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Name
mris_ca_label - Automatically assigns a neuroanatomical label to each location on a cortical surface model. This procedure incorporates both geometric information derived from the cortical model (sulcus and curvature), and neuroanatomical convention, as found in a training set (see mris_ca_train).
Synopsis
mris_ca_label [options] <subject> <hemi> <canonsurf> <classifier> <outputfile>
Arguments
Positional Arguments
[options] |
-sdir, -orig, -long, -novar, -norm, -sulc, -nbrs, -f, -v, -w, -r, -?, -u, --help, --version |
<subject> |
subject id |
<hemi> |
hemisphere: rh or lh |
<canonsurf> |
canonical surface file |
<classifier> |
specify classifier array input file |
<outputfile> |
outputfile |
Required Flagged Arguments
subject hemi canonsurf classifier outputfile
Optional Flagged Arguments
-sdir <subject dir> |
specify a subjects directory (default=$SUBJECTS_DIR) |
-orig <filename> |
specify filename of original surface (default=smoothwm) |
-norm1 |
GCSA normalize input #1 after reading (default: disabled) |
-norm2 |
GCSA normalize input #2 after reading (default: disabled) |
-norm3 |
GCSA normalize input #3 after reading (default: disabled) |
-ic <number_priors> <number_classifiers> |
parameters passed to the classifier routine (default: -ic 7 4) |
-sulc |
specify sulc as only input (default: sulcus and curvature) |
-nbrs <number> |
neighborhood size (default=2) |
-a <number> |
number of averages (default=5) |
-t <filename> |
specify parcellation table input file (default: none) |
-v <number> |
diagnostic level (default=0) |
-n <number> |
number of inputs (default=1) |
-? |
print usage info |
-u |
same as -? |
--help |
print help info |
--version |
print version info |
Outputs
outputfile |
Description
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Examples
Example 1
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Example 2
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Bugs
none
See Also
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Links
Methods Description
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References
Reporting Bugs
Report bugs to <analysis-bugs@nmr.mgh.harvard.edu>