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Dear Lisa,
what you potentially can do is to use the denoised surface (*h.white) as a starting point (instead of *h.orig) in the unfiltered stream. This should remove any bias introduced by the denoising, however, you should gain the advantages of denoised surfaces, e.g. less need for manual intervention, less topological defects, etc.
I had a poster presentation for this method at last ISMRM.
Best,
Falk
Von: freesurfer-bounces@nmr.mgh.harvard.edu [mailto:freesurfer-bounces@nmr.mgh.harvard.edu] Im Auftrag von Lisa Crystal Krishnamurthy
Gesendet: Donnerstag, 11. Oktober 2018 19:07
An: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Betreff: Re: [Freesurfer] denoising and recon-all {Disarmed}
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The ONLM denoising algorithm in the following package: (MailScanner has detected a possible fraud attempt from "na01.safelinks.protection.outlook.com" claiming to be https://sites.google.com/site/pierrickcoupe/softwares/denoising-for-medical-imaging)
Best,
-Lisa
From: freesurfer-bounces@nmr.mgh.harvard.edu [mailto:freesurfer-bounces@nmr.mgh.harvard.edu] On Behalf Of Glasser, Matthew
Sent: Thursday, October 11, 2018 12:39 PM
To: Freesurfer support list
Subject: Re: [Freesurfer] denoising and recon-all
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What are you using for denoising?
Matt.
From: <freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Lisa Crystal Krishnamurthy <lkrishnamurthy@gsu.edu>
Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Date: Thursday, October 11, 2018 at 11:05 AM
To: "freesurfer@nmr.mgh.harvard.edu" <freesurfer@nmr.mgh.harvard.edu>
Subject: [Freesurfer] denoising and recon-all
External Email - Use Caution
Hi,
I have found that denoising the MPRAGE prior to FS recon-all seems to improve the segmentation (see attached pdf). However, it is not clear if the denoising algorithm may cause some signal intensity changes (especially in voxels with partial voluming at the edge of the brain) that violate assumptions of recon-all. Could you help me understand what the assumptions of your algorithm are, and what I need to do to make sure my images conform to those assumptions?
Your help is greatly appreciated.
Best,
-Lisa
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