Jamie, There should be some other information in the log informing why the label is 'bad'. There are checks in the mri_ca_train for labels having strange coordinates, mainly there to catch things like a right- hippocampus label in the left hemisphere. So look for those type error messages in the mri_ca_train output.
Nick On Tue, 2009-04-28 at 15:47 -0500, Jamie Hanson wrote: > > Hi Jamie, > > what do you mean by "bad labels"? > > when going through each subject in mri_ca_train, some subjects output > the following: > ERROR: mri_ca_train: possible bad training data! subject: > /study/eemri/data/proc/freesurfer/30_aseg > > and then after all the subjects are finished in mri_ca_train, it says: > ERROR: mri_ca_train check found 6 subjects with bad labels! > > i edited everything by hand (and had another raters also check the > edits) and there is nothing visually, i can see that is wrong w/ the > segmentation edits. so i wasn't sure if something else went wrong and > i should remove those 6 subjects? > > best, > jamie. > > > > Bruce > > On Tue, 28 Apr 2009, Jamie Hanson wrote: > > > >> Hi Freesurfer folks- > >> > >> I am in the midst of creating a custom aseg atlas and had a quick > >> question regarding when to use v. discard subjects. > >> > >> I just ran the second iterations of mri_ca_train (when you use all the > >> subjects in subjects.csh and are training from segmented subjects > >> using M3D_ONE) and I have 6 (of 18) subjects "with bad labels". Is it > >> best to discard those subjects and just use the successfully labeled > >> subjects? I wasn't sure if only included those good subjects would > >> perhaps boost my aseg atlas accuracy. > >> > >> Thanks much. > >> > >> Best, > >> jamie. > >> > >> > > > > > _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
