3 dG@s@dZddlmZmZmZmZmZddlmZm Z ddlm Z m Z ddl Z d Z Gd d d eZGd d d eZGddde ZGdddeZGdddeZGdddeZGddde ZGdddeZGdddeZGddde ZGdddeZGd d!d!eZGd"d#d#e ZGd$d%d%eZGd&d'd'eZGd(d)d)e ZGd*d+d+eZGd,d-d-eZGd.d/d/e Z Gd0d1d1eZ!Gd2d3d3eZ"Gd4d5d5e Z#Gd6d7d7e eZ$Gd8d9d9e eZ%Gd:d;d;e eZ&Gdd?d?e eZ(Gd@dAdAe eZ)GdBdCdCe e#Z*GdDdEdEe e Z+dS)FamDTITK registration interfaces DTI-TK developed by Gary Hui Zhang, gary.zhang@ucl.ac.uk For additional help, visit http://dti-tk.sf.net The high-dimensional tensor-based DTI registration algorithm Zhang, H., Avants, B.B, Yushkevich, P.A., Woo, J.H., Wang, S., McCluskey, L.H., Elman, L.B., Melhem, E.R., Gee, J.C., High-dimensional spatial normalization of diffusion tensor images improves the detection of white matter differences in amyotrophic lateral sclerosis, IEEE Transactions on Medical Imaging, 26(11):1585-1597, November 2007. PMID: 18041273. The original piecewise-affine tensor-based DTI registration algorithm at the core of DTI-TK Zhang, H., Yushkevich, P.A., Alexander, D.C., Gee, J.C., Deformable registration of diffusion tensor MR images with explicit orientation optimization, Medical Image Analysis, 10(5):764-785, October 2006. PMID: 16899392. ) TraitedSpecCommandLineInputSpectraitsFile isdefined)fname_presuffixsplit_filename)CommandLineDtitkDTITKRenameMixinNZrestructuredtextc @seZdZedddddddZedddddddZejd d d d dd dddd Zej dddddddZ ej dddddddZ eddddddZ dS)RigidInputSpeczfixed tensor volumeTr z%sF)descexists mandatorypositionargstrcopyfilezmoving tensor volumer ZEDSZGDSZDDSZNMIrzsimilarity metric)rrrr usedefaultrz%g %g %gz%dist between samp points (mm) (x,y,z))rrrrrz%gzcost function toleranceg{Gz?)rrrr default_valuerzInitialize w/DTITK-FORMATaffine)rrrrrN)rrr)__name__ __module__ __qualname__r fixed_file moving_filerEnumZsimilarity_metricTupleZ sampling_xyzFloatftolZinitialize_xfmr"r"F/tmp/pip-build-7vycvbft/nipype/nipype/interfaces/dtitk/registration.pyr#sXrc@s eZdZeddZeddZdS)RigidOutputSpecT)rN)rrrrout_file out_file_xfmr"r"r"r#r$Xs r$cs4eZdZdZeZeZdZfddZ ddZ Z S)RigidaPerforms rigid registration between two tensor volumes Example ------- >>> from nipype.interfaces import dtitk >>> node = dtitk.Rigid() >>> node.inputs.fixed_file = 'im1.nii' >>> node.inputs.moving_file = 'im2.nii' >>> node.inputs.similarity_metric = 'EDS' >>> node.inputs.sampling_xyz = (4,4,4) >>> node.inputs.ftol = 0.01 >>> node.cmdline 'dti_rigid_reg im1.nii im2.nii EDS 4 4 4 0.01' >>> node.run() # doctest: +SKIP Z dti_rigid_regcs(tt|j|}d|jkr$|j||S)Nz%.aff doesn't exist or can't be opened)superr'_run_interfacestderrZraise_exception)selfZruntime) __class__r"r#r)xs  zRigid._run_interfacecCs:|jj}|jj}t|ddd|d<t|dd|d<|S)Nz.affF)suffixuse_extr&Z_aff)r-r%) output_specgetinputsrr)r+outputsmovingr"r"r# _list_outputs~s  zRigid._list_outputs) rrr__doc__r input_specr$r/_cmdr)r4 __classcell__r"r")r,r#r']s  r'c@seZdZdZdZdS)Affinea Performs affine registration between two tensor volumes Example ------- >>> from nipype.interfaces import dtitk >>> node = dtitk.Affine() >>> node.inputs.fixed_file = 'im1.nii' >>> node.inputs.moving_file = 'im2.nii' >>> node.inputs.similarity_metric = 'EDS' >>> node.inputs.sampling_xyz = (4,4,4) >>> node.inputs.ftol = 0.01 >>> node.inputs.initialize_xfm = 'im_affine.aff' >>> node.cmdline 'dti_affine_reg im1.nii im2.nii EDS 4 4 4 0.01 im_affine.aff' >>> node.run() # doctest: +SKIP Zdti_affine_regN)rrrr5r7r"r"r"r#r9sr9c@seZdZedddddZedddddd Zed dd ddZejdd ddd ddZ ej dddddddZ ej dddddddZ dS)DiffeoInputSpeczfixed tensor volumeTr z%s)rrrrzmoving tensor volumer F)rrrrrmaskrz!legacy parameter; always set to 1rz%d)rrrrrznumber of iterationsr)rrrrrgMb`?z&iteration for the optimization to stoprz%gN)rrrrrrZ mask_filerrlegacyIntZn_itersr r!r"r"r"r#r:s:r:c@s eZdZeddZeddZdS)DiffeoOutputSpecT)rN)rrrrr%r&r"r"r"r#r?s r?c@s$eZdZdZeZeZdZddZ dS)DiffeoaPerforms diffeomorphic registration between two tensor volumes Example ------- >>> from nipype.interfaces import dtitk >>> node = dtitk.Diffeo() >>> node.inputs.fixed_file = 'im1.nii' >>> node.inputs.moving_file = 'im2.nii' >>> node.inputs.mask_file = 'mask.nii' >>> node.inputs.legacy = 1 >>> node.inputs.n_iters = 6 >>> node.inputs.ftol = 0.002 >>> node.cmdline 'dti_diffeomorphic_reg im1.nii im2.nii mask.nii 1 6 0.002' >>> node.run() # doctest: +SKIP Zdti_diffeomorphic_regcCs8|jj}|jj}t|dd|d<t|dd|d<|S)Nz _diffeo.df)r-r&Z_diffeor%)r/r0r1rr)r+r2r3r"r"r#r4s  zDiffeo._list_outputsN) rrrr5r:r6r?r/r7r4r"r"r"r#r@s r@c@s:eZdZedddddZedddddZedddd Zd S) ComposeXfmInputSpeczdiffeomorphic warp fileTz-df %s)rrrrzaffine transform filez-aff %sz output pathz-out %s)rrZgenfileN)rrrrin_dfZin_affr%r"r"r"r#rAs rAc@seZdZeddZdS)ComposeXfmOutputSpecT)rN)rrrrr%r"r"r"r#rCsrCc@s,eZdZdZeZeZdZddZ ddZ dS) ComposeXfma Combines diffeomorphic and affine transforms Example ------- >>> from nipype.interfaces import dtitk >>> node = dtitk.ComposeXfm() >>> node.inputs.in_df = 'im_warp.df.nii' >>> node.inputs.in_aff= 'im_affine.aff' >>> node.cmdline 'dfRightComposeAffine -aff im_affine.aff -df im_warp.df.nii -out im_warp_affdf.df.nii' >>> node.run() # doctest: +SKIP ZdfRightComposeAffinecCs:|jj}|jj}t|s&|jd}tjj||d<|S)Nr%) Z_outputsr0r1r%r _gen_filenameospathabspath)r+r2r%r"r"r#r4s   zComposeXfm._list_outputscCsR|dkr dSt|jj\}}}d}|jdr@|d7}|dd}t|||ddS)Nr%Z_affdfz.dfrF)r-r.)r r1rBendswithr)r+namerGbaseextr-r"r"r#rEs  zComposeXfm._gen_filenameN) rrrr5rAr6rCr/r7r4rEr"r"r"r#rDs rDc@seZdZedddddZedddddd Zedd d d d dgddZejddddddZ ejdddddddZ edddgddZ ej ej ej ej fdd dgd!Zej ej ej ej fd"dgd#d$Zej ej fd%d&dgd'd$Zd(S))AffSymTensor3DVolInputSpeczmoving tensor volumeTz-in %s)rrrrzoutput filenamez-out %sin_filez %s_affxfmd)rr name_source name_templatekeep_extensionz -trans %starget translationeuler deformationzZtransform to apply: specify an input transformation file; parameters input will be ignored)rrxorrLEIEIz -interp %sz%Log Euclidean/Euclidean Interpolation)rrrPPDNOFSz -reorient %sz_Reorientation strategy: preservation of principal direction, no reorientation, or finite strain)rrrz -target %s transformzDoutput volume specification read from the target volume if specifiedztranslation (x,y,z) in mmz-translation %g %g %g)rrrWz(theta, phi, psi) in degreesz-euler %g %g %g)rrWrr<z(xx,yy,zz,xy,yz,xz)z-deformation %g %g %g %g %g %gN)rrrrrOr%r]rr interpolationreorientrSrr rTrUrVr"r"r"r#rNs\   rNc@seZdZeddZdS)AffSymTensor3DVolOutputSpecT)rN)rrrrr%r"r"r"r#r`Wsr`c@seZdZdZeZeZdZdS)AffSymTensor3DVola Applies affine transform to a tensor volume Example ------- >>> from nipype.interfaces import dtitk >>> node = dtitk.AffSymTensor3DVol() >>> node.inputs.in_file = 'im1.nii' >>> node.inputs.transform = 'im_affine.aff' >>> node.cmdline 'affineSymTensor3DVolume -in im1.nii -interp LEI -out im1_affxfmd.nii -reorient PPD -trans im_affine.aff' >>> node.run() # doctest: +SKIP ZaffineSymTensor3DVolumeN) rrrr5rNr6r`r/r7r"r"r"r#ra[srac@seZdZedddddZedddddd Zedd d d d dgddZejddddddZ edddgddZ ej ej ej ej fdddgdZ ej ej ej ej fddgddZej ej fdd dgd!dZd"S)#AffScalarVolInputSpeczmoving scalar volumeTz-in %s)rrrrzoutput filenamez-out %srOz %s_affxfmd)rrrPrQrRz -trans %srSrTrUrVzZtransform to apply: specify an input transformation file; parameters input will be ignored)rrrWr trilinearNNz -interp %sz+trilinear or nearest neighbor interpolation)rrrz -target %sr]zDoutput volume specification read from the target volume if specifiedztranslation (x,y,z) in mmz-translation %g %g %g)rrrWz(theta, phi, psi) in degreesz-euler %g %g %g)rrWrr<z(xx,yy,zz,xy,yz,xz)z-deformation %g %g %g %g %g %gN)rrrrrOr%r]rrr^rSrr rTrUrVr"r"r"r#rbqsN   rbc@seZdZedddZdS)AffScalarVolOutputSpecz moved volumeT)rrN)rrrrr%r"r"r"r#resrecs,eZdZdZeZeZdZfddZ Z S) AffScalarVola Applies affine transform to a scalar volume Example ------- >>> from nipype.interfaces import dtitk >>> node = dtitk.AffScalarVol() >>> node.inputs.in_file = 'im1.nii' >>> node.inputs.transform = 'im_affine.aff' >>> node.cmdline 'affineScalarVolume -in im1.nii -interp 0 -out im1_affxfmd.nii -trans im_affine.aff' >>> node.run() # doctest: +SKIP ZaffineScalarVolumecs*|dkrddd|}tt|j|||S)Nr^r r )rcrd)r(rf _format_arg)r+rKspecvalue)r,r"r#rgszAffScalarVol._format_arg) rrrr5rbr6rer/r7rgr8r"r")r,r#rfs rfc@seZdZedddddZedddddd Zedd dd d Zejd dddZ ej ddddddZ ej ddddddZ edddgddZ ejejejejfddd gd!Zejejejejfd"d#Zej d$d%d&d'd(Zd)S)*DiffeoSymTensor3DVolInputSpeczmoving tensor volumeTz-in %s)rrrrzoutput filenamez-out %srOz %s_diffeoxfmd)rrrPrQrRz -trans %sztransform to apply)rrrrZFDz-df %s)rrrXrYz -interp %sz%Log Euclidean/Euclidean Interpolation)rrrrZr\z -reorient %szLReorientation strategy: preservation of principal direction or finite strain)rrrz -target %s voxel_sizezDoutput volume specification read from the target volume if specified)rrrWrz%xyz voxel size (superseded by target)z-vsize %g %g %grS)rrrWz-flip %d %d %d)rbackwardforwardz"use backward or forward resamplingz-type %s)rrN)rrrrrOr%r]rStrZdfrr^r_rSrr rkr>flipresampling_typer"r"r"r#rjsP rjc@seZdZeddZdS)DiffeoSymTensor3DVolOutputSpecT)rN)rrrrr%r"r"r"r#rqsrqcs,eZdZdZeZeZdZfddZ Z S)DiffeoSymTensor3DVola Applies diffeomorphic transform to a tensor volume Example ------- >>> from nipype.interfaces import dtitk >>> node = dtitk.DiffeoSymTensor3DVol() >>> node.inputs.in_file = 'im1.nii' >>> node.inputs.transform = 'im_warp.df.nii' >>> node.cmdline 'deformationSymTensor3DVolume -df FD -in im1.nii -interp LEI -out im1_diffeoxfmd.nii -reorient PPD -trans im_warp.df.nii' >>> node.run() # doctest: +SKIP ZdeformationSymTensor3DVolumecs*|dkrddd|}tt|j|||S)Nrpr r )rmrl)r(rrrg)r+rKrhri)r,r"r#rgsz DiffeoSymTensor3DVol._format_arg) rrrr5rjr6rqr/r7rgr8r"r")r,r#rrs rrc@seZdZedddddZedddddd Zedd dd d Zedd dgddZej ej ej ej fdddgdZ ej ej ej ej fddZ ejdddddZejdddddd Zd!S)"DiffeoScalarVolInputSpeczmoving scalar volumeTz-in %s)rrrrzoutput filenamez-out %srOz %s_diffeoxfmd)rrrPrQrRz -trans %sztransform to apply)rrrrz -target %srkzDoutput volume specification read from the target volume if specified)rrrWrz%xyz voxel size (superseded by target)z-vsize %g %g %grS)rrrWz-flip %d %d %d)rrlrmz"use backward or forward resamplingz-type %s)rrrcrdztrilinear, or nearest neighborz -interp %s)rrrN)rrrrrOr%r]rSrrr rkr>rorrpr^r"r"r"r#rssB rsc@seZdZedddZdS)DiffeoScalarVolOutputSpecz moved volumeT)rrN)rrrrr%r"r"r"r#rtDsrtcs,eZdZdZeZeZdZfddZ Z S)DiffeoScalarVola Applies diffeomorphic transform to a scalar volume Example ------- >>> from nipype.interfaces import dtitk >>> node = dtitk.DiffeoScalarVol() >>> node.inputs.in_file = 'im1.nii' >>> node.inputs.transform = 'im_warp.df.nii' >>> node.cmdline 'deformationScalarVolume -in im1.nii -interp 0 -out im1_diffeoxfmd.nii -trans im_warp.df.nii' >>> node.run() # doctest: +SKIP ZdeformationScalarVolumecsB|dkrddd|}n|dkr.ddd|}tt|j|||S)Nrpr r )rmrlr^)rcrd)r(rurg)r+rKrhri)r,r"r#rg]s zDiffeoScalarVol._format_arg) rrrr5rsr6rtr/r7rgr8r"r")r,r#ruHs ruc@s eZdZdS) RigidTaskN)rrrr"r"r"r#rvesrvc@s eZdZdS) AffineTaskN)rrrr"r"r"r#rwisrwc@s eZdZdS) DiffeoTaskN)rrrr"r"r"r#rxmsrxc@s eZdZdS)ComposeXfmTaskN)rrrr"r"r"r#ryqsryc@s eZdZdS)affScalarVolTaskN)rrrr"r"r"r#rzusrzc@s eZdZdS)affSymTensor3DVolTaskN)rrrr"r"r"r#r{ysr{c@s eZdZdS)diffeoScalarVolTaskN)rrrr"r"r"r#r|}sr|c@s eZdZdS)diffeoSymTensor3DVolTaskN)rrrr"r"r"r#r}sr}),r5rLrrrrrZutils.filemaniprr r r rFZ __docformat__rr$r'r9r:r?r@rArCrDrNr`rarbrerfrjrqrrrsrtrurvrwrxryrzr{r|r}r"r"r"r#sF5)$ (=36,