For the registration of embryo data, we use slightly different settings for MICe-build-model compared to the registration of brain data. So far we have not been able to determine a workable set of parameters for mincANTS, and so we use minctracc. To allow for larger deformations (embryo data tends to be more dissimilar) a non-linear stage with a larger blurring kernel is added at the start of the non-linear stage, and the stiffness settings for the elastic grid for minctracc are set more loosely.

For input data at a resolution of 15micron, the following is a sample incantation of the MICe-build-model.pl script :

Assumptions:

- the embryo data is either OPT or CT (because we use the -no-nuc option, meaning that we do not do non-uniformity correction caused by the MR)
- the data is already roughly aligned, i.e., they overlap in space and face the same direction. If this is not the case,the -lsq6-identity flag should be changed

> MICe-build-model.pl -pipeline-name some_embryo_pipeline -init-model /some/initial/model/prefix -no-inormalize -no-resample-atlas -no-registration-accuracy -no-nuc -lsq6-initial-step 0.1 -lsq6-identity -no-lsq6-large-rotations -lsq6-kernels 1.0_blur,0.8_blur,0.5_blur -lsq12 -lsq12-initial-step 0.1 -lsq12-kernels 2.0_blur,1.0_blur -lsq12-max-pairs 0 -nlin -nlin-stats -nlin-registration-method minctracc -nlin-protocol embryo_smasher.pl -stiffness 0.5 -similarity 0.5 -weight 0.3 [ input embryo MINC files ]

where the file embryo_smasher.pl contains:

> cat embryo_smasher.pl ( { memory => 4, generation => 1, kernel => 0.6, iterations => 40, simplex => 3, ncpus => 1, use_gradient => 0, optimization => "-use_simplex", step => 0.3, }, { memory => 4, generation => 2, kernel => 0.4, iterations => 40, simplex => 3, ncpus => 1, use_gradient => 0, optimization => "-use_simplex", step => 0.3, }, { memory => 4, generation => 3, kernel => 0.2, iterations => 20, simplex => 3, ncpus => 1, use_gradient => 0, optimization => "-use_simplex", step => 0.2, }, { memory => 4, generation => 4, kernel => 0.15, iterations => 20, simplex => 3, ncpus => 1, use_gradient => 0, optimization => "-use_simplex", step => 0.15, }, { memory => 4, generation => 5, kernel => 0.09, iterations => 10, simplex => 3, ncpus => 1, use_gradient => 0, optimization => "-use_simplex", step => 0.09, }, { memory => 4, generation => 6, kernel => 0.05, iterations => 10, simplex => 3, ncpus => 1, use_gradient => 0, optimization => "-use_simplex", step => 0.05, }, { memory => 4, generation => 7, kernel => 0.03, iterations => 10, simplex => 3, ncpus => 1, use_gradient => 0, optimization => "-use_simplex", step => 0.03, }, );