What is the SST? Is it the base? Then yes, you should exclude a corrupted time point from the base as it will affect base results. I don't necessarily think that you have to exclude all time points from a subject if you accidentally included a corrupted time point in the base. The base serves to initialize the analysis for the longitudinal time point. Corruption that leaks into a base could leak into an uncorrupted long time point, but it might not. If the long looks ok, then you don't necessarily need to exclude it.External Email - Use Caution
Hi all, I have some questions regarding failed segmentations on longitudinal data.
We have large datasets of Huntington's disease with data collected longitudinally for 3-10 years. Freesurfer is our main tool to extract volumetric scores, particularly in caudate and putamen.
I usually QC Freesurfer segmentations and include the fail/pass status for other researchers to use. I inspect the segmentation of the cross-sectional pipeline because I noticed that mis-segmentations are clearer and the longitudinal pipeline does not seem to correct them. For example, a displaced putamen segmentation in cross-sectional pipeline becomes just more fuzzy in the longitudinal pipeline with more peppered voxels at the edges. So basically, my QC of the cross-sectional segmentation decides if the timepoint is good or not.
I have three questions:1. Is my understanding correct that a motion corrupted scan (i.e., with motion rings) is going to affect the other timepoints by compromising the SST? Thus the only solution would be to exclude the motion corrupt timepoint from FS processing? And in case the timepoint has been processed with FS, is the best practice to exclude the entire subject given that the bad scan have compromised the accuracy of other timepoint segmentations?
The cross segs are fused into the base seg and the base seg is used to initialize the long seg, so a bad cross seg could leak into a non-bad long seg.2. On a different scneario, if a timepoint has a good scan but Freesurfer's segmentation is simply innacurate or displaced, is this bad segmentation at the cross-sectional level going to affect the other timepoints after running the longitudinal pipeline?
I'm not sure what you are asking here. You can't exclude just the segmentation from the long analysis. You'd have to exclude the entire time point.. This is the most important question: is there a common recommendation or practice how to deal with failed segmentations in the longitudinal pipeline? Correcting manually the segmentations is not an option, so I am asking whether we can just exclude the failed segmentation timepoint from the analysis or whether we should exclude the entire subject?
Thank you for sharing any thoughts. I cannot seem to find information on this topic on papers or the mailing list, so any tips on how you or your lab deals with these issues can help.
Dorian
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