minc_nuyl
Intensity normalization using piece-wise linear histogram matching.
minc_nuyl [options] <source.mnc> <target.mnc> [output]
DESCRIPTION
minc_nuyl performs intensity normalization of a source MINC volume to match the intensity histogram of a target volume using the piece-wise linear histogram standardization method. The method is based on Nyul, Udupa, and Zhang (2000), “New Variants of a Method of MRI Scale Standardization” (IEEE Transactions on Medical Imaging, 19(2):143-150).
The tool can also create a standardized histogram model from a single volume using the --chist option, and apply normalization using a look-up table.
OPTIONS
--source-maskmask- Apply a mask to the source volume for histogram computation.
--target-maskmask- Apply a mask to the target volume for histogram computation.
--linear- Use global linear normalization instead of piece-wise linear mapping.
--stepsn- Set the number of histogram matching steps (landmarks). Default: 10.
--fix_zero_padding- Handle zero-padded regions in the input volumes.
--verbose- Print progress information during processing.
--ks- Report the Kolmogorov-Smirnov statistic between the normalized and target histograms.
--chist- Create a standardized histogram file from the source volume instead of normalizing. In this mode, the second argument is the output histogram filename.
--dumplut- Write the intensity mapping look-up table to the specified file.
--cut-offpct- Set the percentile cut-off for histogram matching.
EXAMPLES
Normalize source to match target intensity:
minc_nuyl source.mnc target.mnc normalized.mnc
Normalize with brain masks:
minc_nuyl --source-mask src_mask.mnc --target-mask tgt_mask.mnc \
source.mnc target.mnc normalized.mnc
Create a standardized histogram:
minc_nuyl source.mnc model.hist --chist
Normalize with linear mapping:
minc_nuyl --linear source.mnc target.mnc normalized.mnc
AUTHOR
Vladimir S. Fonov - McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University.
COPYRIGHTS
Copyright © 2011 by Vladimir S. Fonov