Thanks a lot with your help. This is because we want to perform quite a number of functional runs on the same subject at the same session. So we tried to shorten the T1 scan time to minimize the motion artifacts come from the subject.

Attached please find the orig.mgz for your information.

2009/10/8 Bruce Fischl <fischl@nmr.mgh.harvard.edu>
I see. Your TR is quite short and your TE relatively long, so this is probably pretty poor CNR between gray and white. If you send me the orig.mgz I'll take a look and see if it's fixable

On Thu, 8 Oct 2009, Angel Wong wrote:

Hi Bruce

Attached please find the parameters for acquiring the T1 image.

Thank you for your help.

Angel

2009/10/8 Bruce Fischl <fischl@nmr.mgh.harvard.edu>

eek, that looks pretty bad. Can you tell us what the acquisition parameters
are?

On Thu, 8 Oct 2009, Angel Wong wrote:

 Dear all



Actually I would like to perform automated reconstruction for my T1 image
and then obtain anatomical labels after cortical parcellation. I have done
fully automated reconstruction using recon-all. But for my case, the white
and grey matter segmentation appears to be weird. The green line seems
laying on the pial surface rather than on the white surface, and the red
line seems including some non-brain structures (including small portion of
CSF and skull). Thus, the resultant cortical thickness appears to be very
thin after the segmentation. I just doubt if anything was going wrong
during
the procedure. Or need any preprocessing to enhance the segmentation
quality
before performing the reconstruction? If you have had similar situation as
mine, please let me know how to tackle the problem.

Attached please find the images for better illustration.

fs_image_brain.tiff - use brain.mgz as aux volume
fs_image_norm.tiff - use norm.mgz as aux volume
fs_image_brainmask.tiff - use brainmask.mgz as aux volume and load
segmentation file aseg.mgz

Thanks
Angel