External Email - Use Caution        

I've just exposed the option to the user. It might take some days before it
will be available in the development version.

@sudeepti: In the new development version, if you add to your
samseg command the following flag "--do-not-use-shape-model", the lesion
shape model (VAE) will not be used. This will most probably produce a
lesion segmentation with more true positives *and* more false positives.
Please double-check the results if you're using this option.

Stefano

On Fri, Jan 5, 2024 at 11:20 AM Koen Van Leemput <leem...@gmail.com> wrote:

>         External Email - Use Caution
>
> Hi Stefano,
>
> For samseg isn't there also an option to disable the VAE shape model? I
> forgot the details, but if false positives are not an issue maybe that
> could also help?
>
> Koen
>
> On Friday, January 5, 2024, Stefano Cerri <ste.45....@gmail.com> wrote:
>
>>         External Email - Use Caution
>>
>> Hi,
>>
>> For SAMSEG:
>>
>> Are you using the --lesion-mask-pattern flag with the value "1" on the
>> FLAIR scan? You can try to relax the masking by excluding darker than WM
>> mean intensities voxels rather than darker than GM ones, i.e., by adding to
>> your command: --lesion-mask-structure "White"
>>
>> For WMH-SynthSeg:
>>
>> It looks like a memory error (the process was killed). On the Wiki: 
>> *MailScanner
>> has detected a possible fraud attempt from "secure-web.cisco.com" claiming
>> to be* 
>> https://secure-web.cisco.com/1n6HHxGODqkOuO4bNnigMhWKnI-nKae-t26hw5s_Sdz9GzWiUDG_AtQ_j3y3ivmY1bmsnhBUnuuvFPcgoa2Ua5qxVd2xrLqy1F6WaQqEFMV2oyQt1k1XiINNYLrPrgl_55cjqyYyK-0u0uTe8FglkHsn4QxDt9cGdw6DVTpcrCn1Djm11J3BMY7juusRHnx7T1Ifog1C9FbOf_lSU9arBqg8dq0W6qyObwIZs4mXMO62bnn-LGm7gFX80Hl5jA_A5WtNdmQ2Fvkp1nzKkDTXPxhQYUxdWzBikOu49wbIrBb0nSjwVccUy7pV40H2YjjLnI276nbbmJAPQapRw3FHrRw/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FWMH-SynthSeg
>> <https://secure-web.cisco.com/1HuCfTaru0pjBRImg5FBdnCDAClGBp2QhQDG_ONxySiD4aBpb8dX_9OWokS_PrsTYfMYUj6Dub6piUJi2g2Zpl7rhqLNDkcwSORd5hQ3SUk7_fYeGPCEOrfp3QjhjjHebnuj-k3zV_yc_wRKAI-jbX5BHqaNgPByMMc7-bhmMcBGophr1_lP4tmBxmq-SvMcZ0iWerp81-cOXMxo4NtbhS5gIUIhprFiFtLhcXjlwCtPcMIaIHbmTzL5XjtfzOLAg-22R7Awi6o7400qTCzIKXxyS473rB0txewIziNjlNmHT6MgPBPh5iwHokUj3naGQ_jEESDEujufpSbUwtVxLbA/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FWMH-SynthSeg>
>> they recommend 32GB of RAM. Do you have access to a machine with more RAM?
>>
>> Stefano
>>
>> [Freesurfer] WMH-SynthSeg vs. SAMSEG for WM lesions
>> <https://secure-web.cisco.com/10UF5Sfsck6gBiuQyh4tRFtvmnzLpFEUi-WgbbCbj9UG2boB9N5XjVjTMWP2Y5j0lQtS3keltoGD7fPWDgtVe4_5zwOh3es5NY-BMN0A-JNk3wH3si-segJF_xIACeMG_YaMeVT-mTgyjusr2X32cUZsjuXj60HXiGVdQp0SfFDc9lQHUzFNKP3zkFwCj3pM52K3KI10F1CmH4AxI-FtLil2AAV-fRw1C8_HdbId3ZjXeXMyJ7gC8DUXEWapUSmiRGZACymUMayzcIvfmH1L1S2za6QCGAGCsPoM8UG7wXCdJkTPJuWZKCpJPNYKouK85kbjGj8LeyF54sUq5M5VR-A/https%3A%2F%2Fwww.mail-archive.com%2Fsearch%3Fl%3Dfreesurfer%40nmr.mgh.harvard.edu%26q%3Dsubject%3A%2522%255C%255BFreesurfer%255C%255D%2BWMH%255C-SynthSeg%2Bvs.%2BSAMSEG%2Bfor%2BWM%2Blesions%2522%26o%3Dnewest>
>>
>> SudEEpti
>> <https://secure-web.cisco.com/1oJN1ySIU6hTF6KozyWDOxPUxnfQT6NbHWVuqvL4RV_PNw-mjuH5HUIQ_4CrcrA2nB92UzWiqt0sldQoX7neyVBIx5YQ_ClIloJhwjfN3Wr-65IptS-tt7ZRgYRK4ptYQGQfsFX5B8cKOsc0-XY7SOZxDPnLT5_SQDK_zbCwXForrAFt6h-C4TbVXo15OSdI9A8_Wa4dkPrebnymfACMnEVmCmQyBjnkS71J2FBFdGJ1m8j_Gmkg7V-5nKiYy-Loc0f8uI6uvcCDH2wkofUf0wC8tT9K0feA_coqMJR_k3brvE_FKWAKCcp4TEUfmxhx39s2jcXEa0Kk6Ko5v93TwIA/https%3A%2F%2Fwww.mail-archive.com%2Fsearch%3Fl%3Dfreesurfer%40nmr.mgh.harvard.edu%26q%3Dfrom%3A%2522SudEEpti%2522>
>>  Thu, 04 Jan 2024 23:54:04 -0800
>> <https://secure-web.cisco.com/1JsH5pJG8BzMI3v8LKsEGcmt1J0aRmNdo-KqIrQw8arF8BP4GEGTyt7o7BBWBpoBhFnf7H2f8hDDHgVlApzrrpJd2B6CFkE6_1l2GHF-la-9yG9VlF8r8WARQiwmJu8zcMm1Lo6NFMGySBH954XRq9sg_4lBw_KdBCO3c04OTsh4eiUGXUNVO4_ev_uGvK9CaGTT5qsKtJouRpJarF-2rJi15G4_C7HH3EQu1fTC-ZfCnZR_Iu-HmfT3RIgmWaGcMQ39UdoH5yjZTKXI60uUiVnYj8_pwvoQ1Je2JsEFnyBS_EBQIAzYniwh1Cqk6q8EevaCdjfZi-bisWeUEnjws8g/https%3A%2F%2Fwww.mail-archive.com%2Fsearch%3Fl%3Dfreesurfer%40nmr.mgh.harvard.edu%26q%3Ddate%3A20240104>
>>
>>         External Email - Use Caution
>>
>> Hello Freesurfer
>>
>> I am reaching out for some advice on unsupervised WM lesion detection using
>> SAMSEG and WMH-SynthSeg.
>>
>> *SAMSEG: *
>> Our use case prioritizes maximizing true positives over minimizing false
>> positives. However, even with a low threshold of 0.1, SAMSEG misses some
>> areas (on FLAIR). Are there any strategies or parameters to force SAMSEG to
>> be more "aggressive"?
>>
>> *WMH-SynthSeg:*
>> Unfortunately, I have not been able to get WMH-SynthSeg to work. The error
>> message is pasted below. Does this point to a memory issue (I have 24GB
>> RAM)?
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>
>> *Arguments seem correct; loading Python packages...Using cpuUsing 1
>> thread(s)Preparing model and loading weightsWorking on image 1 of 1:
>> /home/localuser01/southekal/TEMP/101-001_3scans_FLAIR/101-001-1_reg.mgz
>>  Loading input volume and normalizing to [0,1]     Upscaling to target
>> resolution     Pushing data through the CNNKilledreal 3m33.897suser
>> 2m48.028ssys 0m32.337s*
>>
>> Any insights or suggestions would be greatly appreciated! Thank you in
>> advance.
>>
>> _______________________________________________
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>>  
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