Hi Matt,
you can use strategy 3 of my previous email ;-)
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 19:31, Matt Glasser <[email protected]<mailto:[email protected]>> 
wrote:

I would be interested to know how well 0.7mm isotropic resolution data performs 
at hippocampal segmentation.  It would be better if folks could do this then 
needing to acquire specialized anisotropic scans for hippocampal segmentation.

Peace,

Matt.

From: 
<[email protected]<mailto:[email protected]>>
 on behalf of Fernando Pasquini Santos 
<[email protected]<mailto:[email protected]>>
Reply-To: Freesurfer support list 
<[email protected]<mailto:[email protected]>>
Date: Thursday, June 9, 2016 at 1:23 PM
To: "[email protected]<mailto:[email protected]>" 
<[email protected]<mailto:[email protected]>>
Subject: [Freesurfer] Hippocampal subfields segmentation - what is the voxel 
size of the input?

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
[email protected]<mailto:[email protected]>
[email protected]<mailto:[email protected]>
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