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,
},
);