I am trying to use the Morphologist Pipeline (non-UI) (from BrainVISA version 4.5) on a Mac (OSX 10.9), and I am running into a few errors. I am not using the UI because the T1MRI's I have are already preprocessed/masked/skull stripped, and the UI procedure applies another brain mask that causes some sulci to not be traced (namely the Orbitfrontal Sulci, which are the sulci I am interested in--the additional brain mask does not encompass the full orbitofrontal cortex). However if there is a way to customize the UI procedure and avoid the creation of a new brain mask, please let me know.
In the non-UI version, I have been using the different models/approaches but have not had luck with any of them. The ANN model will run to completion, but will throw a warning saying that the 3.0 version is being used and isn't completely compatible with the 3.1 version. I tried to use the 3.1 discriminative models but the pipeline throws an error saying the 3.1 model's .dat file has no value. The Global Registration appears to allow for correct labeling of sulci, but takes up to 50 minutes to run, which is especially long compared to how the full pipeline can be run in the UI on a brain on my computer within 6 minutes. The Talairach model will run quickly, but incorrectly labels all the sulci, and when I use the Talairach/Global models with local/markovian models (or with local/markovian on their own without Talairach/global registration), the program doesn't run to completion. With local, the error output is:
Traceback (most recent call last): File "/brainvisa-4.5.0/scripts/sigraph/sulci_registration/independent_tag_with_registration.py", line 473, in <module> if __name__ == '__main__' : main() File "/brainvisa-4.5.0/scripts/sigraph/sulci_registration/independent_tag_with_registration.py", line 441, in main elif model_type == 'spam' : d = SpamTagger(*tagger_opt) File "/brainvisa-4.5.0/scripts/sigraph/sulci_registration/independent_tag_with_registration.py", line 258, in __init__ Tagger.__init__(self, *args, **kwargs) File "/brainvisa-4.5.0/scripts/sigraph/sulci_registration/independent_tag_with_registration.py", line 66, in __init__ gd = gaussians_distrib['vertices'][label] KeyError: 'F.C.L.a._left'
With Markovian, it runs to completion but gives these warnings, and does not properly label the sulci:
/brainvisa-4.5.0/lib/python2.6/site-packages/scipy/stats/distributions.py
/brainvisa-4.5.0/python/sulci/models/distribution.py:820: RuntimeWarning: divide by zero encountered in log 0, self._scale))
/brainvisa-4.5.0/lib/python2.6/site-packages/scipy/stats/distributions.py
Also, I tried to use the Simplified Morphologist pipeline, but even after I entered in all the parameters, it tells me "transformation_information" has no value. I tried to edit the .bvproc file to enter a value for it, but the resulting .bvproc file will not open in brainvisa after.
I've been using Morphologist 2015 for all of these, but the older pipelines are also behaving the same for me.
In summary, I have not been able to use the Morphologist Pipeline's sulci labeling except for when I wait 50 minutes with the global registration model. The previous parts of the pipeline/segmentations have all been working well and have a good output (except for some issues in the split brain mask creation, which only runs when I uncheck the "use template" option, but still has generally good segmentation). The subject.arg sulci maps have resulted very well, only they cannot be labeled efficiently as I have described above.
I can avoid all these problems by just using the UI instead and using raw data (with skull intact), but if anyone can give me advice for how to use the non-ui pipeline I would greatly appreciate it as I hope to create a bash script that automates the pipeline's execution and orbit frontal sulcus isolation (with create sulcus label volume) altogether so I can run it on many subjects who already have had skull-stripping/preprocessing.
Thank you!
Will Snyder