There of course is some variability in the analysis due to the way the segmentation happens. Your results are certainly not out of the ordinary for the volume you are viewing. On average you can expect a ~1% variance between several scans of the same subject.
If you want to know more I certainly suggest reading the paper titled: "Whole Brain Segmentation: Automated Labeling of Neuroanatomical Structures in the Human Brain"
- Bryan
Actually, if you run 'recon-all' a second time (from scratch) on the same subject, on the same platform/architecture, and you use the default recon-all settings (i.e., don't use the -randomness flag, or specify your random seed via the -rng-seed flag), then you should get identical results, because for quite a few versions now, recon-all has been set up to use the same random seed (1234) in all the binaries that involve randomness.
cheers, -MH
-- Michael Harms, Ph.D.
----------------------------------------------------------- Conte Center for the Neuroscience of Mental Disorders Washington University School of Medicine Department of Psychiatry, Box 8134 660 South Euclid Ave. Tel: 314-747-6173 St. Louis, MO 63110 Email: mharms@wustl.edu
On 6/23/14 12:05 PM, "Chiu, Bryan (PHTH)" bryan.chiu@ubc.ca wrote:
There of course is some variability in the analysis due to the way the segmentation happens. Your results are certainly not out of the ordinary for the volume you are viewing. On average you can expect a ~1% variance between several scans of the same subject.
If you want to know more I certainly suggest reading the paper titled: "Whole Brain Segmentation: Automated Labeling of Neuroanatomical Structures in the Human Brain"
- Bryan
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________________________________ 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.
yes, that was our goal some time ago and we thought we had succeeded in tracking down and fixing any randomness if the same seed is specified
Bruce
On Mon, 23 Jun 2014, Harms, Michael wrote:
Actually, if you run 'recon-all' a second time (from scratch) on the same subject, on the same platform/architecture, and you use the default recon-all settings (i.e., don't use the -randomness flag, or specify your random seed via the -rng-seed flag), then you should get identical results, because for quite a few versions now, recon-all has been set up to use the same random seed (1234) in all the binaries that involve randomness.
cheers, -MH
-- Michael Harms, Ph.D.
Conte Center for the Neuroscience of Mental Disorders Washington University School of Medicine Department of Psychiatry, Box 8134 660 South Euclid Ave. Tel: 314-747-6173 St. Louis, MO 63110 Email: mharms@wustl.edu
On 6/23/14 12:05 PM, "Chiu, Bryan (PHTH)" bryan.chiu@ubc.ca wrote:
There of course is some variability in the analysis due to the way the segmentation happens. Your results are certainly not out of the ordinary for the volume you are viewing. On average you can expect a ~1% variance between several scans of the same subject.
If you want to know more I certainly suggest reading the paper titled: "Whole Brain Segmentation: Automated Labeling of Neuroanatomical Structures in the Human Brain"
- Bryan
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.
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
freesurfer@nmr.mgh.harvard.edu
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Bruce Fischl -
Chiu, Bryan (PHTH) -
Harms, Michael