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ENH: Set ANTS Registraiton parameters based on experimental results
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These values for registration parameters should make the
registration process proceed faster with very nominal
change to the result values.
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@hjmjohnson
hjmjohnson committed Jan 9, 2013
1 parent 7414c49 commit b8f5d4d
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Showing 3 changed files with 25 additions and 23 deletions.
30 changes: 16 additions & 14 deletions AutoWorkup/BAWantsRegistrationBuildTemplate.py
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Expand Up @@ -198,22 +198,24 @@ def BAWantsRegistrationTemplateBuildSingleIterationWF(iterationPhasePrefix=''):
BeginANTS.inputs.dimension = 3
""" This is the recommended set of parameters from the ANTS developers """
BeginANTS.inputs.output_transform_prefix = str(iterationPhasePrefix) + '_tfm'
BeginANTS.inputs.transforms = ["Rigid", "Affine", "SyN"]
BeginANTS.inputs.transform_parameters = [[0.1], [0.1], [0.15, 3.0, 0.0]]
BeginANTS.inputs.metric = ['Mattes', 'Mattes', 'CC']
BeginANTS.inputs.sampling_strategy = ['Regular', 'Regular', None]
BeginANTS.inputs.sampling_percentage = [0.1, 0.1, 1.0]
BeginANTS.inputs.metric_weight = [1.0, 1.0, 1.0]
BeginANTS.inputs.radius_or_number_of_bins = [32, 32, 4]
BeginANTS.inputs.number_of_iterations = [[2000, 2000, 2000], [1000, 1000, 1000], [10000, 500, 500, 200]]
BeginANTS.inputs.convergence_threshold = [5e-7, 5e-7, 5e-7]
BeginANTS.inputs.convergence_window_size = [15, 15, 15]
BeginANTS.inputs.use_histogram_matching = [True, True, True]
BeginANTS.inputs.shrink_factors = [[4, 2, 1], [4, 2, 1], [6, 4, 2, 1]]
BeginANTS.inputs.smoothing_sigmas = [[4, 2, 0], [4, 2, 0], [6, 4, 2, 0]]
BeginANTS.inputs.use_estimate_learning_rate_once = [False, False, False]
BeginANTS.inputs.transforms = ["Rigid", "Similarity", "Affine", "SyN"]
BeginANTS.inputs.transform_parameters = [[0.1], [0.1], [0.1], [0.15, 3.0, 0.0]]
BeginANTS.inputs.metric = ['Mattes', 'Mattes', 'Mattes', 'CC']
BeginANTS.inputs.sampling_strategy = ['Regular', 'Regular', 'Regular', None]
BeginANTS.inputs.sampling_percentage = [1.0, 1.0, 1.0, 1.0]
BeginANTS.inputs.metric_weight = [1.0, 1.0, 1.0, 1.0]
BeginANTS.inputs.radius_or_number_of_bins = [32, 32, 32, 4]
BeginANTS.inputs.convergence_threshold = [5e-7, 5e-7, 5e-7, 5e-7]
BeginANTS.inputs.convergence_window_size = [25, 25, 25, 25]
BeginANTS.inputs.use_histogram_matching = [True, True, True, True]
BeginANTS.inputs.number_of_iterations = [[2000, 2000], [2000, 2000], [1000, 1000, 100], [10000, 500, 500, 200]]
BeginANTS.inputs.smoothing_sigmas = [[4, 2], [5, 2], [4, 2, 1], [5, 4, 2, 0]]
BeginANTS.inputs.shrink_factors = [[4, 2], [5, 2], [4, 2, 1], [5, 4, 2, 1]]
BeginANTS.inputs.use_estimate_learning_rate_once = [False, False, False, False]
BeginANTS.inputs.write_composite_transform = True
BeginANTS.inputs.collapse_output_transforms = True
BeginANTS.inputs.winsorize_lower_quantile = 0.025
BeginANTS.inputs.winsorize_upper_quantile = 0.975
BeginANTS.inputs.output_warped_image = 'atlas2subject.nii.gz'
BeginANTS.inputs.output_inverse_warped_image = 'subject2atlas.nii.gz'

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8 changes: 4 additions & 4 deletions AutoWorkup/WorkupT1T2.py
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Expand Up @@ -693,15 +693,15 @@ def WorkupT1T2(subjectid, mountPrefix, ExperimentBaseDirectoryCache, ExperimentB
AtlasToSubjectantsRegistration[sessionid].inputs.transform_parameters = [[0.1], [0.15, 3.0, 0.0]]
AtlasToSubjectantsRegistration[sessionid].inputs.metric = ['Mattes', 'CC']
AtlasToSubjectantsRegistration[sessionid].inputs.sampling_strategy = ['Regular', None]
AtlasToSubjectantsRegistration[sessionid].inputs.sampling_percentage = [0.1, 1.0]
AtlasToSubjectantsRegistration[sessionid].inputs.sampling_percentage = [1.0, 1.0]
AtlasToSubjectantsRegistration[sessionid].inputs.metric_weight = [1.0, 1.0]
AtlasToSubjectantsRegistration[sessionid].inputs.radius_or_number_of_bins = [32, 4]
AtlasToSubjectantsRegistration[sessionid].inputs.number_of_iterations = [[1000, 1000, 1000], [10000, 500, 500, 200]]
AtlasToSubjectantsRegistration[sessionid].inputs.convergence_threshold = [5e-7, 5e-7]
AtlasToSubjectantsRegistration[sessionid].inputs.convergence_window_size = [15, 15]
AtlasToSubjectantsRegistration[sessionid].inputs.convergence_window_size = [25, 25]
AtlasToSubjectantsRegistration[sessionid].inputs.use_histogram_matching = [True, True]
AtlasToSubjectantsRegistration[sessionid].inputs.shrink_factors = [[4, 2, 1], [6, 4, 2, 1]]
AtlasToSubjectantsRegistration[sessionid].inputs.smoothing_sigmas = [[4, 2, 0], [6, 4, 2, 0]]
AtlasToSubjectantsRegistration[sessionid].inputs.shrink_factors = [[4, 2, 1], [5, 4, 2, 1]]
AtlasToSubjectantsRegistration[sessionid].inputs.smoothing_sigmas = [[4, 2, 0], [5, 4, 2, 0]]
AtlasToSubjectantsRegistration[sessionid].inputs.use_estimate_learning_rate_once = [False, False]
AtlasToSubjectantsRegistration[sessionid].inputs.write_composite_transform = True
AtlasToSubjectantsRegistration[sessionid].inputs.collapse_output_transforms = True
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10 changes: 5 additions & 5 deletions BRAINSCommonLib/BRAINSFitSyN.h
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Original file line number Diff line number Diff line change
Expand Up @@ -17,8 +17,8 @@ simpleSynReg( typename FixedImageType::Pointer & infixedImage,

typename SyNRegistrationHelperType::Pointer regHelper = SyNRegistrationHelperType::New();
{
const float lowerQuantile = 0.0;
const float upperQuantile = 1.0;
const float lowerQuantile = 0.025;
const float upperQuantile = 0.975;
const bool doWinsorize(false);
regHelper->SetWinsorizeImageIntensities(doWinsorize, lowerQuantile, upperQuantile);
}
Expand Down Expand Up @@ -48,7 +48,7 @@ simpleSynReg( typename FixedImageType::Pointer & infixedImage,
}
{
std::vector<unsigned int> convergenceWindowSizeList;
const unsigned int convergenceWindowSize = 15;
const unsigned int convergenceWindowSize = 25;
convergenceWindowSizeList.push_back(convergenceWindowSize);
regHelper->SetConvergenceWindowSizes( convergenceWindowSizeList );
}
Expand All @@ -57,7 +57,7 @@ simpleSynReg( typename FixedImageType::Pointer & infixedImage,
// --shrink-factors 3x2x1
std::vector<std::vector<unsigned int> > shrinkFactorsList;
std::vector<unsigned int> factors(4);
factors[0] = 6;
factors[0] = 5;
factors[1] = 4;
factors[2] = 2;
factors[3] = 1;
Expand All @@ -68,7 +68,7 @@ simpleSynReg( typename FixedImageType::Pointer & infixedImage,
// --smoothing-sigmas 3x2x0
std::vector<std::vector<float> > smoothingSigmasList;
std::vector<float> sigmas(4);
sigmas[0] = 6;
sigmas[0] = 5;
sigmas[1] = 4;
sigmas[2] = 2;
sigmas[3] = 0;
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