Hi Martin,

In addition to the --gpu=all or 0 flag for Docker, you'll need to include the 
-g flag for SynthMorph to enable the GPU. You can choose the device by setting 
CUDA_VISIBLE_DEVICES; SynthMorph will default to 0. Affine registration should 
require at least 16 GB of device memory, and the deformable model needs 24 GB.

While there may be some speed-up, keep in mind that there are several 
resampling steps that SynthMorph delegates to surfa, and these will still use 
the CPU. I'm not aware of anyone having tested it for distortion correction.

Best wishes,
Malte

________________________________________
From: [email protected] 
<[email protected]> on behalf of Martin Kavec 
<[email protected]>
Sent: Friday, November 8, 2024 06:12
To: Freesurfer support list
Subject: Re: [Freesurfer] FS version 8-beta

        External Email - Use Caution

Hi,

Thanks a lot.

I am particularly excited to the Synth* tools. I am trying SynthMorph from 
docker. I see that it does not use GPU (nvtop). I tried adding —gpus=0 but 
still see that inference runs on CPU (htop).

Are there any experiences in registering DTI to T1 to correct for distortions, 
instead of topup? I do not have AP-PA images.

Thanks

Martin

On Thu, 7 Nov 2024 at 20:38, Aaron Tanenbaum 
<[email protected]<mailto:[email protected]>> wrote:

        External Email - Use Caution

Awesome, Will this version be able to process over older versions of FreeSurfer?

On Thu, Nov 7, 2024 at 11:54 AM Douglas N. Greve 
<[email protected]<mailto:[email protected]>> wrote:
Hi All, as some of you have figured out, we have a beta version of FS 8.0.0. 
Please give it a spin and let us know if you have any problems or concerns.

The release notes are here MailScanner has detected a possible fraud attempt 
from "secure-web.cisco.com" claiming to be 
https://surfer.nmr.mgh.harvard.edu/fswiki/ReleaseNotes<https://secure-web.cisco.com/1nfzJIH7mosYphab5nKXdF6Pe6cRILHpFbuENvvf0xNybGXN5dFVNHJpGgR0en61nEygdqxr_r1Wc2lzTP8tMxj2Mm5Kd12legZwYkmuUNI6W1pV128FFEKR50sXw0SWoAhimRb0wA4zNSb8vHOLda-h3SFtiXHW3UijR_Q2VNWxXg9Mf_u2QEuTxw6FSxJfmShpM3jaSD_K-mKrVmEKpykxD0152nXBL4MJ2LBp6Rio8mv0TzalahFHdHUqcEqnNmqL-1p1v1D3WuBFgM7CaT1LKZ5UQdNaQRKtd65tOkK2y1wIdk-WpFqLJknkohHGN/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FReleaseNotes>
 which I have copied below.
One bug that we have already found is that you must set environment variable 
FS_ALLOW_DEEP to 1, eg, export FS_ALLOW_DEEP=1 (for bash) or setenv 
FS_ALLOW_DEEP 1 (for csh/tcsh)

thanks
doug

  *   Now uses 
SynthSeg<https://secure-web.cisco.com/1KBsMN2BPKXgFi2gdkFpM55EcglFvUieMSC91xEli7Gih0z7b614Aab1GJgskTCYke2PuFnswV1hgD8u4nKYa8qMZ56B8A8PyQ1PWichRRzI-OEimPC821sAeiu-pzo0Pi66Y3tKOQEmBj3zsy3LPEca2e35qnmjk8bQlUMIK420Yl0Wyp-2Zun1yWx-KcSQ6HeWNeT06W8plWjAv65wqzY3Jlo3jB_ee1aglB1FAOFqy5Ue5RU63BdmWOeX36flyPoiFNj6XyHrYmLsoqNf9bNHQrtUgysUnQtNo0E0CCsb6HLinq_gY7ix7_FqSVBMQ/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FSynthSeg>,
 
SynthStrip<https://secure-web.cisco.com/1VXLmpw2yihWcZU0vul0tnP_5VpqF82JyCCwIVae31F_LCDzCk2x448Vt7fow8QIvtbXMZ0KHWP-fAgLeSiV9LIg_azUp_nU-10_YJYDCO42xs5WTgpbTq3O8Y_-dKGgalVqigH2xrUmVtw_oUcXxxLEt1gKz61xWqwwFan2pn5t9igJpdDLkSAJCZfxusDF95EYrUeaCBVIJfqe8q3mnfC3ujb5Ul8nz79yOJaOAMJbm4zkKysaeyMzaiNnYsVkGsraKHAz20mNCwC65TDzZ2ZJp4yWkJKEKXS2JEklcjidLF9AZZJll4UvKzjL9wfVw/https%3A%2F%2Fsynthstrip.io>,
 and 
SynthMorph<https://secure-web.cisco.com/1gV8mZhIt5XFZ04MEHNjyef68jYwr64lzOgyCeaG_kXAM5rQmht_BVbkfa7EIgfGgCmVQuMNSxCd9Hmssboq7tP1ZkCjBTjgCE3QgKJYVmV5qs-XLzi0L2U_7DhKUfdYcD1BEg2UDOwUq9yl33C1sGtlHC1bx_bE_d3s_dJpG55I-BaJWCIgRnBQETLH9e3Rflmr8pl4mCUpETAZSuHKKV3FXyqeOYL_aPhXo18yP-BEvaK-O8Dasd4cyY8xWmnBC3xj2n5-VQrwa4z_jeqeBCs_yJmYFJXAo10ruHtKEnCMQKY8VUamhlr39tJil6EXB/https%3A%2F%2Fsynthmorph.io>
 (deep learning algorithms). These make recon-all more robust and much faster. 
Technically, 
SynthMorph<https://secure-web.cisco.com/1gV8mZhIt5XFZ04MEHNjyef68jYwr64lzOgyCeaG_kXAM5rQmht_BVbkfa7EIgfGgCmVQuMNSxCd9Hmssboq7tP1ZkCjBTjgCE3QgKJYVmV5qs-XLzi0L2U_7DhKUfdYcD1BEg2UDOwUq9yl33C1sGtlHC1bx_bE_d3s_dJpG55I-BaJWCIgRnBQETLH9e3Rflmr8pl4mCUpETAZSuHKKV3FXyqeOYL_aPhXo18yP-BEvaK-O8Dasd4cyY8xWmnBC3xj2n5-VQrwa4z_jeqeBCs_yJmYFJXAo10ruHtKEnCMQKY8VUamhlr39tJil6EXB/https%3A%2F%2Fsynthmorph.io>
 is not needed for recon-all to run, but the nonlinear registration can be used 
in multimodal analysis to map to the MNI152.

  *   There is now DL automatic segmentation of regions that often cause errors 
in pial surface placement. These include the major sinuses (sagittal and 
transverse) as well as a spot between frontal and temporal lobes where the 
middle cerebral artery (MCA) and dura cause bright areas.
  *   Several fixes in entorhinal cortex. First, the WM in EC is segmented 
using DL. The WM is often only 0.5mm thick and very hard to see; this often 
resulted in severe white surface areas in this location requiring manual 
editing to fix. The new surface now represents gyrus ambiens much better. 
Second, The white surface is extended to the front of amygdala. Third, the 
binary cortex of label now covers entorhinal cortex and parts of the temporal 
pole better allowing the pial surface to extend out to its true edge.
  *   Some bugs where found in and around inferior frontal cortex causes the 
white surface to extend too far into basal ganglia. This has been fixed. This 
is above and beyond the issue reported in 7.3.2 below.
  *   All the bug fixes described below are now turned on by default.
  *   These changes will work with longitudinal with the caveat that the 
volumetric segmentation will not be fully longitudinal. The segmentation will 
be applied to the time point in the base space, but it will not (and cannot) be 
initialized with the base segmentation. Initial tests indicated that the change 
in power was minimal and mixed.
  *   recon-all will now run in about 2h vs 8h on a single CPU. It will, 
however, required about 24GB of memory to run.
  *   The use of 
SynthStrip<https://secure-web.cisco.com/1VXLmpw2yihWcZU0vul0tnP_5VpqF82JyCCwIVae31F_LCDzCk2x448Vt7fow8QIvtbXMZ0KHWP-fAgLeSiV9LIg_azUp_nU-10_YJYDCO42xs5WTgpbTq3O8Y_-dKGgalVqigH2xrUmVtw_oUcXxxLEt1gKz61xWqwwFan2pn5t9igJpdDLkSAJCZfxusDF95EYrUeaCBVIJfqe8q3mnfC3ujb5Ul8nz79yOJaOAMJbm4zkKysaeyMzaiNnYsVkGsraKHAz20mNCwC65TDzZ2ZJp4yWkJKEKXS2JEklcjidLF9AZZJll4UvKzjL9wfVw/https%3A%2F%2Fsynthstrip.io>
 should make recon-all much more robust as the old skull stripping method often 
included extra cerebral tissue.

  *   With synthseg, we are now supplying a segmentation-based total 
intracrainial volume (sTIV) along with the registration-based estimated TIV 
(eTIV)
  *   We have applied v8 to several studies (aging, AD crossectional, AD 
longitudinnal, schizophrenia). There were no major changes in the ability to 
detect effects, and there was no interaction between effect and version. But 
let us know how it performs on your studies.




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