External Email - Use Caution
What are you using for denoising?
Matt.
From: <freesurfer-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Lisa Crystal Krishnamurthy <lkrishnamurthy@gsu.edumailto:lkrishnamurthy@gsu.edu> Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu> Date: Thursday, October 11, 2018 at 11:05 AM To: "freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu" <freesurfer@nmr.mgh.harvard.edumailto: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
________________________________ The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail.
External Email - Use Caution
The ONLM denoising algorithm in the following package: (https://sites.google.com/site/pierrickcoupe/softwares/denoising-for-medical-...https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsites.google.com%2Fsite%2Fpierrickcoupe%2Fsoftwares%2Fdenoising-for-medical-imaging&data=02%7C01%7Clkrishnamurthy%40gsu.edu%7Cadf6338b011843f3549d08d62f89e5d0%7C515ad73d8d5e4169895c9789dc742a70%7C0%7C0%7C636748666676225518&sdata=F0mfd%2B63mdYPHplRq4jcjz9FuSvE2nUxMxqDlFfIZB4%3D&reserved=0)
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
External Email - Use Caution What are you using for denoising?
Matt.
From: <freesurfer-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Lisa Crystal Krishnamurthy <lkrishnamurthy@gsu.edumailto:lkrishnamurthy@gsu.edu> Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu> Date: Thursday, October 11, 2018 at 11:05 AM To: "freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu" <freesurfer@nmr.mgh.harvard.edumailto: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
________________________________ The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail.
External Email - Use Caution
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}
External Email - Use Caution 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-...https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsites.google.com%2Fsite%2Fpierrickcoupe%2Fsoftwares%2Fdenoising-for-medical-imaging&data=02%7C01%7Clkrishnamurthy%40gsu.edu%7Cadf6338b011843f3549d08d62f89e5d0%7C515ad73d8d5e4169895c9789dc742a70%7C0%7C0%7C636748666676225518&sdata=F0mfd%2B63mdYPHplRq4jcjz9FuSvE2nUxMxqDlFfIZB4%3D&reserved=0)
Best, -Lisa
From: freesurfer-bounces@nmr.mgh.harvard.edumailto: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
External Email - Use Caution What are you using for denoising?
Matt.
From: <freesurfer-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Lisa Crystal Krishnamurthy <lkrishnamurthy@gsu.edumailto:lkrishnamurthy@gsu.edu> Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu> Date: Thursday, October 11, 2018 at 11:05 AM To: "freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu" <freesurfer@nmr.mgh.harvard.edumailto: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
________________________________ The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail.
External Email - Use Caution
Dear Falk,
I tried to search your poster presentation in the 2018 ISMRM web but unfortunately I did not find it. Can you attach the link? I would be interested in this information and how to proceed.
Thanks in advance,
Best,
El vie., 12 oct. 2018 a las 13:59, Falk Lüsebrink (falk.luesebrink@ovgu.de) escribió:
External Email - Use CautionDear 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}
External Email - Use Caution *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-... https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsites.google.com%2Fsite%2Fpierrickcoupe%2Fsoftwares%2Fdenoising-for-medical-imaging&data=02%7C01%7Clkrishnamurthy%40gsu.edu%7Cadf6338b011843f3549d08d62f89e5d0%7C515ad73d8d5e4169895c9789dc742a70%7C0%7C0%7C636748666676225518&sdata=F0mfd%2B63mdYPHplRq4jcjz9FuSvE2nUxMxqDlFfIZB4%3D&reserved=0 )
Best,
-Lisa
*From:* freesurfer-bounces@nmr.mgh.harvard.edu [ mailto:freesurfer-bounces@nmr.mgh.harvard.edu 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
External Email - Use Caution *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
The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail. _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
External Email - Use Caution
Dear Miguel,
sorry that I forgot to attach the link to the abstract. You can find it here: http://archive.ismrm.org/2018/2834.html
Best, Falk
Von: freesurfer-bounces@nmr.mgh.harvard.edu [mailto:freesurfer-bounces@nmr.mgh.harvard.edu] Im Auftrag von Miguel Ángel Rivas Fernández Gesendet: Freitag, 12. Oktober 2018 14:18 An: Freesurfer support list freesurfer@nmr.mgh.harvard.edu Betreff: Re: [Freesurfer] denoising and recon-all {Disarmed}
External Email - Use Caution Dear Falk,
I tried to search your poster presentation in the 2018 ISMRM web but unfortunately I did not find it. Can you attach the link? I would be interested in this information and how to proceed.
Thanks in advance,
Best,
El vie., 12 oct. 2018 a las 13:59, Falk Lüsebrink (<falk.luesebrink@ovgu.demailto:falk.luesebrink@ovgu.de>) escribió:
External Email - Use Caution 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.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu [mailto:freesurfer-bounces@nmr.mgh.harvard.edumailto: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.edumailto:freesurfer@nmr.mgh.harvard.edu> Betreff: Re: [Freesurfer] denoising and recon-all {Disarmed}
External Email - Use Caution 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-...https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsites.google.com%2Fsite%2Fpierrickcoupe%2Fsoftwares%2Fdenoising-for-medical-imaging&data=02%7C01%7Clkrishnamurthy%40gsu.edu%7Cadf6338b011843f3549d08d62f89e5d0%7C515ad73d8d5e4169895c9789dc742a70%7C0%7C0%7C636748666676225518&sdata=F0mfd%2B63mdYPHplRq4jcjz9FuSvE2nUxMxqDlFfIZB4%3D&reserved=0)
Best, -Lisa
From: freesurfer-bounces@nmr.mgh.harvard.edumailto: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
External Email - Use Caution What are you using for denoising?
Matt.
From: <freesurfer-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Lisa Crystal Krishnamurthy <lkrishnamurthy@gsu.edumailto:lkrishnamurthy@gsu.edu> Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu> Date: Thursday, October 11, 2018 at 11:05 AM To: "freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu" <freesurfer@nmr.mgh.harvard.edumailto: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
________________________________ The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail. _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edumailto:Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
-- Miguel Ángel Rivas Fernández
freesurfer@nmr.mgh.harvard.edu
-
Falk Lüsebrink -
Glasser, Matthew -
Lisa Crystal Krishnamurthy -
Miguel Ángel Rivas Fernández