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, -nbrs, -f, -v, -w, -r, --help, --version
<subject>	subject id
<hemi>	hemisphere: rh or lh
<canonsurf>	canonical surface file
<classifier>	specify classifier array input file
<outputfile>	annotated surface output file

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)
-long	refines the initial labeling read-in from -r (default: disabled)
-r <filename>	file containing precomputed parcellation
-novar	sets all covariance matrices to the identify (default: disabled)
-nbrs <number>	neighborhood size (default=2)
-f <number>	applies mode filter <number> times before writing output (default=10)
-t <filename>	specify parcellation table input file (default: none)
-v <number>	diagnostic level (default=0)
-w <number> <filename>	writes-out snapshots of gibbs process every <number> iterations to <filename> (default=disabled)
--help	print help info
--version	print version info

Outputs

outputfile:

labeled cortical surface model

Example

mris_ca_label \
 -orig white \
 -novar \
 -t $SUBJECTS_DIR/scripts/colortable_final.txt \
 my_subject \
 lh \
 sphere.reg \
 $SUBJECTS_DIR/average/lh.rahul.gcs \
 $SUBJECTS_DIR/my_subject/label/lh.raparc.annot

In this example, mris_ca_label take sphere.reg as the canonical surface input file, lh.rahul.gcs as the classifier array input file, and writes the annotated surface info to lh.raparc.annot. The file colortable_final.txt is embedded into the output file, so that tksurfer (and other utilities) can read it in.

Bugs

none

Links

CorticalParcellation, FreeSurfer, FsFast

References

[https://surfer.nmr.mgh.harvard.edu/ftp/articles/fischl04-parcellation.pdf Automatically Parcellating the Human Cerebral Cortex], Fischl et al., (2004). Cerebral Cortex, 14:11-22.

Reporting Bugs

Report bugs to <analysis-bugs@nmr.mgh.harvard.edu>

Author/s

BruceFischl

-  ⇤ ← Revision 4 as of 2005-11-18 22:19:04 → 
  Size: 2293
  Editor: NickSchmansky
  Comment:
+   ← Revision 10 as of 2005-12-05 20:20:06 → ⇥
  Size: 2889
  Editor: NickSchmansky
  Comment: removed -? option
-Deletions are marked like this.
+Additions are marked like this.
 Line 1:
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-'''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).
+'''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"]).
-Line 15:
+Line 14:
-|| [options] || -sdir, -orig, -long, -novar, -norm, -sulc, -nbrs, -f, -v, -w, -r, -?, -u, --help, --version ||
+|| [options] || -sdir, -orig, -long, -novar, -nbrs, -f, -v, -w, -r, --help, --version ||
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+Line 19:
-|| <outputfile> || outputfile ||
+|| <outputfile> || annotated surface output file ||
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+Line 27:
-|| -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) ||
+|| -long || refines the initial labeling read-in from -r (default: disabled) ||
|| -r <filename> || file containing precomputed parcellation ||
|| -novar || sets all covariance matrices to the identify (default: disabled) ||
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+Line 31:
-|| -a <number> || number of averages (default=5) ||
+|| -f <number> || applies mode filter <number> times before writing output (default=10) ||
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+Line 34:
-|| -n <number> || number of inputs (default=1) ||
|| -? || print usage info ||
|| -u || same as -? ||
+|| -w <number> <filename> || writes-out snapshots of gibbs process every <number> iterations to <filename> (default=disabled) ||
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-||outputfile||
+|| outputfile: || labeled cortical surface model ||
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+Line 41:
-= Description =
??

= Examples =
== Example 1 ==
??

== Example 2 ==
??
+= Example =
{{{
mris_ca_label \
 -orig white \
 -novar \
 -t $SUBJECTS_DIR/scripts/colortable_final.txt \
 my_subject \
 lh \
 sphere.reg \
 $SUBJECTS_DIR/average/lh.rahul.gcs \
 $SUBJECTS_DIR/my_subject/label/lh.raparc.annot 
}}}
In this example, mris_ca_label take sphere.reg as the canonical surface input file, lh.rahul.gcs as the classifier array input file, and writes the annotated surface info to lh.raparc.annot.  The file colortable_final.txt is embedded into the output file, so that tksurfer (and other utilities) can read it in.
-Line 60:
+Line 59:
-??
+["mris_sample_parc"], ["mris_ca_train"]
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+Line 62:
-FreeSurfer, FsFast

= Methods Description =
??
+CorticalParcellation, FreeSurfer, FsFast
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+Line 65:
+[https://surfer.nmr.mgh.harvard.edu/ftp/articles/fischl04-parcellation.pdf Automatically Parcellating the Human Cerebral Cortex], Fischl et al., (2004). Cerebral Cortex, 14:11-22.