We have had some suboptimal results from FreeSurfer's skullstripping algorithm, even after iteratively trying different watershed thresholds and after checking the quality of Talairach registration. The results are pretty good, but often leave some dura matter and bits of neck behind whose higher intensity values, I believe, may end up skewing recon-all's later estimation of the range of intensity values within grey matter, and consequently compromising the accuracy of pial surface estimation.

FSL's BET, however, seems to do a better job of extracting the brain, at least for our dataset. So, I was wondering if I might be able to skip over mri_watershed and feed autorecon2 and autorecon3 a brainmask.mgz file created using BET. I tried this procedure:

1) mri_convert <path/to/T1dcm> T1.nii.gz

2) bet T1.nii.gz BET_brainmask.nii.gz -A

3) mri_convert BET_brainmask.nii.gz BET_brainmask.mgz

4) recon-all -s <subjid> -autorecon1 -noskullstrip

5) mv BET_brainmask.nii.gz ./<subjid>/mri/brainmask.mgz

6) recon-all -s <subjid> -autorecon2 -autorecon3

#@# Mask BFS Tue Mar 5 22:52:05 EST 2013

/net/rc-fs-nfs/ifs/data/Shares/DMC-Sheridan2/projects/FOCUS/FreeSurfer/2012_bet/mri

mri_mask -T 5 brain.mgz brainmask.mgz brain.finalsurfs.mgz

threshold mask volume at 5

ERROR: dimension mismatch between source and mask

Linux rc-thunderball 3.2.21-mosix #1 SMP Mon Jul 2 08:55:48 EDT 2012 x86_64 x86_64 x86_64 GNU/Linux

recon-all -s 2012_bet exited with ERRORS at Tue Mar 5 22:52:06 EST 2013

I'm guessing that the dimensions of norm.mgz and aseg.mgz didn't match those of brainmask.mgz, resulting during normalization2 in a mismatch between brain.mgz and brainmask.mgz. Does that seem right, and is there a possible workaround?

Thank you!

Warren

Warren Winter

Research Coordinator

Boston Children's Hospital

Sheridan Laboratory of Cognitive Neuroscience

Division of Developmental Medicine

1 Autumn Street, AU 650

Boston, MA 02215

857-218-5224