3 dk@stddlZddlmZddlmZmZmZmZmZm Z ddl m Z GdddeZ GdddeZ Gd d d eZdS) N)Path) TraitedSpecCommandLineInputSpec CommandLineFiletraits isdefined)split_filenamec @s^eZdZeddddddZeddddd d gdd Zed d dddd gdd ZejddddZ dS)RobexInputSpecz Input volumeTrz%s)descexists mandatorypositionargstrz Output volumeFz%s_brainin_file)r rrZ hash_filesZ name_templateZ name_sourceZkeep_extensionz Output maskz %s_brainmaskz Seed for random number generatorz%i)r rrN) __name__ __module__ __qualname__rrout_fileout_maskrZIntseedrrD/tmp/pip-build-7vycvbft/nipype/nipype/interfaces/robex/preprocess.pyr s&r c@s eZdZeddZeddZdS)RobexOutputSpecz Output volume)r z Output maskN)rrrrrrrrrrr(s rc@seZdZdZeZeZdZdS) RobexSegmenta ROBEX is an automatic whole-brain extraction tool for T1-weighted MRI data (commonly known as skull stripping). ROBEX aims for robust skull-stripping across datasets with no parameter settings. It fits a triangular mesh, constrained by a shape model, to the probabilistic output of a supervised brain boundary classifier. Because the shape model cannot perfectly accommodate unseen cases, a small free deformation is subsequently allowed. The deformation is optimized using graph cuts. The method ROBEX is based on was published in IEEE Transactions on Medical Imaging; please visit the website http://www.jeiglesias.com to download the paper. Examples -------- >>> from nipype.interfaces.robex.preprocess import RobexSegment >>> robex = RobexSegment() >>> robex.inputs.in_file = 'structural.nii' >>> robex.cmdline 'runROBEX.sh structural.nii structural_brain.nii structural_brainmask.nii' >>> robex.run() # doctest: +SKIP z runROBEX.shN) rrr__doc__r Z input_specrZ output_specZ_cmdrrrrr-sr)osZpathlibrZnipype.interfaces.baserrrrrrZnipype.utils.filemanipr r rrrrrrs