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. Using orig is sufficient for an atlas created with MPRAGES, but for other data types (i.e. multi-echo flash) this volume should be choosen more carefully, see example 2. |
-T1 |
input volume (i.e. nu, norm.mgh etc) |
-flash |
specifies the atlas as either single-echo or multi-echo |
-xform |
reference transform |
Outputs
<output file> |
gca file - gaussian class array file, in this instance essentially a probabilistic map |
Description
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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 -input flash30_avg.mgz -input flash5_avg.mgz $SUBJECTS multi_one.gca
Bugs
??
See Also
["mri_em_register"], ["mri_ca_normalize"]
Links
Methods Description
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References
["References/Lastname###"]
Reporting Bugs
Report bugs to <analysis-bugs@nmr.mgh.harvard.edu>