Hi Donna, Thanks for you extended reply. The plan is to do the following:
Surface-register the individual image to the F99 surface, select one of the existing atlasses on this surface, extend the atlas to a volume-atlas, volume-register to the T2-weighted image, and re-do the fiber-tracking (I do not necessarily need the atlas I have now; I just need white-matter tracts in register with an atlas) Thank again, Rikkert On Fri, Oct 31, 2014 at 4:27 PM, Donna Dierker <[email protected]> wrote: > On Oct 30, 2014, at 11:29 AM, "HINDRIKS, RIKKERT" < > [email protected]> wrote: > > > Dear Donna, > > > > Thanks for your fast response, I appreciate it! > > > > My situation is as follows: > > > > On the one hand, I have a group-averaged T1-weighted image, together > with a volumetric atlas (that is, an integer labeling of the > > voxels) as well as a structural connectivity matrix (obtained via > fiber-tracking on the group-averaged diffusion-weighted image). On > > the other hand, I have a T1-weighted image of an individual monkey. My > aim is to obtain a surface atlas (derived from volumetric atlas) > > for the individual monkey. > > This is an interesting scenario, and I've not encountered it before. > > > Could I first to a volumetric-registration of the individual image to > the group-averaged image and subsequently project the induced > > labeling of the voxels of the individual image to the individual surface? > > This seems reasonable and not too hard. The lower variability in macaque > folding may make it less problematic than for humans. > > > Or do I have to extract the surface of the group-averaged > > image, project the volumetric atlas to it, and subsequently perform a > spherical registration of the individual surface to the group- > > averaged surface? > > People do extract surfaces from group averaged anatomical volumes for some > purposes, but I doubt it will be worth it in this case. I hope others will > voice their opinions if they feel otherwise. > > > The first approach seems more straightforward, but I don't know if it is > correct. Also, a complication with the second approach is that > > the extracted surface from the group-averaged image looks worse than > that extracted from the individual image (it is entirely ok, except > > for that the primary visual cortex has a large part missing at the > medial side). > > This is to be expected. A more reasonable thing to do if you want an > average surface is generate surfaces for the individuals and compute an > average from them. You probably don't have those surfaces, so honestly I'd > try the first option and vet the resulting mapping using the > T1+contour+volumetric-overlay view. > > Still another option would be to use surface based registration to get > your individual monkey in register with the F6 atlas (part 3, > http://brainvis.wustl.edu/wiki_linked_files/documentation/Caret_Tutorial_Sep22.pdf) > or Donald McLaren's population average macaque atlas ( > http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2659879). You could do > something like this: > > * volumetrically warp your atlas goodies to match the mean anatomical > McLaren image. > * surface-based register your individual macaque atlas to the McLaren > standard mesh surface. > * map your warped atlas goodies to the McLaren population surface. > * view your mapped results on your individual's standard mesh surface. > > But that second step isn't trivial, and your easier route might suffice. > So I'd give that a go first. > > > And Donna, could you please tell me how to create a paint file from a > nifty-file? (the atlas I have is saved as a nifti-file) > > In caret5, Attributes: Map Volume to Surface and choose paint. But > getting the color lookup is a bit messy. The newer CIFTI format contains a > label lookup table, and we also have a nifti extension for that, but it's > not understood by other viewers. > > Caret5 has two volume formats that store that color lookup info: AFNI, > using a caret-specific header extension, and wustl's IFH/4dfp. The ifh > header lists the lookup, with an offset of 2. (Like I said: Messy.) I > can point you to some helpful threads on caret-users if needed. > > > The background is that we want to construct a computational model of > cortical dynamics using the structural connectivity information. > > An alternative, I guess, would be to spherically register the individual > surface to the F99 template and subsequently, use the CoCoMAc > > or other available connectivity data. The drawback of this, however, is > that the strength of connections is more or less qualitative, hence > > not so well-suited for modeling. If you think, though, that this is the > best option for the creation of a surface-atlas, then I will go for it. > > See how far you get with the easy option. If not far enough, then it's > possible the McLaren atlas mesh is in register with F99. I can't recall > clearly, but read that link above for more info. > > > Thanks a lot Donna, and kind regards, > > Rikkert > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > On Thu, Oct 30, 2014 at 3:13 PM, Donna Dierker <[email protected]> > wrote: > > On Oct 29, 2014, at 10:56 AM, "HINDRIKS, RIKKERT" < > [email protected]> wrote: > > > > > > > > Dear all, > > > > > > I have an averaged T1-image and co-registered volumetric atlas of the > macaque brain (which has been digitized by a collaborator) and want to > derive from it a surface-based > > > atlas. Subsequently, I would like to use this atlas to get a > parcellation of the cortical surface of an individual macaque brain). How > should I approach this problem? > > > > > > I have extracted the cortical surface from the averaged T1-weigthed > scan. Should I now > > > just label each cortical vertex by determining to which ROI it > belongs? And what if some vertices fall outside all ROI's? Also, the result > does not look so smooth as existing atlases. > > > > It sounds like you need to map the volume(s) onto the surface. It also > sounds like these are discrete parcellations (ROI/label/paint) as opposed > to probabilistic atlases, since it sounds like it is an individual monkey's > data, rather than group data. It would be helpful to clarify this. > > > > Assuming it is ROI/label (i.e., each intensity value -- e.g., 1, 2, 3, … > -- corresponds to a region -- e.g., cingulate, arcuate, …), then I would > map it as a paint volume. I believe doing so constrains the mapping > algorithms, but I am not certain. > > > > If you load your anatomical T1 with your surfaces and toggle on the > surface contours (Volume Surface Outline, on the D/C page selection), then > you can overlay the volumetric atlas over these two anatomical underlays > (T1+surface contours) to look for regions where the surface does not > intersect the atlas. I see three choices: > > > > * fix the volumetric atlas data > > * fix the surfaces, so the intersection is improved > > * accept the fact that there are real holes in your data > > > > You will be better equipped to make that choice when you are looking at > T1+surface contours+volumetric-atlas. > > > > > And to parcellate an individual macaque brain, can I register both the > surfaces (that is, the template surface and the individual surface) > spherically? > > > > Registering an individual monkey brain to a monkey atlas (e.g., F99) > isn't really parcellating it, but there are parcellations already on the > F99 atlas, so if you use spherical registration to register your monkey to > F99, then you could look at the F99 parcellations overlaid on your monkey's > surface. But it's not a quick or easy process. You need to draw > registration borders. (Though there are other registration algorithms out > there that use sulcal maps and/or other data to automatically derive the > deformation. I encourage others to chime in if they ones they have used > and found not too hard.) How would you be using the registered surface? > > > > (Sorry for the delayed reply, but it wasn't a quick one. ;-) > > > > > Thanks a lot, > > > Rikkert > > > > > > > > > _______________________________________________ > > > caret-users mailing list > > > [email protected] > > > http://brainvis.wustl.edu/mailman/listinfo/caret-users > > > > > > _______________________________________________ > > caret-users mailing list > > [email protected] > > http://brainvis.wustl.edu/mailman/listinfo/caret-users > > > > _______________________________________________ > > caret-users mailing list > > [email protected] > > http://brainvis.wustl.edu/mailman/listinfo/caret-users > > > _______________________________________________ > caret-users mailing list > [email protected] > http://brainvis.wustl.edu/mailman/listinfo/caret-users >
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