Differences between revisions 5 and 6
Deletions are marked like this. Additions are marked like this.
Line 9: Line 9:
Muller-Gartner Method), region-based voxel-wise (RBV). PVC also
accounts for the volu
me fraction effect. PETSurfer will be released
with FreeSurfer version 6.
Muller-Gartner (MG) Method), region-based voxel-wise (RBV). SGTM is
used for ROI analysis where as the others are used for voxel-wise
analysis. All
PVC implementations also accounts for the volume
fraction effect. PETSurfer will be released with FreeSurfer version
6.
Line 24: Line 26:
{{{
mri_coreg --s subject --mov template.nii.gz --reg template.reg.lta
}}}
where template.nii.gz is the template image for your PET data. If your
PET data only has one frame (eg, an SUV image), then that will be your
template. If your PET data has multiple frames (ie, dynamic), then you
will need to create the template from the dynamic data. This can be
done by extracting a single frame (mri_convert pet.nii.gz --frame
frameno template.nii.gz) or averaging all the time frames together
(eg, mri_concat pet.nii.gz --mean --o template.nii.gz),

PETSurfer provides a set of tools within FreeSurfer for Partical Volume Correction (PVC) and Kinetic Modeling. While these are typically used for PET analysis, the tools can be used in any context where PVC is needed. PVC methods include the Symmetric Geometric Transfer Matrix (SGTM), two-compartment model (also known as the Meltzer Method), three-compartment model (also known as the Muller-Gartner (MG) Method), region-based voxel-wise (RBV). SGTM is used for ROI analysis where as the others are used for voxel-wise analysis. All PVC implementations also accounts for the volume fraction effect. PETSurfer will be released with FreeSurfer version 6.

In all cases, you will need a T1-weighted MRI of your subject of sufficient quality to run in FreeSurfer. FreeSurfer analysis must be done first. After that, follow the steps below.

1. gtmseg --s subject

where "subject" is the name of the FreeSurfer subject when you ran recon-all. This creates several files in the FS folder used to run the PVC methods. This should take about an hour or two.

2. Register your PET image with the anatomical:

mri_coreg --s subject --mov template.nii.gz --reg template.reg.lta

where template.nii.gz is the template image for your PET data. If your PET data only has one frame (eg, an SUV image), then that will be your template. If your PET data has multiple frames (ie, dynamic), then you will need to create the template from the dynamic data. This can be done by extracting a single frame (mri_convert pet.nii.gz --frame frameno template.nii.gz) or averaging all the time frames together (eg, mri_concat pet.nii.gz --mean --o template.nii.gz),

PetSurfer (last edited 2020-07-27 10:45:02 by DougGreve)