sa(1)
part of ANTS registration suite
DESCRIPTION
segAdapter: Apply corrections to segmentations produced by the host segmentation method.
Usage:
./sa input_Segmentation AdaBoost_OutPutPrefix output_Segmentation [options]
-
Meanings of the parameters:
input_Segmentation: Segmentation produced by the host segmentation method for the image
AdaBoost_OutPutPrefix: Path and prefix to the AdaBoost files specified in ./bl
output_Segmentation: Path and file name of the output corrected segmentation.
options:
- -f feature1.nii feature2.nii ...
-
Feature images for the target subject.
The name pattern could be in C printf format, e.g. feature%04d.nii
Then feature0000.nii will be used for label 0 and feature0001.nii for label 1, etc.
- -m mask:
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Specify ROI for the training images. Should be in C printf format, e.g. mask%04d.nii
ROI will be derived by performing dilation on this mask.
- -x label image.nii
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Specify an exclusion region for the given label.
If a voxel has non-zero value in an exclusion image,
the corresponding label is not allowed at that voxel.
- -p filenamePattern
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Save the posterior maps (probability that each
voxel belongs to each label) as images. The number of
images saved equals the number of labels. The filename
pattern must be in C printf format, e.g. posterior%04d.nii.gz
- -mrf <method> [parameters]
-
Apply Markov Random Field prior to derive the segmentation.
Options: ICM (Iterated Conditional Modes)
May be followed by optional parameters in brackets, e.g., -mrf ICM[beta,iter].
beta: weight for the MRF prior, must be a non-negative number. Default: 0.1
iter: max iteration for ICM optimization. Default: 10