> 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. >> >> > -- Jamie L. Hanson Waisman Laboratory for Brain Imaging & Behavior | Child Emotion Research Lab University of Wisconsin - Madison 1500 Highland Avenue Madison, WI 53705 Email: jamielarshan...@gmail.com Homepage: http://tezpur.keck.waisman.wisc.edu/~hanson/ _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
