[Neuroimaging] Segmentation of .nii file using WatershedSkullStrip()
suprajasankari at gmail.com
Tue Dec 12 02:56:32 EST 2017
Thanks for the input. I am using FAST FSL routine although i am wondering
if it's possible to process multiple anatomical images at once. I think
processing one image takes 10-20 minutes. Is this usually done on the cloud
On Sun, Dec 10, 2017 at 6:23 AM, Satrajit Ghosh <satra at mit.edu> wrote:
> in order to actually execute the command you will need to call
> skullstrip.run(). you may need to set some other parameters to watershed to
> get labeled output. you can also consider other routines like FAST from FSL
> and AntsCorticalThickness from ANTS.
> On Thu, Dec 7, 2017 at 7:42 AM, Supraja Jayakumar <
> suprajasankari at gmail.com> wrote:
>> I am trying to use the above API for segmenting .nii.gz (should i extract
>> it first?) files from the ABIDE datasets into white and grey matter. After
>> 'mri_watershed -T1 transforms/talairach_with_skull.lta T1.mgz
>> The full code is here:
>>> from nipype.interfaces.freesurfer import WatershedSkullStrip
>>> skullstrip = WatershedSkullStrip()
>>> skullstrip.inputs.in_file = '/home/venkat/connectomes/data
>>> skullstrip.inputs.t1 = True
>>> skullstrip.inputs.transform = "transforms/talairach_with_skull.lta"
>>> skullstrip.inputs.out_file = "brainmask.auto.mgz"
>>> 'mri_watershed -T1 transforms/talairach_with_skull.lta T1.mgz
>>> # skullstrip.help()
>> I do not see any segmented images generated in the given out_file
>> location. I suppose i am not doing this the right way. Pls point out what's
>> wrong in the above code.
>> Neuroimaging mailing list
>> Neuroimaging at python.org
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