3 dh@shdZddlmZmZmZmZddlmZddlmZGdddeZ Gdd d eZ Gd d d eZ d S) zJ The ASL module of niftyfit, which wraps the fitting methods in NiftyFit. )File TraitedSpectraitsCommandLineInputSpec)NiftyFitCommand)get_custom_pathc@sxeZdZdZdZeddddedZejddd Z ejd d d Z d Zed gddedZ ed gddddZ ed gddddZ dZeddedZdZeddedZdZeddedZdZeddedZd Zedd!edZed"dd#d$d%Zejd&d'd Zd(Zejed)d Zd*Zejed+d Zd,Zejed-d Zejd.d/d Zejd0d1d Zd2Zejed3d Zejd4d5d Zejd6d7d Zd8Zejed9d Zejd:d;d Zejdd?d Z!ejd@dAd Z"ejdBdCd Z#ejdDdEd Z$dFZeddGedZ%dHZejedId Z&dJZej'edKd Z(ej'dLdMd Z)ej*ej'ej'ej'dNdOd Z+dPZejedQd Z,ejdRdId Z-dSZejedTd Z.ejdUdVd Z/dWS)XFitAslInputSpeczInput Spec for FitAsl.z@Filename of the 4D ASL (control/label) source image (mandatory).rTz -source %s)positionexistsargstr mandatorydesczFit PASL ASL data [default]z-pasl)rr zFit PCASL ASL dataz-pcaslz9Filename of the Cerebral Blood Flow map (in ml/100g/min). source_filez %s_cbf.nii.gzz-cbf %s)Z name_sourceZ name_templater rz%s_error.nii.gzz -error %szFilename of the CBF error map.z %s_syn.nii.gzz-syn %sz#Filename of the synthetic ASL data.z/Filename of the estimated input T1 map (in ms).z -t1map %s)r r rz'Filename of the estimated input M0 map.z -m0map %sz-Filename of the estimated input M0 map error.z -m0mape %szXFilename of a [1,2,5]s Inversion Recovery volume (T1/M0 fitting carried out internally).z -IRvolume %sz.Output of [1,2,5]s Inversion Recovery fitting.z -IRoutput %srzFilename of image mask.z-mask %s)r r rr z"T1 of arterial component [1650ms].z-T1a %fz5Single plasma/tissue partition coefficient [0.9ml/g].z-L %fzoLabelling efficiency [0.99 (pasl), 0.85 (pcasl)], ensure any background suppression pulses are included in -effz-eff %fzROutlier rejection for multi CL volumes (enter z-score threshold (e.g. 2.5)) [off].z-out %fzPost Labelling Delay [2000ms].z-PLD %fzLabelling Duration [1800ms].z-LDD %fz6Difference in labelling delay per slice [0.0 ms/slice.z-dPLD %fzSaturation pulse time [800ms].z -Tinv1 %fzInversion time [2000ms].z -Tinv2 %fz3Difference in inversion time per slice [0ms/slice].z -dTinv2 %fzT1 of GM [1150ms].z-gmT1 %fz%Plasma/GM water partition [0.95ml/g].z-gmL %fzTime to GM [ATT+0ms].z -gmTTT %fzT1 of WM [800ms].z-wmT1 %fz%Plasma/WM water partition [0.82ml/g].z-wmL %fzTime to WM [ATT+0ms].z -wmTTT %fzaFilename of the 4D segmentation (in ASL space) for L/T1 estimation and PV correction {WM,GM,CSF}.z-seg %sz7Use sigmoid to estimate L from T1: L(T1|gmL,wmL) [Off].z-sigzFSimple PV correction (CBF=vg*CBFg + vw*CBFw, with CBFw=f*CBFg) [0.25].z-pv0 %dzIn plane PV kernel size [3x3].z-pv2 %dz3D kernel size [3x3x1].z -pv3 %d %d %dzAMultiply CBF by this value (e.g. if CL are mislabelled use -1.0).z-mul %fz#Multiply CBF by segmentation [Off].z/Set PV threshold for switching off LSQR [O.05].z -pvthresholdzSet CBF as [gm,wm] not [wm,gm].z -segstyleN)0__name__ __module__ __qualname____doc__rrrrZBoolZpaslZpcaslcbf_file error_filesyn_fileZt1mapZm0mapZm0mapeZ ir_volumeZ ir_outputmaskZFloatZ t1_art_cmpZ plasma_coeffZeffoutZpldZlddZdpldZt_inv1Zt_inv2Zdt_inv2Zgm_t1Z gm_plasmaZgm_tttZwm_t1Z wm_plasmaZwm_tttsegsigZIntZpv0Zpv2TupleZpv3mulZmulgmZ pv_thresholdZsegstylerr@/tmp/pip-build-7vycvbft/nipype/nipype/interfaces/niftyfit/asl.pyr s   r c@s@eZdZdZdZededZdZededZdZededZdS)FitAslOutputSpeczOutput Spec for FitAsl.z9Filename of the Cerebral Blood Flow map (in ml/100g/min).T)r rzFilename of the CBF error map.z#Filename of the synthetic ASL data.N) rrrrrrrrrrrrrrs  rc@s(eZdZdZedddZeZeZ dZ dS)FitAslaKInterface for executable fit_asl from Niftyfit platform. Use NiftyFit to perform ASL fitting. ASL fitting routines (following EU Cost Action White Paper recommendations) Fits Cerebral Blood Flow maps in the first instance. `Source code `_ Examples -------- >>> from nipype.interfaces import niftyfit >>> node = niftyfit.FitAsl() >>> node.inputs.source_file = 'asl.nii.gz' >>> node.cmdline 'fit_asl -source asl.nii.gz -cbf asl_cbf.nii.gz -error asl_error.nii.gz -syn asl_syn.nii.gz' Zfit_aslZ NIFTYFITDIR)Zenv_dirZ_fit_aslN) rrrrrZ_cmdr Z input_specrZ output_spec_suffixrrrrr s  r N) rbaserrrrrZ niftyreg.baserr rr rrrrs   w