Thank you for your feedback on my previous question regarding the surface area measurement. We found it very helpful to move forward.
I am beginning (again) to do longitudinal processing using fs4.5.0, but I just want to make sure that I understand everything right before starting this time. We have about 150 subjects with timepoints varying from 2-7, for a total of somewhere around 750 scans. All have already been processed cross-sectionally. 1. Reading through the wiki, the main thing to check on the cross-sectional runs are the control points. I'm confused by this though because the base creation only needs the reconstruction ran through the norm.mgz step to start. But we won't know if we need to add control points to the cross-sectional scan until after the surfaces are made, later in the stream. So it seems like I need to run the cross-sectionals through the norm.mgz step to start the base creation, but then before I run the -long part, I need to run the cross-sectionals through the surface reconstruction so that I can check the control points so that they can be copied from the cross-sectional run to the -long run? Are there any other edits I need to look at before starting the -base run? The cross-sectional brainmasks? The brainmask QA is just to make sure that the skull and other things are correctly stripped away? What about intensity normalization and gm/wm contrast on the norm.mgz image? 2. Also, in http://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg12895.html, Martin says "the cross sectional asegs are 'fused' (probabilistic voting), to initialize the labeling in the longitudinal runs." Can someone explain what this 'fused' means? This is the only place I have read this besides the short description in recon-all --help. So it seems like I need to finish the cross-sectionals pretty much completely before doing the -long run. 3. Why is the brainmask from the -base run used in the -long run? I can see how this increases consistency between timepoints, but it seems like there would be a larger benefit of using the brainmask from the cross-sectional run? 4. I read that if the -base is stopped halfway through due to earthquakes, then it can be restarted from some point in the stream. I will just restart it from the beginning for ease of use. My question is what if the -long stops halfway through? I forget the command I use to restart from the last step in the cross-sectional stream (our cluster is down now), but can I do the same thing: recon-all -long tp1 longbase -restart_from_last_step_command? And then I had some questions specific to our data, if you would permit me =) 1. We have timepoints from the past 6 years, and so our scanning parameters have changed. Our old data is 1x1x1.4mm and 144 slices and our new data is 1x1x1mm and 160 slices. Some subjects have an acceleration of 2, while most have no acceleration. Our scanner is a Siemens 3T Trio. Will I need to exclude any of these timepoints? From both -base and -long? The thread http://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg14014.htmlsays that the new stream significantly reduces these effects, but I just wanted to doublecheck. 2. Because of the way our group is set up, sometimes subjects will have more than one mprage - from different days, say one week apart - for each timepoint. Even though I will only use one of these mprages for each -long timepoint, will the -base be better if I include all of them? As a tangential question, could I use these close together visits and average their mprages in the -motioncor step? My feeling would be no, that I could only do that if the subject does not move, but I wanted to check. Sorry for the long questions! Thank you for all of your great help all the time! Jeff Sadino
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