Hi Elizabeth
I guess it could help by removing a feature that is variable across subjects so things like the talairach transform are more stable
cheers Bruce On Thu, 30 Nov 2017, Buimer, E.E.L. wrote:
Dear FreeSurfer experts,
We want to implement a deface method to ensure anonymity of participants before making the data available to researchers. Because the raw data is stored on the imaging platform XNAT, we preferred the mask_face method implemented on the XNAT server rather than FreeSurfer’s defacing. However, we will be using FreeSurfer for processing and segmentations afterwards. I am currently investigating the effect of face and earmasks on brain measures. I used FreeSurfer v5.3 (freesurfer-x86_64-unknown-linux-gnu-stable5-20130513) and the mask_face function developed for XNAT (Milchienko & Marcus, 2013) with the default normalized filter. The masks were not invasive and did not overlap with brain tissue.
I compared output of the recon-all between T1 scans with and without masked face for a small sample. I found high correlations between the output of the two scans (extracted values: cortical thickness, surface area, (sub)cortical volume, global values). Slight differences seem to occur from the start of the recon-all (talairach transform). Adding ear masks to the face-masked scans, made the differences smaller (i.e. higher correlations with raw scans). Also, the recon-all run time appears to be reduced.
Could you explain how face and ear information is used in the recon-all and why adding ear masks to masked-face scans might reduce run-time and improve reliability? Could it be the case that skull stripping is easier without ears for example?
Thank you in advance.
Kind regards,
Elizabeth
Elizabeth Buimer, Research Assistant
Department of Psychiatry, UMC Utrecht
Room: A.01.161
e.e.l.buimer@umcutrecht.nl
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