Hey Freesurfers,
Couple question about 2 FS commands: first is mri_normalize, a command used in -autorecon2 pipeline.
1) Can someone tell me exactly what flags to pass this command in order for it to be as aggressive as possible in bumping up intensities, in an attempt to end up with more expanded grey/white and pial surfaces? (I'm currently losing lateral cortex in surfaces, even with extensive manual control points.)
Here's a link to the command info: http://surfer.nmr.mgh.harvard.edu/fswiki/mri_normalize
Next question is about mri_ca_normalize, another command used in -autorecon2:
2) From what I gather, the way to ensure that mri_ca_normalize is being as aggressive as possible in declaring white matter is by setting the flag -p to 1.0 - Is that right? Are there any other options that could help in this regard?
Link: http://surfer.nmr.mgh.harvard.edu/fswiki/mri_ca_normalize
My issue is sagittally-acquired data with bad inhomogeneity - namely cortical grey matter is far lateral cortex that is not as intense as it needs to be. Normalization needs to be bumping up the intensity in these regions and instead it's still lowering the intensity, resulting in loss of cortex in pial surface. Adding control points to ensure white/grey boundary is correct tends to expand the pial surface when segmentation doesn't get enough WM, which helps me, but it's not enough. Thus I want to ensure I am maximizing the potential for WM (and indirectly, pial) surface size through these normalization commands.
I'm also looking at the mri_nu_correct.mni command which was taken from MNI - haven't had much luck there but I've been messing with the iteration number (and trying removing it completely).
Thanks in advance!
Hi John,
do you want to send us a sample dataset so we can take a look?
Bruce
On Mon, 13 Oct 2008, John Sheppard wrote:
Hey Freesurfers,
Couple question about 2 FS commands: first is mri_normalize, a command used in -autorecon2 pipeline.
- Can someone tell me exactly what flags to pass this command in order for
it to be as aggressive as possible in bumping up intensities, in an attempt to end up with more expanded grey/white and pial surfaces? (I'm currently losing lateral cortex in surfaces, even with extensive manual control points.)
Here's a link to the command info: http://surfer.nmr.mgh.harvard.edu/fswiki/mri_normalize
Next question is about mri_ca_normalize, another command used in -autorecon2:
- From what I gather, the way to ensure that mri_ca_normalize is being as
aggressive as possible in declaring white matter is by setting the flag -p to 1.0 - Is that right? Are there any other options that could help in this regard?
Link: http://surfer.nmr.mgh.harvard.edu/fswiki/mri_ca_normalize
My issue is sagittally-acquired data with bad inhomogeneity - namely cortical grey matter is far lateral cortex that is not as intense as it needs to be. Normalization needs to be bumping up the intensity in these regions and instead it's still lowering the intensity, resulting in loss of cortex in pial surface. Adding control points to ensure white/grey boundary is correct tends to expand the pial surface when segmentation doesn't get enough WM, which helps me, but it's not enough. Thus I want to ensure I am maximizing the potential for WM (and indirectly, pial) surface size through these normalization commands.
I'm also looking at the mri_nu_correct.mni command which was taken from MNI
- haven't had much luck there but I've been messing with the iteration
number (and trying removing it completely).
Thanks in advance!
freesurfer@nmr.mgh.harvard.edu