Differences between revisions 1 and 4 (spanning 3 versions)

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

gca file - gaussian class array file, in this instance essentially a probabilistic map

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

References

[https://surfer.nmr.mgh.harvard.edu/ftp/articles/fischl02-labeling.pdf Whole Brain Segmentation: Automated Labeling of Neuroanatomical Structures in the Human Brain], Fischl et al., (2002). Neuron, 33:341-355.

Reporting Bugs

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

Author/s

BruceFischl

-  ⇤ ← Revision 1 as of 2004-09-13 10:17:12 → 
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+   ← Revision 4 as of 2006-10-06 14:04:59 → ⇥
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  Editor: NickSchmansky
  Comment:
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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.  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 ||
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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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-= Description =
??
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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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+Line 45:
-??

= Bugs =
??
+{{{
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
}}}
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+Line 56:
-["othercommand1"], ["othercommand2"]

= Links =
FreeSurfer

= Methods Description =
{{{
??
}}}
+["mri_em_register"], ["mri_ca_normalize"]
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-["References/Lastname###"]
+  * [https://surfer.nmr.mgh.harvard.edu/ftp/articles/fischl02-labeling.pdf Whole Brain Segmentation: Automated Labeling of Neuroanatomical Structures in the Human Brain], Fischl et al., (2002). Neuron, 33:341-355.