is that all it says? I think we put some checks in to make sure that e.g. the left hippocampus wasn't labeled right. Is there anything like that in the output?
On Tue, 28 Apr 2009, 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.