Deletions are marked like this. | Additions are marked like this. |
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mri_ca_train - ?? | mri_ca_train - create a GCA from MNI and xfm files |
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mri_ca_train [options] <subject 1> <subject 2> ... <output file> | mri_ca_train [options] <subject 1> <subject 2> ... <output gca fname> |
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none | || -parc_dir || segmentation directory (path relative to $subject/mri|| |
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|| -spacing ||spacing of classifiers in canonical space|| || -gradient ||use intensity gradient as input to classifier|| |
|| -spacing ||spacing of classifiers in canonical space|| || -gradient ||use intensity gradient as input to classifier|| || -mask volname ||use volname as a mask || || -node_spacing ||spacing of classifiers in canonical space i.e. memory you devote to intensity distribution|| || -prior_spacing ||spacing of class priors in canonical space i.e. memory you devote to prior probabity distributions|| || -input name || specifying training data (path relative to $subject/mri). can specify multiple inputs. If not specified, "orig" is used|| || -T1 || input volume (i.e. nu, norm.mgh etc || || -xform || reference transform || |
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|| <output file> || output file || | || <output file> || gca file - gaussian class array file, in this instance essentially a probabilistic map || |
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?? |
mri_ca_train -prior_spacing 2 -node_spacing 8 -mask brain -parc_dir esegatlast -xform manual_registration.xfm -T1 nu subject1 single_one.gca |
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?? | mri_ca_train -node_spacing 4 -prior_spacing 2 -parc_dir esegatlast -xform talairach_one.m3d -T1 norm_one.mgh $SUBJECTS multi_one.gca |
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["othercommand1"], ["othercommand2"] | ["mri_em_register"], ["mri_ca_normalize"] |
Index TableOfContents
Name
mri_ca_train - create a GCA from MNI and xfm files
Synopsis
mri_ca_train [options] <subject 1> <subject 2> ... <output gca fname>
Arguments
Positional Arguments
<subject 1> |
subject 1 |
<subject 2> |
subject 2 |
<output file> |
output file |
Required Flagged Arguments
-parc_dir |
segmentation directory (path relative to $subject/mri |
Optional Flagged Arguments
-spacing |
spacing of classifiers in canonical space |
-gradient |
use intensity gradient as input to classifier |
-mask volname |
use volname as a mask |
-node_spacing |
spacing of classifiers in canonical space i.e. memory you devote to intensity distribution |
-prior_spacing |
spacing of class priors in canonical space i.e. memory you devote to prior probabity distributions |
-input name |
specifying training data (path relative to $subject/mri). can specify multiple inputs. If not specified, "orig" is used |
-T1 |
input volume (i.e. nu, norm.mgh etc |
-xform |
reference transform |
Outputs
<output file> |
gca file - gaussian class array file, in this instance essentially a probabilistic map |
Description
??
Examples
Example 1
mri_ca_train -prior_spacing 2 -node_spacing 8 -mask brain -parc_dir esegatlast -xform manual_registration.xfm -T1 nu subject1 single_one.gca
Example 2
mri_ca_train -node_spacing 4 -prior_spacing 2 -parc_dir esegatlast -xform talairach_one.m3d -T1 norm_one.mgh $SUBJECTS multi_one.gca
Bugs
??
See Also
["mri_em_register"], ["mri_ca_normalize"]
Links
Methods Description
??
References
["References/Lastname###"]
Reporting Bugs
Report bugs to <analysis-bugs@nmr.mgh.harvard.edu>