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# interfaces.niftyseg.lesions

## FillLesions

Link to code

Wraps command seg_FillLesions

Interface for executable seg_FillLesions from NiftySeg platform.

Fill all the masked lesions with WM intensity average.

Source code | Documentation

### Examples

    >>> from nipype.interfaces import niftyseg
    >>> node = niftyseg.FillLesions()
    >>> node.inputs.in_file = 'im1.nii'
    >>> node.inputs.lesion_mask = 'im2.nii'
    >>> node.cmdline
    'seg_FillLesions -i im1.nii -l im2.nii -o im1_lesions_filled.nii.gz'

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            Input image to fill lesions
            flag: -i %s, position: 1
    lesion_mask: (an existing file name)
            Lesion mask
            flag: -l %s, position: 2

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    bin_mask: (a file name)
            Give a binary mask with the valid search areas.
            flag: -mask %s
    cwf: (a float)
            Patch cardinality weighting factor (by default 2).
            flag: -cwf %f
    debug: (a boolean)
            Save all intermidium files (by default OFF).
            flag: -debug
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    in_dilation: (an integer (int or long))
            Dilate the mask <int> times (in voxels, by default 0)
            flag: -dil %d
    match: (a float)
            Percentage of minimum number of voxels between patches <float> (by
            default 0.5).
            flag: -match %f
    other: (a boolean)
            Guizard et al. (FIN 2015) method, it doesn't include the
            multiresolution/hierarchical inpainting part, this part needs to be
            done with some external software such as reg_tools and reg_resample
            from NiftyReg. By default it uses the method presented in Prados et
            al. (Neuroimage 2016).
            flag: -other
    out_datatype: (a string)
            Set output <datatype> (char, short, int, uchar, ushort, uint, float,
            double).
            flag: -odt %s
    out_file: (a file name)
            The output filename of the fill lesions results
            flag: -o %s, position: 3
    search: (a float)
            Minimum percentage of valid voxels in target patch <float> (by
            default 0).
            flag: -search %f
    size: (an integer (int or long))
            Search regions size respect biggest patch size (by default 4).
            flag: -size %d
    smooth: (a float)
            Smoothing by <float> (in minimal 6-neighbourhood voxels (by default
            0.1)).
            flag: -smo %f
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    use_2d: (a boolean)
            Uses 2D patches in the Z axis, by default 3D.
            flag: -2D
    verbose: (a boolean)
            Verbose (by default OFF).
            flag: -v

Outputs:

    out_file: (a file name)
            Output segmentation