Ah, I see those now, under recon-all expert preferences. No, I haven't tried those, I suppose I was following a bad lead with the mri_ca_normalize script. Thanks for the quick answer; I'll experiment with these for now.
-Victor
-----Original Message----- From: Bruce Fischl [mailto:fischl@nmr.mgh.harvard.edu] Sent: Monday, October 20, 2008 2:30 PM To: Laluz, Victor Cc: freesurfer@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] Recurring issue with poor gray/white distinction - easy fix?
Hi Victor,
have you tried messing with the segmentation parameters to mri_segment and mris_make_surfaces? They are written to be quite general across a bunch of T1-weighted acquistion types, but if you know the exact sequence and hence the gm/wm intensity values, you can set them explicitly using e.g.
-wlo, -whi, etc... (and min_gray_at_white_border etc... to mris_make_surfaces)
cheers, Bruce
On Mon, 20 Oct 2008, Laluz, Victor wrote:
Hello everyone,
I have many scans taken just under 10 years ago on a 1.5T Siemens scanner. For some reason, the images from this time period have consistent problems with gray matter / white matter contrast; consistently, Freesurfer measures almost all cerebral brain tissue as being white. I have experimented with mri_ca_normalize (turning -p
down
to 0.25 or so helps), with mri_normalize (using -prune helped
somewhat,)
but all of these trials are experimental and I haven't gotten a solid script written that handles these special cases for me in an efficient way.
My question: has anyone else dealt with this problem regularly, and
come
up with a good way to either use recon-all to take care of it (I can't find any useful flags, or workflow tutorials for dealing with this on the wiki) or written a handy script to do recon-all with several of these "less wm" options built in? I have seen people ask about issues relating to mri_ca_normalize on the mailing list in the past, but the conversations usually end with "send us some of your data and we'll
take
a look at it."
Or, am I missing something here? Did someone already discuss this in detail? Sorry if this seems obvious. Thanks in advance for any help...
Victor Laluz
UCSF Memory and Aging Center