FSL¶

Module contents¶

Input and output specification dicationaries for FSL analyses.

Submodules¶

django_mri.analysis.specifications.fsl.apply_topup module¶

Input and output specification dictionaries for FSL’s applytopup script.

django_mri.analysis.specifications.fsl.bet module¶

Input and output specification dictionaries for FSL’s BET_ script.

django_mri.analysis.specifications.fsl.binary_maths module¶

Input and output specification dictionaries for nipype’s BinaryMaths interface, wrapping FSL’s fslmaths.

django_mri.analysis.specifications.fsl.binary_maths.BINARY_MATHS_INPUT_SPECIFICATION = {'in_file': {'description': 'Path to image to operate on.', 'is_configuration': False, 'required': True, 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>, 'value_attribute': 'path.__str__'}, 'internal_datatype': {'choices': ['float', 'char', 'int', 'short', 'double', 'input'], 'default': 'float', 'description': 'Datatype to use for calculations.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'nan2zero': {'description': 'Change NaNs to zeros before doing anything.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'operand_file': {'description': 'Path to second image to perform operation with. Mutually exclusive with inputs: operand_value.', 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>}, 'operand_value': {'description': 'Value to perform operation with.', 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'operation': {'choices': ['add', 'sub', 'mul', 'div', 'rem', 'max', 'min'], 'description': 'Operation to perform.', 'required': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'out_file': {'default': 'math_out.nii.gz', 'description': 'Path to image to write results to.', 'is_output_path': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'output_datatype': {'choices': ['float', 'char', 'int', 'short', 'double', 'input'], 'description': 'Datatype to use for output (default uses input type).', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'output_type': {'choices': ['NIFTI', 'NIFTI_PAIR', 'NIFTI_GZ', 'NIFTI_PAIR_GZ'], 'default': 'NIFTI_GZ', 'description': 'Output file format.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}}¶: BinaryMaths input specification dictionary.

django_mri.analysis.specifications.fsl.binary_maths.BINARY_MATHS_OUTPUT_SPECIFICATION = {'out_file': {'description': "Path to image containing calculation's result.", 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}}¶: BinaryMaths input specification dictionary.

django_mri.analysis.specifications.fsl.eddy module¶

Input and output specification dictionaries for FSL’s eddy script.

django_mri.analysis.specifications.fsl.eddy.EDDY_INPUT_SPECIFICATION = {'cnr_maps': {'default': False, 'description': 'Output CNR-Maps.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'dont_peas': {'default': False, 'description': 'Do NOT perform a post-eddy alignment of shells.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'dont_sep_offs_move': {'default': False, 'description': 'Do NOT perform a post-eddy alignment of shells.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'estimate_move_by_susceptibility': {'default': False, 'description': 'Estimate how susceptibility field changes with subject movement.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'fep': {'default': False, 'description': 'Fill empty planes in x- or y-directions.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'field': {'description': 'Non-topup derived fieldmap scaled in Hz.', 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>}, 'field_mat': {'description': 'Matrix specifying the relative positions of the fieldmap, –field, and the first volume of the input file, –imain.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'flm': {'choices': ['quadratic', 'linear', 'cubic'], 'default': 'quadratic', 'description': 'First level EC model.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'fudge_factor': {'default': 10.0, 'description': 'Fudge factor for hyperparameter error variance.', 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'fwhm': {'description': 'FWHM for conditioning filter when estimating the parameters.', 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'in_acqp': {'description': 'File containing acquisition parameters.', 'required': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'in_bval': {'description': 'File containing the b-values for all volumes in –imain.', 'required': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'in_bvec': {'description': 'File containing the b-vectors for all volumes in –imain.', 'required': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'in_file': {'description': 'File containing all the images to estimate distortions for.', 'is_configuration': False, 'required': True, 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>}, 'in_index': {'description': 'File containing indices for all volumes in –imain into –acqp and –topup.', 'required': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'in_mask': {'description': 'Mask to indicate brain.', 'required': True, 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>}, 'in_topup_fieldcoef': {'description': 'opup results file containing the field coefficients.', 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>}, 'in_topup_movpar': {'description': 'Topup results file containing the movement parameters (movpar.txt). Requires inputs: in_topup_fieldcoef', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'initrand': {'description': 'Resets rand for when selecting voxels.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'interp': {'choices': ['spline', 'trilinear'], 'default': 'spline', 'description': ' Interpolation model for estimation step.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'is_shelled': {'description': 'Override internal check to ensure that date are acquired on a set of b-value shells.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'json': {'description': 'Name of .json text file with information about slice timing. Mutually exclusive with inputs: slice_order. Requires inputs: mporder.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mbs_ksp': {'description': 'Knot-spacing for MBS field estimation. Requires inputs: estimate_move_by_susceptibility.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'mbs_lambda': {'description': 'Weighting of regularisation for MBS estimation. Requires inputs: estimate_move_by_susceptibility.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'mbs_niter': {'description': 'Number of iterations for MBS estimation. Requires inputs: estimate_move_by_susceptibility.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'method': {'choices': ['jac', 'lsr'], 'default': 'jac', 'description': 'Final resampling method (jacobian/least squares).', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mporder': {'description': 'Order of slice-to-vol movement model.Requires inputs: use_cuda.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'multiband_factor': {'description': 'Multi-band factor.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'multiband_offset': {'description': 'Multi-band offset (-1 if bottom slice removed, 1 if top slice removed. Requires inputs: multiband_factor.', 'max_value': 1, 'min_value': -1, 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'niter': {'default': 5, 'description': 'Number of iterations.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'num_threads': {'default': 1, 'description': 'Number of openmp threads to use.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'nvoxhp': {'description': '# of voxels used to estimate the hyperparameters.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'out_base': {'default': 'eddy_corrected', 'description': 'Basename for output image.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'outlier_nstd': {'description': 'Number of std off to qualify as outlier.Requires inputs: repol.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'outlier_pos': {'description': 'Consider both positive and negative outliers if set. Requires inputs: repol.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'outlier_sqr': {'description': 'Consider outliers among sums-of-squared differences if set. Requires inputs: repol.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'outlier_type': {'choices': ['sw', 'gw', 'both'], 'description': 'Type of outliers, slicewise (sw), groupwise (gw) or both (both). Requires inputs: repol.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'output_type': {'choices': ['NIFTI', 'NIFTI_PAIR', 'NIFTI_GZ', 'NIFTI_PAIR_GZ'], 'default': 'NIFTI_GZ', 'description': 'Output file format.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'repol': {'description': 'Detect and replace outlier slices.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'residuals': {'description': 'Output Residuals.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'session': {'description': 'File containing session indices for all volumes in –imain.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'slice2vol_interp': {'choices': ['trilinear', 'spline'], 'description': ' Slice-to-vol interpolation model for estimation step. Requires inputs: mporder.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'slice2vol_lambda': {'description': 'Regularisation weight for slice-to-vol movement (reasonable range 1-10). Requires inputs: mporder.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'slice2vol_niter': {'description': 'umber of iterations for slice-to-vol. Requires inputs: mporder.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'slice_order': {'description': 'Name of text file completely specifying slice/group acquisition. Mutually exclusive with inputs: json. Requires inputs: mporder.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'slm': {'choices': ['none', 'linear', 'quadratic'], 'default': 'none', 'description': 'Second level EC model.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'use_cuda': {'description': 'Run eddy using cuda gpu.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}}¶: eddy input specification dictionary.

django_mri.analysis.specifications.fsl.eddy.EDDY_OUTPUT_SPECIFICATION = {'out_cnr_maps': {'description': 'Path/name of file with the cnr_maps.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'out_corrected': {'description': '4D image file containing all the corrected volumes.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'out_movement_over_time': {'description': 'Text file containing translations (mm) and rotations (radians) for each excitation.', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'out_movement_rms': {'description': 'Summary of the ‘total movement’ in each volume.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'out_outlier_free': {'description': '4D image file not corrected for susceptibility or eddy-current distortions or subject movement but with outlier slices replaced.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'out_outlier_map': {'description': 'Matrix where rows represent volumes and columns represent slices. “0” indicates that scan-slice is not an outlier and “1” indicates that it is.', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'out_outlier_n_sqr_stdev_map': {'description': 'Matrix where rows represent volumes and columns represent slices. Values indicate number of standard deivations off the square root of the mean squared difference between observation and prediction is.', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'out_outlier_n_stdev_map': {'description': 'Matrix where rows represent volumes and columns represent slices. Values indicate number of standard deviations off the mean difference between observation and prediction is.', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'out_outlier_report': {'description': 'Text file with a plain language report on what outlier slices eddy has found.', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'out_parameter': {'description': 'Text file with parameters defining the field and movement for each scan.', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'out_residuals': {'description': 'Path/name of file with the residuals.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'out_restricted_movement_rms': {'description': 'Summary of the ‘total movement’ in each volume disregarding translation in the PE direction.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'out_rotated_bvecs': {'description': 'File containing rotated b-values for all volumes.', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'out_shell_alignment_parameters': {'description': ' Text file containing rigid body movement parameters between the different shells as estimated by a post-hoc mutual information based registration.', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'out_shell_pe_translation_parameters': {'description': 'Text file containing translation along the PE-direction between the different shells as estimated by a post-hoc mutual information based registration.', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}}¶: eddy input specification dictionary.

django_mri.analysis.specifications.fsl.fast module¶

Input and output specification dictionaries for FSL’s FAST script.

django_mri.analysis.specifications.fsl.fast.FAST_INPUT_SPECIFICATION = {'args': {'description': 'Additional parameters to the command.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'bias_iters': {'description': 'Number of main-loop iterations during bias-field removal.', 'max_value': 10, 'min_value': 1, 'required': False, 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'bias_lowpass': {'description': 'Bias field smoothing extent (FWHM) in millimeters.', 'max_value': 40, 'min_value': 4, 'required': False, 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'hyper': {'description': 'Segmentation spatial smoothness.', 'max_value': 1, 'min_value': 0, 'required': False, 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'img_type': {'description': 'Integer specifying type of image: (1=T1, 2=T2, 3=PD).', 'max_value': 3, 'min_value': 1, 'required': False, 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'in_files': {'description': 'Path to NIfTI format image file to be segmented.', 'required': True, 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>, 'value_attribute': 'path.__str__'}, 'init_seg_smooth': {'description': 'Initial segmentation spatial smoothness (during bias field estimation).', 'max_value': 0.1, 'min_value': 0.0001, 'required': False, 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'init_transform': {'description': '<standard2input.mat> initialise using priors.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'iters_afterbias': {'description': 'Number of main-loop iterations after bias-field removal.', 'max_value': 20, 'min_value': 1, 'required': False, 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'manual_seg': {'description': 'Filename containing intensities.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'mixel_smooth': {'description': 'Spatial smoothness for mixeltype.', 'max_value': 1, 'min_value': 0, 'required': False, 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'no_bias': {'description': 'Do not remove bias field.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'no_pve': {'description': 'Turn off PVE (partial volume estimation).', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'number_classes': {'default': 3, 'description': 'Number of tissue-type classes.', 'max_value': 10, 'min_value': 1, 'required': False, 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'out_basename': {'default': 'segmented', 'description': 'Base name of output files.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'output_biascorrected': {'description': 'Output restored image (bias-corrected image).', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'output_biasfield': {'description': 'Output estimated bias-field.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'output_type': {'choices': ['NIFTI', 'NIFTI_PAIR', 'NIFTI_GZ', 'NIFTI_PAIR_GZ'], 'default': 'NIFTI_GZ', 'description': 'Output file format.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'probability_maps': {'description': 'Outputs individual probability maps.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'segment_iters': {'description': 'Number of segmentation-initialisation iterations.', 'max_value': 50, 'min_value': 1, 'required': False, 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'segments': {'description': 'Outputs a separate binary image for each tissue type.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'use_priors': {'description': 'Use priors throughout.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}}¶: FAST input specification dictionary.

django_mri.analysis.specifications.fsl.fast.FAST_OUTPUT_SPECIFICATION = {'mixeltype': {'description': 'Path/name of mixeltype volume file _mixeltype.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'partial_volume_0': {'description': '', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'partial_volume_1': {'description': '', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'partial_volume_2': {'description': '', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'tissue_class_map': {'description': 'An image of all tissue classes represented as 1, 2, and 3.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}}¶: FAST output specification dictionary.

django_mri.analysis.specifications.fsl.flirt module¶

Input and output specification dictionaries for FSL’s FLIRT script.

django_mri.analysis.specifications.fsl.flirt.FLIRT_INPUT_SPECIFICATION = {'angle_rep': {'choices': ['quaternion', 'euler'], 'description': 'Rotation angles representation.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'apply_isoxfm': {'description': 'Whether to apply an affine transformation with isotropic resampling.', 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'apply_xfm': {'description': 'Whether to apply an existing affine transformation.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'bbr_slope': {'description': 'Value of BBR slope.', 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'bbrtype': {'choices': ['signed', 'global_abs', 'local_abs'], 'description': 'Type of BBR cost function.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'bgvalue': {'description': 'Use a specified background value for points outside FOV.', 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'bins': {'description': 'Number of histogram bins.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'coarse_search': {'description': 'Coarse search delta angle.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'cost': {'choices': ['mutualinfo', 'corratio', 'normcorr', 'normmi', 'leastsq', 'labeldiff', 'bbr'], 'default': 'corratio', 'description': 'Type of cost function to apply.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'datatype': {'choices': ['char', 'short', 'int', 'float', 'double'], 'description': 'Output data type.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'display_init': {'description': 'Whether to display the initial matrix.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'dof': {'default': 12, 'description': 'Tranform degrees of freedom.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'echospacing': {'description': 'Value of EPI echo spacing in seconds.', 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'fieldmap': {'description': 'Fieldmap image in radians per second. Must be already registered to the reference image.', 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'fieldmapmask': {'description': 'Mask for fieldmap image.', 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'fine_search': {'description': 'Fine search delta angle.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'force_scaling': {'description': 'Force rescaling even for low resolution images.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'in_file': {'description': 'A NIfTI format file to register to the reference.', 'is_configuration': False, 'required': True, 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>, 'value_attribute': 'path.__str__'}, 'in_matrix_file': {'description': 'An 4x4 affine transformation matrix to apply.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'in_weight': {'description': 'Input file for weighting.', 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'interp': {'choices': ['trilinear', 'nearestneighbour', 'sinc', 'spline'], 'description': 'Final interpolation method used in reslicing.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'min_sampling': {'description': 'Minimum voxel dimensions for resampling.', 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'no_clamp': {'description': 'Whether to not use intensity clamping.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'no_resample': {'description': 'Whether to not change input sampling.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'no_resample_blur': {'description': 'Whether to not use blurring on downsampling.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'no_search': {'description': 'Set all angular search ranges to [0, 0].', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'out_file': {'default': 'registered.nii.gz', 'description': 'The resulting registered image.', 'is_output_path': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'out_log': {'default': 'log.txt', 'description': 'Path to save a log of the run if required.', 'is_output_path': True, 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'out_matrix_file': {'default': 'affine_matrix.txt', 'description': 'The calculated affine transformation that registers the input to the reference which is saved as a 4x4 affine matrix.', 'is_output_path': True, 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'padding_size': {'description': 'Interpolates outside image when using apply_xfm.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'pedir': {'description': 'Phase encode direction of EPI - 1/2/3=x/y/z & -1/-2/-3=-x/-y/-z.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'ref_weight': {'description': 'Refernce file for weighting.', 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'reference': {'description': 'A NIfTI format file to register the input file with.', 'required': True, 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>, 'value_attribute': 'path.__str__'}, 'rigid2D': {'description': 'Whether to use 2D rigid body mode (ignores DOF).', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'save_log': {'default': False, 'description': 'Whether to save a run log.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'schedule': {'description': 'Replace default schedule.', 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'searchr_x': {'description': 'Search angles along X-axis in degrees.', 'element_type': 'INT', 'max_length': 2, 'min_length': 2, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'searchr_y': {'description': 'Search angles along Y-axis in degrees.', 'element_type': 'INT', 'max_length': 2, 'min_length': 2, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'searchr_z': {'description': 'Search angles along Z-axis in degrees.', 'element_type': 'INT', 'max_length': 2, 'min_length': 2, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'sinc_width': {'description': 'Full width in voxels.', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'sinc_window': {'choices': ['rectangular', 'hanning', 'blackman'], 'description': 'Final interpolation method used in reslicing.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'uses_qform': {'description': 'Whether to initialize using sform or qform.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'verbose': {'description': 'Verbosity level (0 is the least verbose).', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'wm_seg': {'description': 'White matter segmentation volume needed by BBR cost function.', 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'wmcoords': {'description': 'White matter boundary coordinates for BBR cost function.', 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'wmnorms': {'description': 'White matter boundary normals for BBR cost function.', 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}}¶: FLIRT input specification dictionary.

django_mri.analysis.specifications.fsl.flirt.FLIRT_OUTPUT_SPECIFICATION = {'out_file': {'description': 'Path to registered file (if generated).', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'out_log': {'description': 'Path to the run log (if generated).', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>, 'validate_existence': False}, 'out_matrix_file': {'description': 'Path to the calculated affine transform (if generated).', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>, 'validate_existence': False}}¶: FLIRT output specification dictionary.

django_mri.analysis.specifications.fsl.fnirt module¶

Input and output specification dictionaries for FSL’s FNIRT script.

django_mri.analysis.specifications.fsl.fnirt.FNIRT_INPUT_SPECIFICATION = {'affine_file': {'description': 'File containing an existing affine transformation matrix.', 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'apply_inmask': {'description': 'A list of iterations to use the input mask on (1 to use, 0 to skip).', 'element_type': 'INT', 'required': False, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'apply_intensity_mapping': {'description': 'List of subsampling levels to apply intensity mapping for (0 to skip, 1 to apply).', 'element_type': 'INT', 'required': False, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'apply_refmask': {'description': 'A list of iterations to use the reference mask on (1 to use, 0 to skip).', 'element_type': 'INT', 'required': False, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'bias_regularization_lambda': {'default': 10000, 'description': 'Weight of regularisation for bias-field.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'biasfield_resolution': {'as_tuple': True, 'default': [50, 50, 50], 'description': 'Approximate resolution (in mm) of warp basis in the X, Y, and Z axes.', 'element_type': 'INT', 'max_length': 3, 'min_length': 3, 'required': False, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'config_file': {'description': 'Path for a config file specifying command line arguments.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'derive_from_ref': {'default': False, 'description': 'If true, reference image is used to calculate derivatives.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'field_file': {'default': 'field.nii.gz', 'description': 'Path for the output file with field.', 'is_output_path': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'fieldcoeff_file': {'default': 'field_coefficients.nii.gz', 'description': 'Name for field coefficients file to output.', 'is_output_path': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'hessian_precision': {'choices': ['double', 'float'], 'default': 'double', 'description': 'Precision for representing Hessian.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'in_file': {'description': 'A NIfTI format file to register to the reference.', 'is_configuration': False, 'required': True, 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>, 'value_attribute': 'path.__str__'}, 'in_fwhm': {'default': [6, 4, 2, 2], 'description': 'FWHM (in mm) of gaussian smoothing kernel for the input volume.', 'element_type': 'INT', 'required': False, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'in_intensitymap_file': {'description': 'File containing initial initial intensity mapping usually generated by a previous FNIRT run.', 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'inmask_file': {'description': 'Path for a file with a mask in the input image space.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'inmask_val': {'default': 0, 'description': 'Value to mask out in input image.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'intensity_mapping_model': {'choices': ['none', 'global_linear', 'global_non_linear', 'local_linear', 'global_non_linear_with_bias', 'local_non_linear'], 'description': 'Model for intensity-mapping.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'intensity_mapping_order': {'default': 5, 'description': 'Order of poynomial for mapping intensities.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'inwarp_file': {'description': 'File containing initial non-linear warps.', 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'jacobian_file': {'default': 'jacobian.nii.gz', 'description': 'Path to the output file for writing out the Jacobian of the field (for diagnostic or VBM purposes).', 'is_output_path': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'jacobian_range': {'as_tuple': True, 'default': [0.01, 100.0], 'description': 'Allowed range of Jacobian determinants.', 'element_type': 'FLT', 'required': False, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'log_file': {'default': 'log.txt', 'description': 'Path for a log file.', 'is_output_path': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'max_nonlin_iter': {'default': [5, 5, 5, 5], 'description': 'List containing the maximal numbers of non-linear iterations.', 'element_type': 'INT', 'required': False, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'modulatedref_file': {'default': 'modulatedref.nii.gz', 'description': 'Path to the output file for writing out intensity modulated --ref (for diagnostic purposes).', 'is_output_path': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'output_type': {'choices': ['NIFTI', 'NIFTI_PAIR', 'NIFTI_GZ', 'NIFTI_PAIR_GZ'], 'description': 'Output file format.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'ref_file': {'description': 'A NIfTI format file to register the input file with.', 'required': True, 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>, 'value_attribute': 'path.__str__'}, 'ref_fwhm': {'default': [4, 2, 0, 0], 'description': 'FWHM (in mm) of gaussian smoothing kernel for the reference volume.', 'element_type': 'INT', 'required': False, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'refmask_file': {'description': 'Path for a file with a mask in the reference space.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'refmask_val': {'default': 0, 'description': 'Value to mask out in reference image.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'regularization_lambda': {'description': 'Weight of regularisation.', 'element_type': 'FLT', 'required': False, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'regularization_model': {'choices': ['membrane_energy', 'bending_energy'], 'default': 'bending_energy', 'description': 'Model for regularisation of warp-field.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'skip_implicit_in_masking': {'description': 'Skip implicit masking based on value in input image.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'skip_implicit_ref_masking': {'description': 'Skip implicit masking based on value in reference image.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'skip_inmask': {'description': 'Skip specified inmask_file if set.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'skip_intensity_mapping': {'default': False, 'description': 'Whether to skip estimate intensity-mapping.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'skip_lambda_ssq': {'default': False, 'description': 'If true, lambda is not weighted by current ssq.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'skip_refmask': {'description': 'Skip specified refmask_file if set.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'spline_order': {'default': 3, 'description': 'Order of spline (2 = quadratic, 3 = cubic).', 'required': False, 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'subsampling_scheme': {'default': [4, 2, 1, 1], 'description': 'Sub-sampling scheme.', 'element_type': 'INT', 'required': False, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'warp_resolution': {'as_tuple': True, 'default': [10, 10, 10], 'description': 'Approximate resolution (in mm) of warp basis in the X, Y, and Z axes.', 'element_type': 'INT', 'max_length': 3, 'min_length': 3, 'required': False, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'warped_file': {'default': 'warped.nii.gz', 'description': 'Path for the output image.', 'is_output_path': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}}¶: FNIRT input specification dictionary.

django_mri.analysis.specifications.fsl.fnirt.FNIRT_OUTPUT_SPECIFICATION = {'field_file': {'description': 'Warp field.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'fieldcoeff_file': {'description': 'Field coefficients.', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'jacobian_file': {'description': 'Jacobian of the field.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'log_file': {'description': 'Run log.', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'modulatedref_file': {'description': 'Intensity modulated reference.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'warped_file': {'description': 'Warped image.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}}¶: FNIRT output specification dictionary.

django_mri.analysis.specifications.fsl.fsl_anat module¶

Input and output specification dictionaries for FSL’s fsl_anat script.

django_mri.analysis.specifications.fsl.fsl_anat.FSL_ANAT_INPUT_SPECIFICATION = {'bias_field_smoothing': {'description': 'Specify the value for bias field smoothing (the -l option in FAST).', 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'destination': {'description': 'Run output destination.', 'is_configuration': False, 'is_output_directory': True, 'required': False, 'run_method_input': True, 'type': <class 'django_analyses.models.input.definitions.directory_input_definition.DirectoryInputDefinition'>}, 'image': {'description': 'Input image for preprocessing.', 'is_configuration': False, 'required': True, 'run_method_input': True, 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>}, 'image_type': {'choices': ['T1', 'T2', 'PD'], 'default': 'T1', 'description': 'Specify the type of image (T1, T2, or PD, default is T1).', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'no_bias': {'description': 'Turn off FAST bias field correction.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'no_cleanup': {'description': 'Do not remove intermediate files.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'no_crop': {'description': 'Turn off automated cropping (`robustfov`).', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'no_nonlinear_registration': {'description': 'Turn off non-linear registration to standard using FNIRT.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'no_registration': {'description': 'Turn off registration to standard using FLIRT and FNIRT.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'no_reorient': {'description': 'Turn off `fslreorient2std` execution.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'no_search': {'description': 'Specify that linear registration uses the -nosearch option (FLIRT).', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'no_segmentation': {'description': 'Turn off tissue-type segmentation using FAST.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'no_subcortical_segmentation': {'description': 'Turn off subcortical segmentation using FIRST.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'weak_bias': {'description': 'Used for images with little and/or smooth bias fields.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}}¶: fsl_anat input specification dictionary.

django_mri.analysis.specifications.fsl.fsl_anat.FSL_ANAT_OUTPUT_SPECIFICATION = {'bias_corrected_brain': {'description': 'Bias-corrected brain extraction result.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'bias_corrected_brain_mask': {'description': 'Mask of bias-corrected brain extraction result.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'csf_partial_volume': {'description': 'CSF partial volume segmenetation.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'fast_bias_correction': {'description': 'Bias-corrected version used for FAST segmentation.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'grey_matter_partial_volume': {'description': 'Grey matter partial volume segmenetation.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'linear_registration': {'description': 'Linear registration output.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'nonlinear_registration': {'description': 'Non-linear registration output.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'nonlinear_registration_field': {'description': 'Non-linear warp field.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'nonlinear_registration_jacobian': {'description': 'Jacobian of the non-linear warp field.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'segmentation_summary': {'description': 'A summary image showing the tissue with the greatest partial volume fraction per voxel.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'subcortical_segmentation_summary': {'description': 'A summary image of subcortical segmentation results.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'volume_scales': {'description': 'A file containing a scaling factor and brain volumes, based on skull-contrained registration, suitable for head-size normalisation (as the scaling is based on the skull size, not the brain size).', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'white_matter_partial_volume': {'description': 'White matter partial volume segmenetation.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}}¶: fsl_anat output specification dictionary.

django_mri.analysis.specifications.fsl.fslmerge module¶

Input and output specification dictionaries for FSL’s fslmerge script.

django_mri.analysis.specifications.fsl.fslmerge.FSLMERGE_INPUT_SPECIFICATION = {'dimension': {'choices': ['t', 'x', 'y', 'z', 'a'], 'description': "Dimension along which to merge, optionally set tr inputs when dimension is 't'.", 'required': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'in_files': {'db_value_preprocessing': 'path.__str__', 'description': 'A list of (at least 2) NIfTI format files to merge.', 'element_type': 'FIL', 'is_configuration': False, 'required': True, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'merged_file': {'default': 'merged.nii.gz', 'description': 'Desired output file path.', 'is_output_path': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'output_type': {'choices': ['NIFTI', 'NIFTI_PAIR', 'NIFTI_GZ', 'NIFTI_PAIR_GZ'], 'default': 'NIFTI_GZ', 'description': 'Output file format.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'tr': {'default': 1.0, 'description': 'Specified TR in seconds.', 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}}¶: fslmerge input specification dictionary.

django_mri.analysis.specifications.fsl.fslmerge.FSLMERGE_OUTPUT_SPECIFICATION = {'merged_file': {'description': 'Path of merged file', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}}¶: fslmerge output specification dictionary.

django_mri.analysis.specifications.fsl.fslroi module¶

Input and output specification dictionaries for FSL’s fslroi script.

django_mri.analysis.specifications.fsl.fslroi.FSLROI_INPUT_SPECIFICATION = {'crop_list': {'description': 'list of two tuples specifying crop options.', 'element_type': 'TUP', 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'ignore_exception': {'description': 'Print an error message instead of throwing an exception in case the interface fails to run', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'in_file': {'description': 'A NIfTI to extract an ROI from.', 'is_configuration': False, 'required': True, 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>, 'value_attribute': 'path.__str__'}, 'output_type': {'choices': ['NIFTI', 'NIFTI_PAIR', 'NIFTI_GZ', 'NIFTI_PAIR_GZ'], 'default': 'NIFTI_GZ', 'description': 'Output file format.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'roi_file': {'default': 'roi.nii.gz', 'description': 'Path to output file.', 'is_output_path': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 't_min': {'description': '', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 't_size': {'description': '', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'x_min': {'description': '', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'x_size': {'description': '', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'y_min': {'description': '', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'y_size': {'description': '', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'z_min': {'description': '', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'z_size': {'description': '', 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}}¶: fslroi input specification dictionary.

django_mri.analysis.specifications.fsl.fslroi.FSLROI_OUTPUT_SPECIFICATION = {'roi_file': {'description': 'Path to output file.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}}¶: fslroi output specification dictionary.

django_mri.analysis.specifications.fsl.mean_image module¶

Input and output specification dictionaries for nipype’s MeanImage interface, wrapping FSL’s fslmaths.

django_mri.analysis.specifications.fsl.mean_image.MEAN_IMAGE_INPUT_SPECIFICATION = {'dimension': {'choices': ['T', 'X', 'Y', 'Z'], 'description': "Dimension along which to merge, optionally set TR inputs when dimension is 'T'", 'required': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'in_file': {'description': 'Path to image to operate on.', 'is_configuration': False, 'required': True, 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>, 'value_attribute': 'path.__str__'}, 'internal_datatype': {'choices': ['float', 'char', 'int', 'short', 'double', 'input'], 'default': 'float', 'description': 'Datatype to use for calculations.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'nan2zero': {'description': 'Change NaNs to zeros before doing anything.', 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'out_file': {'default': 'mean.nii.gz', 'description': 'Path to image to write results to.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'output_datatype': {'choices': ['float', 'char', 'int', 'short', 'double', 'input'], 'description': 'Datatype to use for output (default uses input type).', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'output_type': {'choices': ['NIFTI', 'NIFTI_PAIR', 'NIFTI_GZ', 'NIFTI_PAIR_GZ'], 'default': 'NIFTI_GZ', 'description': 'Output file format.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}}¶: MeanImage input specification dictionary.

django_mri.analysis.specifications.fsl.mean_image.MEAN_IMAGE_OUTPUT_SPECIFICATION = {'out_file': {'description': "Path to image containing calculation's result.", 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}}¶: MeanImage output specification dictionary.

django_mri.analysis.specifications.fsl.reorient2std module¶

Input and output specification dictionaries for nipype’s Reorient2Std interface, wrapping FSL’s fslreorient2std.

django_mri.analysis.specifications.fsl.reorient2std.REORIENT2STD_INPUT_SPECIFICATION = {'args': {'description': 'Additional parameters to the command.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'in_file': {'description': 'Path to NIfTI format image file to reorient.', 'is_configuration': False, 'required': True, 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>, 'value_attribute': 'path.__str__'}, 'out_file': {'default': 'reoriented.nii.gz', 'description': 'Desired output file path.', 'is_output_path': True, 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'output_type': {'choices': ['NIFTI', 'NIFTI_PAIR', 'NIFTI_GZ', 'NIFTI_PAIR_GZ'], 'default': 'NIFTI_GZ', 'description': 'Output file format.', 'is_configuration': False, 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}}¶: Reorient2Std input specification dictionary.

django_mri.analysis.specifications.fsl.reorient2std.REORIENT2STD_OUTPUT_SPECIFICATION = {'out_file': {'description': 'Reorient output file.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}}¶: Reorient2Std output specification dictionary.

django_mri.analysis.specifications.fsl.robustfov module¶

Input and output specification dictionaries for nipype’s RobustFOV interface, wrapping FSL’s robustfov.

django_mri.analysis.specifications.fsl.robustfov.ROBUSTFOV_INPUT_SPECIFICATION = {'args': {'description': 'Additional parameters to the command.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'brainsize': {'default': 170, 'description': 'Size of brain (in millimiteres) in the z-dimension.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'in_file': {'description': 'Path to NIfTI format image file to crop.', 'is_configuration': False, 'required': True, 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>, 'value_attribute': 'path.__str__'}, 'out_roi': {'default': 'roi.nii.gz', 'description': 'ROI volume output file path.', 'is_output_path': True, 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'out_transform': {'default': 'transform.mat', 'description': 'Tranformation matrix output file path.', 'is_output_path': True, 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'output_type': {'choices': ['NIFTI', 'NIFTI_PAIR', 'NIFTI_GZ', 'NIFTI_PAIR_GZ'], 'default': 'NIFTI_GZ', 'description': 'Output file format.', 'is_configuration': False, 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}}¶: RobustFOV input specification dictionary.

django_mri.analysis.specifications.fsl.robustfov.ROBUSTFOV_OUTPUT_SPECIFICATION = {'out_roi': {'description': 'ROI volume.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}, 'out_transform': {'description': 'Transformation matrix in_file to out_roi output name.', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}}¶: RobustFOV output specification dictionary.

django_mri.analysis.specifications.fsl.susan module¶

Input and output specification dictionaries for FSL’s SUSAN script.

django_mri.analysis.specifications.fsl.susan.SUSAN_INPUT_SPECIFICATION = {'args': {'description': 'Additional parameters to pass to the command.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'brightness_threshold': {'description': 'Should be greater than noise level and less than contrast of edges to be preserved.', 'required': True, 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'dimension': {'default': 3, 'max_value': 3, 'min_value': 2, 'required': False, 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'fwhm': {'description': 'FWHM of smoothing, in millimeters.', 'required': True, 'type': <class 'django_analyses.models.input.definitions.float_input_definition.FloatInputDefinition'>}, 'in_file': {'description': 'Filename of input time-series.', 'required': True, 'type': <class 'django_mri.models.inputs.nifti_input_definition.NiftiInputDefinition'>, 'value_attribute': 'path.__str__'}, 'out_file': {'default': 'smooth.nii.gz', 'description': 'Desired output file path.', 'is_output_path': True, 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'output_type': {'choices': ['NIFTI', 'NIFTI_PAIR', 'NIFTI_GZ', 'NIFTI_PAIR_GZ'], 'default': 'NIFTI_GZ', 'description': 'Output file format.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'use_median': {'default': True, 'description': 'Whether to use a local median filter in the cases where single-point noise is detected.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}}¶: SUSAN input specification dictionary.

django_mri.analysis.specifications.fsl.susan.SUSAN_OUTPUT_SPECIFICATION = {'smoothed_file': {'description': 'Smoothed output file.', 'type': <class 'django_mri.models.outputs.nifti_output_definition.NiftiOutputDefinition'>}}¶: SUSAN output specification dictionary.