config_settings.xml

<root>
    <config>
        <general>
            <!-- Configuration string that may be added to distinguish different configuration -->
            <config_str></config_str>
            <!--  Defines whether image processing and computations should be performed in 2D (True) or 3D (False). Default: False -->
            <by_slice></by_slice>
            <!-- Limits use of methods and computation of features to those that exist in the IBSI reference standard.
            Default: True-->
            <ibsi_compliant></ibsi_compliant>
            <!-- Defines whether multiple mask objects should be combined into a single mask. Default: False -->
            <mask_merge></mask_merge>
            <!-- Defines whether a mask that contains multiple regions should be split into separate mask objects. Default: False -->
            <mask_split></mask_split>
            <!-- Defines whether the largest region within a mask object should be selected. For example, in a mask that
            contains multiple separate lesions. mask_select_largest_region = True will remove all but the largest
            lesion. Default: False -->
            <mask_select_largest_region></mask_select_largest_region>
            <!-- Defines whether the largest slice within a mask object should be selected. Default: False -->
            <mask_select_largest_slice></mask_select_largest_slice>
            <!-- Defines whether any approximation can be made to speed up image processing and feature processing.
            Default: True -->
            <no_approximation></no_approximation>
        </general>
        <image_interpolation>
            <!-- Voxel spacing after interpolation. Units are defined by the headers of the image files. Every
            value represents the spacing that will be applied in all directions. Non-uniform voxel spacing may also
            be provided, but requires 3 values for z, y, and x directions (if by_slice = False) or 2 values for y and
            x directions (otherwise). -->
            <new_spacing></new_spacing>
            <!-- Sets the order of the interpolation spline. It can be 0 (nearest neighbour), 1 (linear), 2, 3
            (cubic), 4, 5 -->
            <spline_order></spline_order>
            <!-- Anti-aliasing filter to reduce aliasing artefacts when down-sampling. Enabled by default (True). -->
            <anti_aliasing></anti_aliasing>
            <!-- Smoothing parameter beta for antialiasing filter. Must be in range (0.0, 1.0]. At 1.0 no
            antialiasing is performed. Default is 0.98. -->
            <smoothing_beta></smoothing_beta>
        </image_interpolation>
        <mask_interpolation>
            <!-- Sets the order of the interpolation spline. It can be 0 (nearest neighbour), 1 (linear), 2 (cubic),
            3, 4, 5. Nearest neighbour or linear interpolation (default) are recommended. -->
            <spline_order></spline_order>
            <!-- Threshold for ROIS with partial volumes after interpolation. Default: 0.5 -->
            <incl_threshold></incl_threshold>
        </mask_interpolation>
        <image_processing>
            <!-- Type of algorithm used to produce an approximate mask of the tissue. Can be none, range (requires
            intensity values), relative_range (default; requires fractions). -->
            <tissue_mask_type></tissue_mask_type>
            <!-- Range values for creating an approximate mask of the tissue. Required for range and relative range
            options. Default: 0.02, 1.0 (relative_range); 0.0, nan (range; effectively none) -->
            <tissue_mask_range></tissue_mask_range>
            <!-- Whether N4 bias field correction should be performed. Disabled by default (False); only applicable
            to MR imaging. If a tissue mask is created, this is used as the mask for N4 bias field correction  -->
            <bias_field_correction></bias_field_correction>
            <!-- Number of fitting levels for N4 bias field correction. Default: 1 -->
            <n_fitting_levels></n_fitting_levels>
            <!-- Max number of iterations for each of the fitting levels for N4 bias field correction, e.g. 100, 100
            if two fitting levels are used. Default: 50 -->
            <n_max_iterations></n_max_iterations>
            <!-- Convergence threshold for N4 bias field correction. Default: 0.001 -->
            <convergence_threshold></convergence_threshold>
            <!-- Intensities in PET imaging are often stored as detected radiotracer activity. To make detected activity more
            comparable between patients, these are converted to standardised uptake values. The following are possible:
            body_weight, body_surface_area, lean_body_mass, lean_body_mass_bmi, ideal_body_weight, none -->
            <pet_suv_conversion></pet_suv_conversion>
            <!-- Algorithm used to normalise intensities in the image. Will use only intensities in voxels masked by
            the  tissue mask. Can be none (default), range (maps to an intensity range), relative_range (maps to a
            range  of relative intensities), quantile_range (maps to a range of relative intensities based on
            intensity percentiles), standardisation (performs z-normalisation). -->
            <intensity_normalisation></intensity_normalisation>
            <!-- Intensity range for range, relative_range and quantile_range normalisation. -->
            <intensity_normalisation_range></intensity_normalisation_range>
            <!-- Intensity saturation after normalisation. Values outside the given range are limited to this range.
             You may define two values for lower and upper boundary respectively. Default: [np.nan, np.nan] (no
             saturation). -->
            <intensity_normalisation_saturation></intensity_normalisation_saturation>
            <!-- Defines scaling parameter to linearly scale intensities with. The scaling parameter is applied after
            normalisation (if any). For example, intensity_scaling = 1000.0, combined with intensity_normalisation =
            "range" results in intensities being mapped to a [0.0, 1000.0] range instead of [0.0, 1.0]. -->
            <intensity_scaling></intensity_scaling>
        </image_processing>
        <image_perturbation>
            <!-- Whether the image may be cut to only maintain the interesting parts. Default: False. Setting this to
             True speeds up calculations and saves memory. -->
            <crop_around_roi></crop_around_roi>
            <!-- Distance (in mm) around the ROI mask that should be maintained when cropping. Default: 150 mm. -->
            <crop_distance></crop_distance>
            <!-- Number of times noise is randomly added to the image. Used in noise addition image perturbations.
            Default: 0 -->
            <noise_repetitions></noise_repetitions>
            <!-- Manually provided noise level in intensity units. If left unset, noise is determined from the image
             itself. -->
            <noise_level></noise_level>
            <!-- Angles (in degrees) over which the image and mask are rotated. This rotation is only in the x-y (axial)
            plane. Used in the rotation image perturbation. Default: 0.0.-->
            <rotation_angles></rotation_angles>
            <!-- Sub-voxel translation distance fractions of the interpolation grid. This forces the interpolation grid
             to shift slightly and interpolate at different points. Used in translation perturbations. Default: 0.0.-->
            <translation_fraction></translation_fraction>
            <!-- Growth/shrinkage of the ROI mask. Interpretations depends on the roi_adapt_size tag. If "distance":
            growth/shrinkage in world dimension units. If "fraction": growth/shrinkage in volume fraction.
             Default: 0.0 (no changes)-->
            <roi_adapt_size></roi_adapt_size>
            <!-- Type of growth/shrinkage. Can be either fraction or distance (default). fraction is used in the volume
            growth/shrinkage image perturbation. -->
            <roi_adapt_type></roi_adapt_type>
            <!-- Limit to shrinkage of the ROI by distance-based adaptations. Fraction of the original volume.
            Default: 0.8 (but not used unless roi_adapt_size!=0.0 and roi_adapt_type=distance) -->
            <roi_adapt_max_erosion></roi_adapt_max_erosion>
            <!-- Supervoxel-based contour randomisation repetitions for image perturbation. Default: 0 -->
            <roi_random_rep></roi_random_rep>
            <!-- Width of the rim used for splitting the mask into bulk and rim masks, in physical dimensions. Multiple values
            can be provided to generate rims of different widths. -->
            <roi_boundary_size></roi_boundary_size>
            <!-- Determines the minimum volume of the bulk mask when splitting the original mask into bulk and rim sections.
            Fraction of the original volume, e.g. 0.6 means that the bulk contains at least 60% of the original mask.
             -->
            <roi_split_max_erosion></roi_split_max_erosion>
        </image_perturbation>
        <mask_resegmentation>
            <!-- Intensity threshold for threshold-based re-segmentation (threshold and range). If set, requires two
             values for lower and upper range respectively. The upper range value can also be nan for half-open
             ranges. -->
            <intensity_range></intensity_range>
            <!-- Number of standard deviations for outlier-based intensity re-segmentation. 3 is a common setting. -->
            <sigma></sigma>
        </mask_resegmentation>
        <feature_computation>
            <!-- Set of feature families to be computed from the image. Default is all. -->
            <feature_families></feature_families>
            <!-- Discretisation algorithm. Can be none, fixed_bin_number and/or fixed_bin_size. Combinations are
            possible. No default. -->
            <discretisation_method></discretisation_method>
            <!-- Bin width (in intensity units) for the fixed_bin_size algorithm. Multiple values are possible. -->
            <discretisation_bin_width></discretisation_bin_width>
            <!-- Bin number for the fixed_bin_number algorithm. Multiple values are possible. -->
            <discretisation_n_bins></discretisation_n_bins>
            <!-- Discretisation algorithm for the intensity-volume histogram. Can be none, fixed_bin_number and/or
            fixed_bin_size. If unset, the image modality determines the algorithm.-->
            <ivh_discretisation_method></ivh_discretisation_method>
            <!-- Bin number for the fixed_bin_number algorithm. Default: 1000 -->
            <ivh_discretisation_n_bins></ivh_discretisation_n_bins>
            <!-- Bin width (in intensity units) for the fixed_bin_size algorithm. -->
            <ivh_discr_bin_width></ivh_discr_bin_width>
            <!-- Distance (in voxels) for GLCM for determining the neighbourhood. -->
            <glcm_distance></glcm_distance>
            <!-- Determines how cooccurrence matrices are merged. One "2d_average", "2d_slice_merge",
             "2.5d_direction_merge", "2.5d_volume_merge", "3d_average", "3d_volume_merge".
              Default: "2d_slice_merge" (by_slice = True), "3d_volume_merge" (by_slice = False) -->
			<glcm_spatial_method></glcm_spatial_method>
            <!-- Determines how run length matrices are merged. One "2d_average", "2d_slice_merge",
             "2.5d_direction_merge", "2.5d_volume_merge", "3d_average", "3d_volume_merge".
              Default: "2d_slice_merge" (by_slice = True), "3d_volume_merge" (by_slice = False) -->
			<glrlm_spatial_method></glrlm_spatial_method>
            <!-- Calculate GLSZM in 2d, 2.5d or 3d. Default: same as general/by_slice. -->
			<glszm_spatial_method></glszm_spatial_method>
            <!-- Calculate GLDZM in 2d, 2.5d or 3d. Default: same as general/by_slice. -->
			<gldzm_spatial_method></gldzm_spatial_method>
            <!-- Calculate NGTDM in 2d, 2.5d or 3d. Default: same as general/by_slice. -->
			<ngtdm_spatial_method></ngtdm_spatial_method>
            <!-- Distance (in voxels) for NGLDM for determining the neighbourhood. -->
            <ngldm_distance></ngldm_distance>
            <!-- Difference level (alpha) for NGLDM -->
            <ngldm_difference_level></ngldm_difference_level>
            <!-- Calculate NGLDM in 2d, 2.5d or 3d. Default: same as general/by_slice. -->
			<ngldm_spatial_method></ngldm_spatial_method>
        </feature_computation>
        <image_transformation>
            <!-- Filter kernels to apply. Options: gabor, laplacian_of_gaussian, laws, mean, separable_wavelet,
            nonseparable_wavelet. See documentation for additional filter kernels. -->
            <filter_kernels></filter_kernels>
             <!-- Boundary conditions, i.e. how to calculate the filter response for voxels that are less than the
            filter width removed from the volume edge. This is the general setting. -->
            <boundary_condition></boundary_condition>
            <!-- Family of features to computed from response maps. Default: statistical. -->
            <feature_families></feature_families>
            <!-- Discretisation algorithm for response maps. Can be none (default), fixed_bin_number and/or
            fixed_bin_size. Combinations are possible.-->
            <discretisation_method></discretisation_method>
             <!-- Bin width (in intensity units) for the fixed_bin_size algorithm. Multiple values are possible. Not
             recommended as for most filter kernels, intensity units have no intrinsic meaning. -->
            <discretisation_bin_width></discretisation_bin_width>
             <!-- Bin number for the fixed_bin_number algorithm. Multiple values are possible. -->
            <discretisation_n_bins></discretisation_n_bins>
            <!-- Separable wavelet kernel to be used. The name must match a wavelet implemented in the pywavelets
            module. -->
            <separable_wavelet_families></separable_wavelet_families>
            <!-- Wavelet filter set to be used (for separable wavelets), e.g. LLL. LLH. Default: all. -->
            <separable_wavelet_set></separable_wavelet_set>
            <!-- Determines if wavelets are stationary or not. Stationary wavelets maintain the image dimensions after
            decomposition. Default: True -->
            <separable_wavelet_stationary></separable_wavelet_stationary>
            <!-- Decomposition level of the response map: 1 (default) or greater integer. -->
            <separable_wavelet_decomposition_level></separable_wavelet_decomposition_level>
            <!-- Create rotationally invariant wavelet response maps; True or False -->
            <separable_wavelet_rotation_invariance></separable_wavelet_rotation_invariance>
            <!-- Pooling method used for rotationally invariant wavelet response maps for separable wavelets.
            Default: max -->
            <separable_wavelet_pooling_method></separable_wavelet_pooling_method>
            <!-- Boundary condition for separable wavelets. Supersedes generic boundary condition tag. -->
            <separable_wavelet_boundary_condition></separable_wavelet_boundary_condition>
            <!-- Non-separable wavelet kernel to be used. "shannon" and "simoncelli" are supported. -->
            <nonseparable_wavelet_families></nonseparable_wavelet_families>
            <!-- Decomposition level of the response map for non-separable wavelets: 1 (default) or greater integer. -->
            <nonseparable_wavelet_decomposition_level></nonseparable_wavelet_decomposition_level>
            <!-- Type of response map created by nonseparable wavelet filters. Default: "real" -->
            <nonseparable_wavelet_response></nonseparable_wavelet_response>
            <!-- Boundary condition for non-separable wavelets. Supersedes generic boundary condition tag. -->
            <nonseparable_wavelet_boundary_condition></nonseparable_wavelet_boundary_condition>
            <!-- Laplacian of Gaussian sigma (in mm). This specifies the width of the Gaussian filter by
            its standard deviation. -->
            <laplacian_of_gaussian_sigma></laplacian_of_gaussian_sigma>
            <!-- Number of standard deviations o allow before truncating the Gaussian filter -->
            <laplacian_of_gaussian_kernel_truncate></laplacian_of_gaussian_kernel_truncate>
            <!-- Pooling method used to combine Laplacian of Gaussian response maps for different sigma values.
            Default: none -->
            <laplacian_of_gaussian_pooling_method></laplacian_of_gaussian_pooling_method>
            <!-- Boundary condition for Laplacian of Gaussian kernels. Supersedes generic boundary condition tag. -->
            <laplacian_of_gaussian_boundary_condition></laplacian_of_gaussian_boundary_condition>
            <!-- Gaussian sigma (in mm). This specifies the width of the Gaussian filter by its standard deviation. -->
            <gaussian_sigma></gaussian_sigma>
            <!-- Number of standard deviations to allow before truncating the Gaussian filter. Default: 4.0 -->
            <gaussian_kernel_truncate></gaussian_kernel_truncate>
            <!-- Boundary condition for Gaussian kernels. Supersedes generic boundary condition tag. -->
            <gaussian_kernel_boundary_condition></gaussian_kernel_boundary_condition>
            <!-- Calculate specific laws kernels, e.g. L5S5E5, E5E5E5. No default.-->
            <laws_kernel></laws_kernel>
            <!-- Calculate laws texture energy image, or just the response map; True (default) or False -->
            <laws_calculate_energy></laws_calculate_energy>
            <!-- Delta for chebyshev distance between centetr voxel and neighbourhood boundary used to calculate
            texture energy: integer, default: 7-->
            <laws_delta></laws_delta>
            <!-- Create rotationally invariant laws kernel response maps or energy images; True (default) or False -->
            <laws_rotation_invariance></laws_rotation_invariance>
            <!-- Pooling method used for rotationally invariant Laws response maps and energy images; max (default)
            or mean. -->
            <laws_pooling_method></laws_pooling_method>
            <!-- Boundary condition for Laws kernels. Supersedes generic boundary condition tag. -->
            <laws_boundary_condition></laws_boundary_condition>
            <!-- Gabor kernel sigma (in mm). Together with gamma, this specifies the width of the filter. -->
            <gabor_sigma></gabor_sigma>
            <!-- Eccentricity parameter of the Gaussian envelope of the Gabor kernel. Defines width of y-axis
            relative to x-axis for 0-angle Gabor kernel. -->
            <gabor_gamma></gabor_gamma>
            <!-- Wavelength of the oscillator (in mm) -->
            <gabor_lambda></gabor_lambda>
            <!-- Initial angle of the Gabor filter. Defined in degrees. Default: 0.0 -->
            <gabor_theta></gabor_theta>
            <!-- Angle step size for in-plane rotational invariance. Defined in degrees. Default: None (no stepping) -->
            <gabor_theta_step></gabor_theta_step>
            <!-- Type of response map created by Gabor filters. Gabor kernels consist of complex numbers, and the
            direct response map will be complex as well. The complex-valued response map is converted to a
            real-valued response map using the specified method; one of modulus (default), argument, real,
            imaginary -->
            <gabor_response></gabor_response>
             <!-- Create rotationally invariant Gabor response maps by stacking 2D response over orthogonal planes;
             True (default for 3D) or False. Not possible for 2D analysis (by_slice). -->
            <gabor_rotation_invariance></gabor_rotation_invariance>
            <!-- Pooling method used for rotationally invariant response maps for gabor kernels; max (default)
             or mean. -->
            <gabor_pooling_method></gabor_pooling_method>
            <!-- Boundary condition for Gabor kernels. Supersedes generic boundary condition tag. -->
            <gabor_boundary_condition></gabor_boundary_condition>
            <!-- Filter size in voxel units for mean filter. -->
            <mean_filter_kernel_size></mean_filter_kernel_size>
            <!-- Boundary condition for mean filter kernels. Supersedes generic boundary condition tag. -->
            <mean_filter_boundary_condition></mean_filter_boundary_condition>
            <!-- Riesz-transformation order. If required, should be a 2 (2D filter), or 3-element (3D filter) integer
             vector, e.g. 0,0,1. Note: order is (z, y, x).-->
            <riesz_filter_order></riesz_filter_order>
            <!--Sigma for Gaussian filter used in steerable Riesz transformation. -->
            <riesz_filter_tensor_sigma></riesz_filter_tensor_sigma>
        </image_transformation>
    </config>
</root>