Before I try that I will try increasing the intensity of the shaded voxels. I already tried running nu_correct, and does improve a little bit. The shading is a gradient (from darken into brighter, I will see if I can find the gradient in the out of brain pixels (like the dark areas of the image) and create a function that models it, and then apply it to the back and front sections of the scan. By brightening those pixels I might be able include the white and gray matter in the segmentation. Has anyone tried something like this before? I understand that there might be a bias, but if I get it to improve the segmentation and specially the ICV, it will be an improvement. 

Gabriel 

On Sun, Mar 18, 2018 at 3:19 PM, Bruce Fischl <fischl@nmr.mgh.harvard.edu> wrote:

Hi Gabriel

you can try adding control points in the white matter in those regions, but typically when there is so much signal loss there is very little anatomical SNR left to build models with.

good luck
Bruce
On Sun, 18 Mar 2018, Gamaliz wrote:

[IMAGE]

On Sun, Mar 18, 2018 at 2:28 AM, Gamaliz <gliza002@fiu.edu> wrote:

Dear Freesurfer Team,

I have about 200 T1 coronal scans that were obtained with some shading in the frontal and
occipital regions. Not sure if it can be seen from the attached picture, but the image fades
toward the top and bottom (on the axial view). The segmentation left out a large section of
the frontal and occipital, probably because the signal loss brings those voxels below the
threshold for white and gray matter.

I have tried to run FSL bias correction and got a small improvement, but I wonder if there is
any way these faded slides can be corrected so that the segmentation is capable of seeing
these as proper white and gray matter.

In the attached picture, the blue is the wm surface and the red is the gray matter (wm and
pial surfaces)

The image shown is actually the T1.mgz from freesufer that has already gone through the
nu_correct step in recon_all, the original image looks very similar...

Thanks

Gabriel

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