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.mgz 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

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