.. AUTO-GENERATED FILE -- DO NOT EDIT!

nipype.interfaces.freesurfer.preprocess
=======================================


:class:`ApplyVolTransform`
--------------------------


Wraps command **mri_vol2vol**

Use FreeSurfer mri_vol2vol to apply a transform.

Examples
~~~~~~~~

>>> from nipype.interfaces.freesurfer import ApplyVolTransform
>>> applyreg = ApplyVolTransform()
>>> applyreg.inputs.source_file = 'structural.nii'
>>> applyreg.inputs.reg_file = 'register.dat'
>>> applyreg.inputs.transformed_file = 'struct_warped.nii'
>>> applyreg.inputs.fs_target = True
>>> applyreg.cmdline
'mri_vol2vol --fstarg --reg register.dat --mov structural.nii --o struct_warped.nii'

Inputs:: 

	[Mandatory]
	fs_target : (a boolean)
		use orig.mgz from subject in regfile as target
		exclusive: target_file,tal,fs_target
		requires: reg_file
	fsl_reg_file : (an existing file name)
		fslRAS-to-fslRAS matrix (FSL format)
		exclusive: reg_file,fsl_reg_file,xfm_reg_file,reg_header,subject
	reg_file : (an existing file name)
		tkRAS-to-tkRAS matrix   (tkregister2 format)
		exclusive: reg_file,fsl_reg_file,xfm_reg_file,reg_header,subject
	reg_header : (a boolean)
		ScannerRAS-to-ScannerRAS matrix = identity
		exclusive: reg_file,fsl_reg_file,xfm_reg_file,reg_header,subject
	source_file : (an existing file name)
		Input volume you wish to transform
	subject : (a string)
		set matrix = identity and use subject for any templates
		exclusive: reg_file,fsl_reg_file,xfm_reg_file,reg_header,subject
	tal : (a boolean)
		map to a sub FOV of MNI305 (with --reg only)
		exclusive: target_file,tal,fs_target
	target_file : (an existing file name)
		Output template volume
		exclusive: target_file,tal,fs_target
	xfm_reg_file : (an existing file name)
		ScannerRAS-to-ScannerRAS matrix (MNI format)
		exclusive: reg_file,fsl_reg_file,xfm_reg_file,reg_header,subject

	[Optional]
	args : (a string)
		Additional parameters to the command
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	interp : ('trilin' or 'nearest')
		Interpolation method (<trilin> or nearest)
	inverse : (a boolean)
		sample from target to source
	no_resample : (a boolean)
		Do not resample; just change vox2ras matrix
	subjects_dir : (an existing directory name)
		subjects directory
	transformed_file : (a file name)
		Output volume


Outputs:: 

	transformed_file : (an existing file name)
		Path to output file if used normally

:class:`BBRegister`
-------------------


Wraps command **bbregister**

Use FreeSurfer bbregister to register a volume to the Freesurfer anatomical.

This program performs within-subject, cross-modal registration using a
boundary-based cost function. The registration is constrained to be 6
DOF (rigid). It is required that you have an anatomical scan of the
subject that has already been recon-all-ed using freesurfer.

Examples
~~~~~~~~

>>> from nipype.interfaces.freesurfer import BBRegister
>>> bbreg = BBRegister(subject_id='me', source_file='structural.nii', init='header', contrast_type='t2')
>>> bbreg.cmdline
'bbregister --t2 --init-header --reg structural_bbreg_me.dat --mov structural.nii --s me'

Inputs:: 

	[Mandatory]
	contrast_type : ('t1' or 't2')
		contrast type of image
	init : ('spm' or 'fsl' or 'header')
		initialize registration spm, fsl, header
		exclusive: init_reg_file
	init_reg_file : (an existing file name)
		existing registration file
		exclusive: init
	source_file : (a file name)
		source file to be registered
	subject_id : (a string)
		freesurfer subject id

	[Optional]
	args : (a string)
		Additional parameters to the command
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	epi_mask : (a boolean)
		mask out B0 regions in stages 1 and 2
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	out_fsl_file : (a boolean or a file name)
		write the transformation matrix in FSL FLIRT format
	out_reg_file : (a file name)
		output registration file
	registered_file : (a boolean or a file name)
		output warped sourcefile either True or filename
	spm_nifti : (a boolean)
		force use of nifti rather than analyze with SPM
	subjects_dir : (an existing directory name)
		subjects directory


Outputs:: 

	min_cost_file : (an existing file name)
		Output registration minimum cost file
	out_fsl_file : (a file name)
		Output FLIRT-style registration file
	out_reg_file : (an existing file name)
		Output registration file
	registered_file : (a file name)
		Registered and resampled source file

:class:`DICOMConvert`
---------------------


Wraps command **mri_convert**

use fs mri_convert to convert dicom files

Examples
~~~~~~~~

>>> from nipype.interfaces.freesurfer import DICOMConvert
>>> cvt = DICOMConvert()
>>> cvt.inputs.dicom_dir = 'dicomdir'
>>> cvt.inputs.file_mapping = [('nifti','*.nii'),('info','dicom*.txt'),('dti','*dti.bv*')]

Inputs:: 

	[Mandatory]
	base_output_dir : (a directory name)
		directory in which subject directories are created
	dicom_dir : (an existing directory name)
		dicom directory from which to convert dicom files

	[Optional]
	args : (a string)
		Additional parameters to the command
	dicom_info : (an existing file name)
		File containing summary information from mri_parse_sdcmdir
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	file_mapping : (a list of items which are a tuple of the form: (a string, a string))
		defines the output fields of interface
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	ignore_single_slice : (a boolean)
		ignore volumes containing a single slice
		requires: dicom_info
	out_type : ('cor' or 'mgh' or 'mgz' or 'minc' or 'analyze' or 'analyze4d' or 'spm' or 'afni' or 'brik' or 'bshort' or 'bfloat' or 'sdt' or 'outline' or 'otl' or 'gdf' or 'nifti1' or 'nii' or 'niigz')
		defines the type of output file produced
	seq_list : (a list of items which are a string)
		list of pulse sequence names to be converted.
		requires: dicom_info
	subject_dir_template : (a string)
		template for subject directory name
	subject_id	subject identifier to insert into template
	subjects_dir : (an existing directory name)
		subjects directory



:class:`FitMSParams`
--------------------


Wraps command **mri_ms_fitparms**

Estimate tissue paramaters from a set of FLASH images.

Examples
~~~~~~~~
>>> from nipype.interfaces.freesurfer import FitMSParams
>>> msfit = FitMSParams()
>>> msfit.inputs.in_files = ['flash_05.mgz', 'flash_30.mgz']
>>> msfit.inputs.out_dir = 'flash_parameters'
>>> msfit.cmdline
'mri_ms_fitparms  flash_05.mgz flash_30.mgz flash_parameters'

Inputs:: 

	[Mandatory]
	in_files : (a list of items which are a file name)
		list of FLASH images (must be in mgh format)

	[Optional]
	args : (a string)
		Additional parameters to the command
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	flip_list : (a list of items which are an integer)
		list of flip angles of the input files
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	out_dir : (a directory name)
		directory to store output in
	subjects_dir : (an existing directory name)
		subjects directory
	te_list : (a list of items which are a float)
		list of TEs of the input files (in msec)
	tr_list : (a list of items which are an integer)
		list of TRs of the input files (in msec)
	xfm_list : (a list of items which are a file name)
		list of transform files to apply to each FLASH image


Outputs:: 

	pd_image : (an existing file name)
		image of estimated proton density values
	t1_image : (an existing file name)
		image of estimated T1 relaxation values
	t2star_image : (an existing file name)
		image of estimated T2* values

:class:`MRIConvert`
-------------------


Wraps command **mri_convert**

use fs mri_convert to manipulate files

.. note::
   Adds niigz as an output type option

Examples
~~~~~~~~

>>> mc = MRIConvert()
>>> mc.inputs.in_file = 'structural.nii'
>>> mc.inputs.out_file = 'outfile.mgz'
>>> mc.inputs.out_type = 'mgz'
>>> mc.cmdline
'mri_convert --out_type mgz --input_volume structural.nii --output_volume outfile.mgz'

Inputs:: 

	[Mandatory]
	in_file : (an existing file name)
		File to read/convert

	[Optional]
	apply_inv_transform : (an existing file name)
		apply inverse transformation xfm file
	apply_transform : (an existing file name)
		apply xfm file
	args : (a string)
		Additional parameters to the command
	ascii : (a boolean)
		save output as ascii col>row>slice>frame
	autoalign_matrix : (an existing file name)
		text file with autoalign matrix
	color_file : (an existing file name)
		color file
	conform : (a boolean)
		conform to 256^3
	conform_min : (a boolean)
		conform to smallest size
	conform_size : (a float)
		conform to size_in_mm
	crop_center : (a tuple of the form: (an integer, an integer, an integer))
		<x> <y> <z> crop to 256 around center (x,y,z)
	crop_gdf : (a boolean)
		apply GDF cropping
	crop_size : (a tuple of the form: (an integer, an integer, an integer))
		<dx> <dy> <dz> crop to size <dx, dy, dz>
	cut_ends : (an integer)
		remove ncut slices from the ends
	devolve_transform : (a string)
		subject id
	drop_n : (an integer)
		drop the last n frames
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	fill_parcellation : (a boolean)
		fill parcellation
	force_ras : (a boolean)
		use default when orientation info absent
	frame : (an integer)
		keep only 0-based frame number
	frame_subsample : (a tuple of the form: (an integer, an integer, an integer))
		start delta end : frame subsampling (end = -1 for end)
	fwhm : (a float)
		smooth input volume by fwhm mm
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	in_center : (a list of at most 3 items which are a float)
		<R coordinate> <A coordinate> <S coordinate>
	in_i_dir : (a tuple of the form: (a float, a float, a float))
		<R direction> <A direction> <S direction>
	in_i_size : (an integer)
		input i size
	in_info : (a boolean)
		display input info
	in_j_dir : (a tuple of the form: (a float, a float, a float))
		<R direction> <A direction> <S direction>
	in_j_size : (an integer)
		input j size
	in_k_dir : (a tuple of the form: (a float, a float, a float))
		<R direction> <A direction> <S direction>
	in_k_size : (an integer)
		input k size
	in_like : (an existing file name)
		input looks like
	in_matrix : (a boolean)
		display input matrix
	in_orientation : ('LAI' or 'LIA' or 'ALI' or 'AIL' or 'ILA' or 'IAL' or 'LAS' or 'LSA' or 'ALS' or 'ASL' or 'SLA' or 'SAL' or 'LPI' or 'LIP' or 'PLI' or 'PIL' or 'ILP' or 'IPL' or 'LPS' or 'LSP' or 'PLS' or 'PSL' or 'SLP' or 'SPL' or 'RAI' or 'RIA' or 'ARI' or 'AIR' or 'IRA' or 'IAR' or 'RAS' or 'RSA' or 'ARS' or 'ASR' or 'SRA' or 'SAR' or 'RPI' or 'RIP' or 'PRI' or 'PIR' or 'IRP' or 'IPR' or 'RPS' or 'RSP' or 'PRS' or 'PSR' or 'SRP' or 'SPR')
		specify the input orientation
	in_scale : (a float)
		input intensity scale factor
	in_stats : (a boolean)
		display input stats
	in_type : ('cor' or 'mgh' or 'mgz' or 'minc' or 'analyze' or 'analyze4d' or 'spm' or 'afni' or 'brik' or 'bshort' or 'bfloat' or 'sdt' or 'outline' or 'otl' or 'gdf' or 'nifti1' or 'nii' or 'niigz' or 'ge' or 'gelx' or 'lx' or 'ximg' or 'siemens' or 'dicom' or 'siemens_dicom')
		input file type
	invert_contrast : (a float)
		threshold for inversting contrast
	midframe : (a boolean)
		keep only the middle frame
	no_change : (a boolean)
		don't change type of input to that of template
	no_scale : (a boolean)
		dont rescale values for COR
	no_translate : (a boolean)
		???
	no_write : (a boolean)
		do not write output
	out_center : (a tuple of the form: (a float, a float, a float))
		<R coordinate> <A coordinate> <S coordinate>
	out_datatype : ('uchar' or 'short' or 'int' or 'float')
		Unknown
	out_file : (a file name)
		output filename or True to generate one
	out_i_count : (an integer)
		some count ?? in i direction
	out_i_dir : (a tuple of the form: (a float, a float, a float))
		<R direction> <A direction> <S direction>
	out_i_size : (an integer)
		output i size
	out_info : (a boolean)
		display output info
	out_j_count : (an integer)
		some count ?? in j direction
	out_j_dir : (a tuple of the form: (a float, a float, a float))
		<R direction> <A direction> <S direction>
	out_j_size : (an integer)
		output j size
	out_k_count : (an integer)
		some count ?? in k direction
	out_k_dir : (a tuple of the form: (a float, a float, a float))
		<R direction> <A direction> <S direction>
	out_k_size : (an integer)
		output k size
	out_matrix : (a boolean)
		display output matrix
	out_orientation : ('LAI' or 'LIA' or 'ALI' or 'AIL' or 'ILA' or 'IAL' or 'LAS' or 'LSA' or 'ALS' or 'ASL' or 'SLA' or 'SAL' or 'LPI' or 'LIP' or 'PLI' or 'PIL' or 'ILP' or 'IPL' or 'LPS' or 'LSP' or 'PLS' or 'PSL' or 'SLP' or 'SPL' or 'RAI' or 'RIA' or 'ARI' or 'AIR' or 'IRA' or 'IAR' or 'RAS' or 'RSA' or 'ARS' or 'ASR' or 'SRA' or 'SAR' or 'RPI' or 'RIP' or 'PRI' or 'PIR' or 'IRP' or 'IPR' or 'RPS' or 'RSP' or 'PRS' or 'PSR' or 'SRP' or 'SPR')
		specify the output orientation
	out_scale : (a float)
		output intensity scale factor
	out_stats : (a boolean)
		display output stats
	out_type : ('cor' or 'mgh' or 'mgz' or 'minc' or 'analyze' or 'analyze4d' or 'spm' or 'afni' or 'brik' or 'bshort' or 'bfloat' or 'sdt' or 'outline' or 'otl' or 'gdf' or 'nifti1' or 'nii' or 'niigz')
		output file type
	parse_only : (a boolean)
		parse input only
	read_only : (a boolean)
		read the input volume
	reorder : (a tuple of the form: (an integer, an integer, an integer))
		olddim1 olddim2 olddim3
	resample_type : ('interpolate' or 'weighted' or 'nearest' or 'sinc' or 'cubic')
		<interpolate|weighted|nearest|sinc|cubic> (default is interpolate)
	reslice_like : (an existing file name)
		reslice output to match file
	sdcm_list : (an existing file name)
		list of DICOM files for conversion
	skip_n : (an integer)
		skip the first n frames
	slice_bias : (a float)
		apply half-cosine bias field
	slice_crop : (a tuple of the form: (an integer, an integer))
		s_start s_end : keep slices s_start to s_end
	slice_reverse : (a boolean)
		reverse order of slices, update vox2ras
	smooth_parcellation : (a boolean)
		smooth parcellation
	sphinx : (a boolean)
		change orientation info to sphinx
	split : (a boolean)
		split output frames into separate output files.
	status_file : (a file name)
		status file for DICOM conversion
	subject_name : (a string)
		subject name ???
	subjects_dir : (an existing directory name)
		subjects directory
	template_info : (a boolean)
		dump info about template
	template_type : ('cor' or 'mgh' or 'mgz' or 'minc' or 'analyze' or 'analyze4d' or 'spm' or 'afni' or 'brik' or 'bshort' or 'bfloat' or 'sdt' or 'outline' or 'otl' or 'gdf' or 'nifti1' or 'nii' or 'niigz' or 'ge' or 'gelx' or 'lx' or 'ximg' or 'siemens' or 'dicom' or 'siemens_dicom')
		template file type
	unwarp_gradient : (a boolean)
		unwarp gradient nonlinearity
	vox_size : (a tuple of the form: (a float, a float, a float))
		<size_x> <size_y> <size_z> specify the size (mm) - useful for upsampling or downsampling
	zero_ge_z_offset : (a boolean)
		zero ge z offset ???
	zero_outlines : (a boolean)
		zero outlines


Outputs:: 

	out_file : (an existing file name)
		converted output file

:class:`ParseDICOMDir`
----------------------


Wraps command **mri_parse_sdcmdir**

Uses mri_parse_sdcmdir to get information from dicom directories

Examples
~~~~~~~~

>>> from nipype.interfaces.freesurfer import ParseDICOMDir
>>> dcminfo = ParseDICOMDir()
>>> dcminfo.inputs.dicom_dir = '.'
>>> dcminfo.inputs.sortbyrun = True
>>> dcminfo.inputs.summarize = True
>>> dcminfo.cmdline
'mri_parse_sdcmdir --d . --o dicominfo.txt --sortbyrun --summarize'

Inputs:: 

	[Mandatory]
	dicom_dir : (an existing directory name)
		path to siemens dicom directory

	[Optional]
	args : (a string)
		Additional parameters to the command
	dicom_info_file : (a file name)
		file to which results are written
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	sortbyrun : (a boolean)
		assign run numbers
	subjects_dir : (an existing directory name)
		subjects directory
	summarize : (a boolean)
		only print out info for run leaders


Outputs:: 

	dicom_info_file : (an existing file name)
		text file containing dicom information

:class:`ReconAll`
-----------------


Wraps command **recon-all**

Uses recon-all to generate surfaces and parcellations of structural data
from anatomical images of a subject.

Examples
~~~~~~~~

>>> from nipype.interfaces.freesurfer import ReconAll
>>> reconall = ReconAll()
>>> reconall.inputs.subject_id = 'foo'
>>> reconall.inputs.directive = 'all'
>>> reconall.inputs.subjects_dir = '.'
>>> reconall.inputs.T1_files = 'structural.nii'
>>> reconall.cmdline
'recon-all -i structural.nii -all -subjid foo -sd .'

Inputs:: 

	[Optional]
	T1_files : (an existing file name)
		name of T1 file to process
	args : (a string)
		Additional parameters to the command
	directive : ('all' or 'autorecon1' or 'autorecon2' or 'autorecon2-cp' or 'autorecon2-wm' or 'autorecon2-inflate1' or 'autorecon2-perhemi' or 'autorecon3' or 'localGI' or 'qcache')
		process directive
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	flags : (a string)
		additional parameters
	hemi : ('lh' or 'rh')
		hemisphere to process
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	subject_id : (a string)
		subject name
	subjects_dir : (an existing directory name)
		path to subjects directory


Outputs:: 

	T1 : (an existing file name)
		Intensity normalized whole-head volume
	annot : (an existing file name)
		Surface annotation files
	aparc_aseg : (an existing file name)
		Aparc parcellation projected into aseg volume
	aseg : (an existing file name)
		Volumetric map of regions from automatic segmentation
	brain : (an existing file name)
		Intensity normalized brain-only volume
	brainmask : (an existing file name)
		Skull-stripped (brain-only) volume
	curv : (an existing file name)
		Maps of surface curvature
	filled : (an existing file name)
		Subcortical mass volume
	inflated : (an existing file name)
		Inflated surface meshes
	label : (an existing file name)
		Volume and surface label files
	norm : (an existing file name)
		Normalized skull-stripped volume
	nu : (an existing file name)
		Non-uniformity corrected whole-head volume
	orig : (an existing file name)
		Base image conformed to Freesurfer space
	pial : (an existing file name)
		Gray matter/pia mater surface meshes
	rawavg : (an existing file name)
		Volume formed by averaging input images
	ribbon : (an existing file name)
		Volumetric maps of cortical ribbons
	smoothwm : (an existing file name)
		Smoothed original surface meshes
	sphere : (an existing file name)
		Spherical surface meshes
	sphere_reg : (an existing file name)
		Spherical registration file
	subject_id : (a string)
		Subject name for whom to retrieve data
	subjects_dir : (an existing directory name)
		Freesurfer subjects directory.
	sulc : (an existing file name)
		Surface maps of sulcal depth
	thickness : (an existing file name)
		Surface maps of cortical thickness
	volume : (an existing file name)
		Surface maps of cortical volume
	white : (an existing file name)
		White/gray matter surface meshes
	wm : (an existing file name)
		Segmented white-matter volume
	wmparc : (an existing file name)
		Aparc parcellation projected into subcortical white matter

:class:`Resample`
-----------------


Wraps command **mri_convert**

Use FreeSurfer mri_convert to up or down-sample image files

Examples
~~~~~~~~

>>> from nipype.interfaces import freesurfer
>>> resampler = freesurfer.Resample()
>>> resampler.inputs.in_file = 'structural.nii'
>>> resampler.inputs.resampled_file = 'resampled.nii'
>>> resampler.inputs.voxel_size = (2.1, 2.1, 2.1)
>>> resampler.cmdline
'mri_convert -vs 2.10 2.10 2.10 -i structural.nii -o resampled.nii'

Inputs:: 

	[Mandatory]
	in_file : (an existing file name)
		file to resample
	voxel_size : (a tuple of the form: (a float, a float, a float))
		triplet of output voxel sizes

	[Optional]
	args : (a string)
		Additional parameters to the command
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	resampled_file : (a file name)
		output filename
	subjects_dir : (an existing directory name)
		subjects directory


Outputs:: 

	resampled_file : (an existing file name)
		output filename

:class:`RobustRegister`
-----------------------


Wraps command **mri_robust_register**

Perform intramodal linear registration (translation and rotation) using robust statistics.

Examples
~~~~~~~~
>>> from nipype.interfaces.freesurfer import RobustRegister
>>> reg = RobustRegister()
>>> reg.inputs.source_file = 'structural.nii'
>>> reg.inputs.target_file = 'T1.nii'
>>> reg.inputs.auto_sens = True
>>> reg.inputs.init_orient = True
>>> reg.cmdline
'mri_robust_register --satit --initorient --lta structural_robustreg.lta --mov structural.nii --dst T1.nii'

References
~~~~~~~~~~
Reuter, M, Rosas, HD, and Fischl, B, (2010). Highly Accurate Inverse Consistent Registration:
A Robust Approach.  Neuroimage 53(4) 1181-96.

Inputs:: 

	[Mandatory]
	auto_sens : (a boolean)
		auto-detect good sensitivity
		exclusive: outlier_sens
	outlier_sens : (a float)
		set outlier sensitivity explicitly
		exclusive: auto_sens
	source_file : (a file name)
		volume to be registered
	target_file : (a file name)
		target volume for the registration

	[Optional]
	args : (a string)
		Additional parameters to the command
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	est_int_scale : (a boolean)
		estimate intensity scale (recommended for unnormalized images)
	force_double : (a boolean)
		use double-precision intensities
	force_float : (a boolean)
		use float intensities
	half_source : (a boolean or a file name)
		write source volume mapped to halfway space
	half_source_xfm : (a boolean or a file name)
		write transform from source to halfway space
	half_targ : (a boolean or a file name)
		write target volume mapped to halfway space
	half_targ_xfm : (a boolean or a file name)
		write transform from target to halfway space
	half_weights : (a boolean or a file name)
		write weights volume mapped to halfway space
	high_iterations : (an integer)
		max # of times on highest resolution
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	in_xfm_file : (an existing file name)
		use initial transform on source
	init_orient : (a boolean)
		use moments for initial orient (recommended for stripped brains)
	iteration_thresh : (a float)
		stop iterations when below threshold
	least_squares : (a boolean)
		use least squares instead of robust estimator
	mask_source : (an existing file name)
		image to mask source volume with
	mask_target : (an existing file name)
		image to mask target volume with
	max_iterations : (an integer)
		maximum # of times on each resolution
	no_init : (a boolean)
		skip transform init
	no_multi : (a boolean)
		work on highest resolution
	out_reg_file : (a file name)
		registration file to write
	outlier_limit : (a float)
		set maximal outlier limit in satit
	registered_file : (a boolean or a file name)
		registered image; either True or filename
	subjects_dir : (an existing directory name)
		subjects directory
	subsample_thresh : (an integer)
		subsample if dimension is above threshold size
	trans_only : (a boolean)
		find 3 parameter translation only
	weights_file : (a boolean or a file name)
		weights image to write; either True or filename
	write_vo2vox : (a boolean)
		output vox2vox matrix (default is RAS2RAS)


Outputs:: 

	half_source : (a file name)
		source image mapped to halfway space
	half_source_xfm : (a file name)
		transform file to map source image to halfway space
	half_targ : (a file name)
		target image mapped to halfway space
	half_targ_xfm : (a file name)
		transform file to map target image to halfway space
	half_weights : (a file name)
		weights image mapped to halfway space
	out_reg_file : (an existing file name)
		output registration file
	registered_file : (a file name)
		output image with registration applied
	weights_file : (a file name)
		image of weights used

:class:`Smooth`
---------------


Wraps command **mris_volsmooth**

Use FreeSurfer mris_volsmooth to smooth a volume

This function smoothes cortical regions on a surface and non-cortical
regions in volume.

.. note::
   Cortical voxels are mapped to the surface (3D->2D) and then the
   smoothed values from the surface are put back into the volume to fill
   the cortical ribbon. If data is smoothed with this algorithm, one has to
   be careful about how further processing is interpreted.

Examples
~~~~~~~~

>>> from nipype.interfaces.freesurfer import Smooth
>>> smoothvol = Smooth(in_file='functional.nii', smoothed_file = 'foo_out.nii', reg_file='register.dat', surface_fwhm=10, vol_fwhm=6)
>>> smoothvol.cmdline
'mris_volsmooth --i functional.nii --reg register.dat --o foo_out.nii --fwhm 10 --vol-fwhm 6'

Inputs:: 

	[Mandatory]
	in_file : (an existing file name)
		source volume
	num_iters : (an integer)
		number of iterations instead of fwhm
		exclusive: surface_fwhm
	reg_file : (an existing file name)
		registers volume to surface anatomical 
	surface_fwhm : (a float)
		surface FWHM in mm
		exclusive: num_iters
		requires: reg_file

	[Optional]
	args : (a string)
		Additional parameters to the command
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	proj_frac : (a float)
		project frac of thickness a long surface normal
		exclusive: proj_frac_avg
	proj_frac_avg : (a tuple of the form: (a float, a float, a float))
		average a long normal min max delta
		exclusive: proj_frac
	smoothed_file : (a file name)
		output volume
	subjects_dir : (an existing directory name)
		subjects directory
	vol_fwhm : (a float)
		volumesmoothing outside of surface


Outputs:: 

	smoothed_file : (a file name)
		smoothed input volume

:class:`SynthesizeFLASH`
------------------------


Wraps command **mri_synthesize**

Synthesize a FLASH acquisition from T1 and proton density maps.

Examples
~~~~~~~~
>>> from nipype.interfaces.freesurfer import SynthesizeFLASH
>>> syn = SynthesizeFLASH(tr=20, te=3, flip_angle=30)
>>> syn.inputs.t1_image = 'T1.mgz'
>>> syn.inputs.pd_image = 'PD.mgz'
>>> syn.inputs.out_file = 'flash_30syn.mgz'
>>> syn.cmdline
'mri_synthesize 20.00 30.00 3.000 T1.mgz PD.mgz flash_30syn.mgz'

Inputs:: 

	[Mandatory]
	flip_angle : (a float)
		flip angle (in degrees)
	pd_image : (an existing file name)
		image of proton density values
	t1_image : (an existing file name)
		image of T1 values
	te : (a float)
		echo time (in msec)
	tr : (a float)
		repetition time (in msec)

	[Optional]
	args : (a string)
		Additional parameters to the command
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	fixed_weighting : (a boolean)
		use a fixed weighting to generate optimal gray/white contrast
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	out_file : (a file name)
		image to write
	subjects_dir : (an existing directory name)
		subjects directory


Outputs:: 

	out_file : (an existing file name)
		synthesized FLASH acquisition

:class:`UnpackSDICOMDir`
------------------------


Wraps command **unpacksdcmdir**

Use unpacksdcmdir to convert dicom files

Call unpacksdcmdir -help from the command line to see more information on
using this command.

Examples
~~~~~~~~

>>> from nipype.interfaces.freesurfer import UnpackSDICOMDir
>>> unpack = UnpackSDICOMDir()
>>> unpack.inputs.source_dir = '.'
>>> unpack.inputs.output_dir = '.'
>>> unpack.inputs.run_info = (5, 'mprage', 'nii', 'struct')
>>> unpack.inputs.dir_structure = 'generic'
>>> unpack.cmdline
'unpacksdcmdir -generic -targ . -run 5 mprage nii struct -src .'

Inputs:: 

	[Mandatory]
	config : (an existing file name)
		specify unpacking rules in file
		exclusive: run_info,config,seq_config
	run_info : (a tuple of the form: (an integer, a string, a string, a string))
		runno subdir format name : spec unpacking rules on cmdline
		exclusive: run_info,config,seq_config
	seq_config : (an existing file name)
		specify unpacking rules based on sequence
		exclusive: run_info,config,seq_config
	source_dir : (an existing directory name)
		directory with the DICOM files

	[Optional]
	args : (a string)
		Additional parameters to the command
	dir_structure : ('fsfast' or 'generic')
		unpack to specified directory structures
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	log_file : (an existing file name)
		explicilty set log file
	no_info_dump : (a boolean)
		do not create infodump file
	no_unpack_err : (a boolean)
		do not try to unpack runs with errors
	output_dir : (a directory name)
		top directory into which the files will be unpacked
	scan_only : (an existing file name)
		only scan the directory and put result in file
	spm_zeropad : (an integer)
		set frame number zero padding width for SPM
	subjects_dir : (an existing directory name)
		subjects directory


