Difference between revisions of "Cortical Thickness"

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Page describing how we analyze cortical thickness with freesurfer
 
Page describing how we analyze cortical thickness with freesurfer
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==Setting up Freesurfer and MATLAB==
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First make sure that you have the correct lines in your .bashrc file to run freesurfer:
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export FREESURFER_HOME=/usr/local/freesurfer
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source $FREESURFER_HOME/SetUpFreeSurfer.sh > /dev/null
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export SUBJECTS_DIR=/mnt/diskArray/projects/freesurfer
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Next make sure that you have the right tool boxes in your matlab search path. This should be done through your startup.m file
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addpath(genpath('~/git/yeatmanlab'));
  
 
==Create a T1 weighted nifti image for the subject==
 
==Create a T1 weighted nifti image for the subject==
 
Step 1: In a terminal, convert the PAR/REC files to nifti images. You may not need to do this if you have already gone through the [[Anatomy_Pipeline|Anatomy Pipeline]]
 
Step 1: In a terminal, convert the PAR/REC files to nifti images. You may not need to do this if you have already gone through the [[Anatomy_Pipeline|Anatomy Pipeline]]
  cd /home/projects/MRI/[subid]
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  cd /mnt/diskArray/projects/MRI/[subid]
 
  parrec2nii -c -b *.PAR
 
  parrec2nii -c -b *.PAR
 
Step 2: In MATLAB compute the root mean squared (RMS) image. Once again this might have already been done in the [[Anatomy_Pipeline|Anatomy Pipeline]] so you can re-use that RMS image
 
Step 2: In MATLAB compute the root mean squared (RMS) image. Once again this might have already been done in the [[Anatomy_Pipeline|Anatomy Pipeline]] so you can re-use that RMS image
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==Freesurfer Segmentation==
 
==Freesurfer Segmentation==
 
Freesurfer is a useful tool for segmenting a T1-weighted image and building a cortical mesh. To segment the subject's T1-weighted image using freesurfer from the command line type:
 
Freesurfer is a useful tool for segmenting a T1-weighted image and building a cortical mesh. To segment the subject's T1-weighted image using freesurfer from the command line type:
  recon-all -i /home/projects/anatomy/[subid]/t1_acpc_.nii.gz -subjid [subid] -all
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  recon-all -i /home/projects/MRI/[subjid]/[YYYYMMDD]/[subjid]_WIP_MEMP_VBM_SENSE_13_1_MSE.nii.gz -subjid [subid] -all
We will follow the steps outlined in the [https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/LongitudinalTutorial Freesurfer Wiki] for analyzing cortical thickness
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We will follow the steps outlined in the [https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/LongitudinalTutorial Freesurfer Wiki] for analyzing cortical thickness. The first steps are described [https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalProcessing here]

Latest revision as of 21:15, 3 December 2015

Page describing how we analyze cortical thickness with freesurfer

Setting up Freesurfer and MATLAB

First make sure that you have the correct lines in your .bashrc file to run freesurfer:

export FREESURFER_HOME=/usr/local/freesurfer
source $FREESURFER_HOME/SetUpFreeSurfer.sh > /dev/null
export SUBJECTS_DIR=/mnt/diskArray/projects/freesurfer

Next make sure that you have the right tool boxes in your matlab search path. This should be done through your startup.m file

addpath(genpath('~/git/yeatmanlab'));

Create a T1 weighted nifti image for the subject

Step 1: In a terminal, convert the PAR/REC files to nifti images. You may not need to do this if you have already gone through the Anatomy Pipeline

cd /mnt/diskArray/projects/MRI/[subid]
parrec2nii -c -b *.PAR

Step 2: In MATLAB compute the root mean squared (RMS) image. Once again this might have already been done in the Anatomy Pipeline so you can re-use that RMS image

T1path = 'Path to t1 weighted image';
T1path = mri_rms(T1path); % Root mean squared image

Freesurfer Segmentation

Freesurfer is a useful tool for segmenting a T1-weighted image and building a cortical mesh. To segment the subject's T1-weighted image using freesurfer from the command line type:

recon-all -i /home/projects/MRI/[subjid]/[YYYYMMDD]/[subjid]_WIP_MEMP_VBM_SENSE_13_1_MSE.nii.gz -subjid [subid] -all

We will follow the steps outlined in the Freesurfer Wiki for analyzing cortical thickness. The first steps are described here