Deletions are marked like this. | Additions are marked like this. |
Line 56: | Line 56: |
== Example 2 == {{{ mri_normalize -noskull -aseg aseg.mgz -mask brainmask.mgz norm.mgz brain.mgz }}} |
|
Line 73: | Line 76: |
[[References/Lastname###]] | "Cortical Surface-Based Analysis I: Segmentation and Surface Reconstruction", Dale, A.M., Fischl, B., Sereno, M.I. (1999) NeuroImage 9(2):179-194 |
Index
Contents
Name
mri_normalize - converts orig or nu volume into normalized white matter volume
Synopsis
mri_normalize <input directory> <output directory>
Arguments
Positional Arguments
<input directory> |
input directory |
<output directory> |
output directory |
Required Flagged Arguments
none
Optional Flagged Arguments
-no1d |
disable 1d normalization |
-conform |
interpolate and embed volume to be 256^3 |
-gentle |
perform kinder gentler normalization |
-f <path to file> |
use control points file (usually control.dat) |
-w <mri_vol c> <mri_vol b> |
write ctrl point(c) and bias field(b) volumes |
-a <float a> |
use control point with intensity a above target (default=25.0) |
-b <float b> |
use control point with intensity b below target (default=10.0) |
-g <float g> |
use max intensity/mm gradient g (default=1.000) |
-v |
verbose |
-n <int n> |
use n 3d normalization iterations (default=2) |
-u |
print usage |
-prune <boolean> |
turn pruning of control points on/off (default=off). Useful if white is expanding into gm |
Outputs
wm |
wm volume of the cortical reconstruction is used as the input for mri_fill |
Description
mri_normalize converts orig or nu volume from cortical reconstruction as input into a new volume where white matter image values all range around 110
Examples
Example 1
mri_normalize SUBJECT/mri/nu SUBJECT/mri/wm
Uses the nu volume (nonuniformity corrected volume), and creates the wm volume, with white matter voxels around 110 image value
Example 2
mri_normalize -noskull -aseg aseg.mgz -mask brainmask.mgz norm.mgz brain.mgz
Bugs
None
See Also
Links
Methods Description
description description
References
"Cortical Surface-Based Analysis I: Segmentation and Surface Reconstruction", Dale, A.M., Fischl, B., Sereno, M.I. (1999) NeuroImage 9(2):179-194
Reporting Bugs
Report bugs to <analysis-bugs@nmr.mgh.harvard.edu>