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.bui...@umcutrecht.nl
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