Hello FSL group,
I have a Melodic question for you. I was reading a post from last November discussing removing
components of noise. Christian mentioned that typically in denoising one removes components
based on structure, which makes sense to me. The post said that such a method includes removing
non-Gaussian noise, which if anything inflates the false negative rate. I have some noise in my data
that appears as striations across axial slices (possibly RF noise?) throughout several of my scans.
Components that are entirely made of these striations are almost completely Gaussian. Is it
appropriate to select components with these striations based on structure first, but then remove
them only if they are highly Gaussian (which happens unless there is something other than striations
occurring in that component)? I would like to remove the noise related to this artifact without
removing signal that may be related to the task, but I want to make sure that this will not increase
the false-positive rate because of removing some of the variance (as was discussed in the post). In
other words, does what was written still apply if the components are identified first structurally?
Thank you,
Meredith
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