Use nitransforms for LTA-ITK conversions #2041
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oesteban
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May 27, 2020
This is a temporary patch before we go all the way in with NiTransforms in the sampling of BOLD on surfaces. The anatomical _fast-track_ required to expose the fsnative-to-T1w transform in the derivatives folder (which we were already doing in ITK format). When fMRIPrep ran without the fast-track, then the LTA transform would be directly passed in without conversions. The fast-track PR forced the implementation to use the ITK version. This, in conjunction with the little trick to stick the BOLD shape and zooms into the LTA (i.e., using ``lta_concatenate`` with an identity transform with those features, shape and zooms, as moving) resulted in an overly complex workflow that I partially implemented with NiTransforms. This PR gets rid of the concatenation with identity trick, using NiTransforms to generate a transform equivalent to the concatenated LTA we used to generate before the fast-track was introduced. Resolves: nipreps#2145 Assign: @mgxd Milestone: 20.1.0 Related: nipreps#2118, nipreps#2041, nipreps#2121.
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Replacing this: https://github.com/poldracklab/fmriprep/blob/1d93d9e5599d08347ba2b85a4d4590a4c9273814/fmriprep/workflows/bold/registration.py#L456-L463
(will require nipy/nitransforms#64)
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