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Anisotropic template resolutions #1037
...aren't fun or anything we'd like to have in our studies. We saw them recently popping up everywhere. The reason is
Just my 2 cents. Happily proceed as you wish... I assigned some random people to get input going. I labelled it "critical" because a lot of people over here have recently used population_template and have the effects of this in their FBA pipeline. If those need to be redone, that's quite a bit of computation time, and also a bit of people-time.
For registration, there is always a tradeoff between potential bias, data size and loss of information due to undersampling. Imagine two input images with identical transformations but different voxel sizes. Currently, the average grid uses the average voxel size of the two input images which should be unbiased but loses information of the higher resolved image. Using the highest resolution would bias it towards one image. One could argue that super-resolving both images is sensible, especially for nonlinear registration but this increases the computational, memory and storage cost and might introduce undesired side effects during registration such as being stuck in local minima if the original voxels were very anisotropic.
I agree, I don't think there is a principled way of defining the "best" grid size so we should provide a sensible default and offer the option to change it. Using the average voxel volume and isotropic voxels is not ideal for anisotropic voxels. If you prefer isotropic voxels, I'd suggest using the smallest voxel edge length which is at or above the Nyquist sampling density depending on the relative orientation of the input images.
For the template, it very much depends on the input data's resolution and on the Jacobian of the warp fields what a sensible default is. I don't have much experience with FBA but for analysis in subject-space, I suspect that since we already suggest to upsample the input data, spatial frequency content beyond that of the original data's is unlikely to contribute meaningful information especially as in template space we're likely limited by the anatomical resolution and variability.
Can you elaborate on the bias you'd expect to see with anisotropic voxels?
Anyway, I'll add an option to
added a commit
Jul 5, 2017
I noticed the issue of anisotropic voxels is not limited to
So I am not sure that fixing
Internally 'mrregister' uses an average space grid with voxel sizes that depend on the original input voxel sizes and the two voxel to scanner transformations. This is done to avoid bias towards any one input image as I've written above.
The voxel size is larger than the input voxel size as the spatial resolution decreases with the rotation of the average space away from the original voxel grid. This, of course, is only a valid argument for linear registration as the resolution also depends on the warp field itself for nonlinear registration.
I think it is sensible to default to write the warp field as it was used for registration as