israel Deaconess Center >> Harvard Medical School >> 330 Brooklin Avenue, Kirstein Building KS 158 >> 02215 Boston >> >> t: +1 6174077649 >> w: http://www.brainnetworkstim.com >> <https://urldefense.proofpoint.com/v2/url?u=http-3A__www.brainnetworkstim.com&d=CwMFaQ&c=WknmpdNpvrlj2B5K1aWVqL1SOiF30547pqSuOmtwXTQ&r=BTWOP47EynCdRIxIQsxjKLHVp-ucrpC9iMHv26t1NFM&m=gxnHAaHBn2ma4u-R-Z4YZFC3vjjntoi7ICOm3GGoWN8&s=VUZJHmOG8XwpATQMWNnsUgM8RGIDMbdBlrbWWMsbGgY&e=> >> >> Am 08.08.2016 um 18:18 schrieb Timothy Coalson <[email protected]>: >> >> Thanks for putting a note on that page about how we don't recommend >> volume-based group-average methods. >> >> It should be noted that the similarity between the two representations in >> that figure is due to the use of a group average surface for display, so >> that the surface representation shown is also lacking in folding >> definition. Display of the volume data as a slice overlaid on a T1 volume >> would show this lack of folding more clearly. >> >> However, it looks like the coloring scheme has been changed. Do the left >> and right labels still have different values in your version? >> >> Tim >> >> >> On Mon, Aug 8, 2016 at 1:38 PM, Andreas Horn <[email protected]> >> wrote: >> >>> Hi Andrew, >>> >>> I made a projection here: >>> https://figshare.com/articles/HCP-MMP1_0_projected_on_MNI200 >>> 9a_GM_volumetric_in_NIfTI_format/3501911 >>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__figshare.com_articles_HCP-2DMMP1-5F0-5Fprojected-5Fon-5FMNI2009a-5FGM-5Fvolumetric-5Fin-5FNIfTI-5Fformat_3501911&d=CwMFaQ&c=WknmpdNpvrlj2B5K1aWVqL1SOiF30547pqSuOmtwXTQ&r=BTWOP47EynCdRIxIQsxjKLHVp-ucrpC9iMHv26t1NFM&m=H5xXuSmR3u1QpacRdYn9m0eZGn-PQpp4kLn56KftEvo&s=Lr8aIWvpWl0qlTOgPrMh6zgmoTWlS1uVtjLW48nAtNA&e=> >>> >>> Best, Andy >>> >>> Am 08.08.2016 um 14:34 schrieb David Van Essen <[email protected]>: >>> >>> Hi Andrew, >>> >>> 1) As noted in a previous thread, -cifti-separate should solve this >>> problem. >>> >>> On Jul 20, 2016, at 7:37 PM, Chris Gorgolewski < >>> [email protected]> wrote: >>> Awesome - this did the trick. Thanks! >>> On Wed, Jul 20, 2016 at 5:03 PM, Timothy Coalson <[email protected]> wrote: >>> >>>> Use -cifti-separate with the -label repeatable option to make the left >>>> and right cortex gifti label files. >>>> Tim >>>> >>>>> >>>>> 2) As noted in other recent hap-users threads, mapping the HPC_MMP1.0 >>> surface parcellation via a group average midthickness to a group-average >>> volume pays a steep price in the fidelity of spatial relationships, >>> particularly in regions of high individual variability in folding >>> patterns. We have a paper in press (Nature Neuroscience, appearing Aug 28) >>> that discusses this and related issues and suggests alternative analysis >>> strategies for more faithfully preserving spatial fidelity. >>> >>> David >>> >>> On Aug 8, 2016, at 9:14 AM, Reid, A.T. (Andrew) <[email protected]> >>> wrote: >>> >>> Hi all, >>> >>> For comparison purposes, we want to project the excellent new surface >>> parcellation to a NIFTI volume. We tried to do this in two steps using >>> wb_command: >>> >>> 1. Convert CIFTI to GIFTI: >>> wb_command -cifti-convert -to-gifti-ext Q1-Q6_RelatedParcellation210.L >>> .CorticalAreas_dil_Colors.32k_fs_LR.dlabel.nii glasser_labels.gii >>> >>> 2. Project labels to volume (using the nearest-vertex option): >>> wb_command -label-to-volume-mapping glasser_labels.gii >>> Q1-Q6_RelatedParcellation210.L.midthickness_MSMAll_2_d41_WRN_DeDrift.32k_fs_LR.surf.gii >>> MACM_F1_RostroMiddle_red.nii EssaiMap.nii -nearest-vertex 3 >>> >>> >>> Unfortunately, this gives an error: >>> >>> ERROR: input surface and label file have different number of vertices >>> >>> Most likely because the labels are for both hemispheres, and the surface >>> is only for the left hemisphere. >>> >>> Not sure where to go from here. Is there a command to combine surfaces, >>> or conversely to split the labels? Is there a combined surface file >>> somewhere available? >>> >>> Thanks, >>> >>> Andrew >>> >>> _______________________________ >>> >>> Andrew Reid >>> Postdoctoral Fellow >>> Department of Cognitive Artificial Intelligence >>> Donders Institute for Brain, Cognition and Behaviour >>> Radboud University Nijmegen >>> Web: http://andrew.modelgui.org/ >>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__andrew.modelgui.org_&d=CwMFAg&c=WknmpdNpvrlj2B5K1aWVqL1SOiF30547pqSuOmtwXTQ&r=BTWOP47EynCdRIxIQsxjKLHVp-ucrpC9iMHv26t1NFM&m=y4DiXP3EHKT-ppnuw6sH4JENi0SMn5XcrCnpGj4jVJw&s=xPD2VFCvGeS108si8baJMaVxSi1T7aOzOX8Cd0KJL5s&e=> >>> Tel: +31 (0)24 36 55931 >>> >>> >>> >>> >>> >>> _______________________________________________ >>> HCP-Users mailing list >>> [email protected] >>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.humanconnectome.org_mailman_listinfo_hcp-2Dusers&d=CwMFaQ&c=WknmpdNpvrlj2B5K1aWVqL1SOiF30547pqSuOmtwXTQ&r=BTWOP47EynCdRIxIQsxjKLHVp-ucrpC9iMHv26t1NFM&m=H5xXuSmR3u1QpacRdYn9m0eZGn-PQpp4kLn56KftEvo&s=nXC9IaR3o5CplPnCZdR3k-G-LbrNdeWS67y__YZY5og&e=> >>> >>> >>> _______________________________________________ >>> HCP-Users mailing list >>> [email protected] >>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.humanconnectome.org_mailman_listinfo_hcp-2Dusers&d=CwMFaQ&c=WknmpdNpvrlj2B5K1aWVqL1SOiF30547pqSuOmtwXTQ&r=BTWOP47EynCdRIxIQsxjKLHVp-ucrpC9iMHv26t1NFM&m=H5xXuSmR3u1QpacRdYn9m0eZGn-PQpp4kLn56KftEvo&s=nXC9IaR3o5CplPnCZdR3k-G-LbrNdeWS67y__YZY5og&e=> >>> >>> >>> _______________________________________________ >>> HCP-Users mailing list >>> [email protected] >>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.humanconnectome.org_mailman_listinfo_hcp-2Dusers&d=CwMFaQ&c=WknmpdNpvrlj2B5K1aWVqL1SOiF30547pqSuOmtwXTQ&r=BTWOP47EynCdRIxIQsxjKLHVp-ucrpC9iMHv26t1NFM&m=H5xXuSmR3u1QpacRdYn9m0eZGn-PQpp4kLn56KftEvo&s=nXC9IaR3o5CplPnCZdR3k-G-LbrNdeWS67y__YZY5og&e=> >>> >> >> _______________________________________________ >> HCP-Users mailing list >> [email protected] >> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >> <https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.humanconnectome.org_mailman_listinfo_hcp-2Dusers&d=CwMFaQ&c=WknmpdNpvrlj2B5K1aWVqL1SOiF30547pqSuOmtwXTQ&r=BTWOP47EynCdRIxIQsxjKLHVp-ucrpC9iMHv26t1NFM&m=gxnHAaHBn2ma4u-R-Z4YZFC3vjjntoi7ICOm3GGoWN8&s=wTR7xZ2UMZqFeyrRXQ7gK0A-J9qnPiIvf5cewlJw0GQ&e=> >> >> >> >> ------------------------------ >> >> This message is intended for the use of the person(s) to whom it may be >> addressed. 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