Hi Eugenio, Would it also be possible to use the -hires flag in the initial recon-all command to prevent the T1 from being downsampled and maintain the voxel size that the T1 was acquired at, and use that resulting recon for the hippocampal subfield segmentation? I've tested this with MEMPRAGE scans acquired at 0.75mm isotropic and coronal T2 anisotropic scans acquired at 0.33mm in plane with 1mm thick slices, and the results look reasonable. The "1mm" label files are correctly downsampled to 0.75mm instead of 1mm, and the higher resolution label files remain at 0.33mm resolution.
Thanks, Matt
Stufflebeam Lab Athinoula A. Martinos Center Massachusetts General Hospital 149 13th Street, Room 1115S Charlestown, MA 02129 ________________________________ From: freesurfer-bounces@nmr.mgh.harvard.edu [freesurfer-bounces@nmr.mgh.harvard.edu] on behalf of Iglesias, Eugenio [e.iglesias@ucl.ac.uk] Sent: Thursday, June 09, 2016 2:36 PM To: Freesurfer support list Subject: Re: [Freesurfer] Hippocampal subfields segmentation - what is the voxel size of the input?
Hi Fernando,
Unfortunately, FreeSurfer does downsample the T1s to 1mm, and the subfield code assumes that the T1 comes from FreeSurfer… For the paper, I hacked the code to take advantage of multiple images with higher resolution, but it hasn’t been thoroughly tested and it’s not publicly available at this point. That said, there are different things you can do at this point: 1. Use the T1+T2 as is (disadvantage: T1 will be resampled to 1 mm). 2. Use only the T2. 3. Use only the T1. To do this, you would use the T1 as additional scan on its own (i.e., the main and additional scans are the same, but the additional one won’t be resampled). 4. There might be a way (hack) of using both scans at full resolution. If you change the header of the T1 scan and specify that the voxel size is 1mm, no resampling will happen; FreeSurfer will believe that you’re dealing with a subject with a very large head. If you do this, you’ll also have to enlarge the voxel size of the T2 by a factor 1/0.7. Also, the resulting volumes will have to be divided by (1/0.7)^3 in order to correct for the “wrong” voxel size.
I hope this helps!
Cheers,
Eugenio
Juan Eugenio Iglesias Translational Imaging Group University College London http://www.jeiglesias.com http://cmictig.cs.ucl.ac.uk/
On 9 Jun 2016, at 19:23, Fernando Pasquini Santos <fernandopasq@gmail.commailto:fernandopasq@gmail.com> wrote:
Dear,
I have a doubt regarding the input T1 image used for the Hippocampal Subfield segmentation in Freesurfer 6.0 - https://surfer.nmr.mgh.harvard.edu/fswiki/HippocampalSubfields
In this documentation it says that I can use a standard 1mm T1 image or the same standard 1mm T1 image with an additional scan. However, I want to use a 0.7mm T1 image as input, with an additional T2 scan. When I run the program with it, the output images (nu.mgz and orig.mgz) are downsampled to 1mm voxel size. So, I don't know if this happens just because of the recon-all program or if the segmentation is being done in the downsampled T1 image or in the original 0.7mm.
By reading the article "A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI" I saw that, in the methods section, the algorithm is used to segment 0.6mm T1 images. But is this possible to do in the Freesurfer package? Obviously, doing the segmentation directly on 0.7mm data would be better than a downsampled version to 1mm...
Thanks,
Fernando Pasquini Santos PhD student in Dynamic Systems fernandosantos@pitt.edumailto:fernandosantos@pitt.edu fernando.pasquini.santos@usp.brmailto:fernando.pasquini.santos@usp.br _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edumailto:Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
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