NAME

mri_ca_normalize

SYNOPSIS

mri_ca_normalize [<options>] <inbrain1> <inbrain2> ... <atlas> <xform> <output1> <output2> ...

DESCRIPTION

This program creates a normalized volume using the brain volume and an input gca file.

POSITIONAL ARGUMENTS

ArgumentExplanation
inbrain1input volume
inbrain2input volume
atlasatlas file in gca format
xformtranform file in lta format
output1output volume
output2output volume

REQUIRED-FLAGGED ARGUMENTS

None

OPTIONAL-FLAGGED ARGUMENTS

ArgumentExplanation
-seg <filename>aseg file, to help normalization
-sigma <bias sigma>smoothing sigma for bias field if control points specified (def=4)
-fsamples <filename>write control points to filename
-nsamples <filename>write transformed normalization control points to filename
-mask <mri_vol>use mri_vol to mask input
-f <filename>define control points from filename
-fonly <filename>only use control points from filename
-diag <filename>write to log file
-debug_voxel <x> <y> <z>debug voxel
-debug_node <x> <y> <z>debug node
-tr <float n>set TR in msec
-te <float n>set TE in msec
-alpha <float n>set alpha in radians
-example <mri_vol> <segmentation>use T1 (mri_vol) and segmentation as example
-novardo not use variance estimates
-renorm <mri_vol>renormalize using predicted intensity values in mri_vol
-flashuse FLASH forward model to predict intensity values
-prior <float t>use prior threshold t (default=.6)
-wwrite normalized volume each nregion iteration to norm(n).mgh(see -n)
-n <int n>use n regions/struct for normalization
-v <int n>used for debugging and diagnostics
-p <float p>use top p percent(default=.25) white matter points as control points

OUTPUTS

OutputExplanation
outvoloutput volume in either mgh or mgz format

EXAMPLE 1

mri_ca_normalize -mask -p 0.25 subject1/mri/brain subject1/mri/nu single_one.gca subject1/mri/transforms/talairach_one.lta subject1/mri/norm_one.mgh

BUGS

None

REPORTING

Report bugs to <freesurfer@nmr.mgh.harvard.edu>

SEE-ALSO

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