anatomical.py 文件源码

def headmsk_wf(name='HeadMaskWorkflow', use_bet=True):
    """
    Computes a head mask as in [Mortamet2009]_.

    .. workflow::

        from mriqc.workflows.anatomical import headmsk_wf
        wf = headmsk_wf()

    """

    has_dipy = False
    try:
        from dipy.denoise import nlmeans
        has_dipy = True
    except ImportError:
        pass

    workflow = pe.Workflow(name=name)
    inputnode = pe.Node(niu.IdentityInterface(fields=['in_file', 'in_segm']),
                        name='inputnode')
    outputnode = pe.Node(niu.IdentityInterface(fields=['out_file']), name='outputnode')

    if use_bet or not has_dipy:
        # Alternative for when dipy is not installed
        bet = pe.Node(fsl.BET(surfaces=True), name='fsl_bet')
        workflow.connect([
            (inputnode, bet, [('in_file', 'in_file')]),
            (bet, outputnode, [('outskin_mask_file', 'out_file')])
        ])

    else:
        from niworkflows.nipype.interfaces.dipy import Denoise
        enhance = pe.Node(niu.Function(
            input_names=['in_file'], output_names=['out_file'], function=_enhance), name='Enhance')
        estsnr = pe.Node(niu.Function(
            input_names=['in_file', 'seg_file'], output_names=['out_snr'],
            function=_estimate_snr), name='EstimateSNR')
        denoise = pe.Node(Denoise(), name='Denoise')
        gradient = pe.Node(niu.Function(
            input_names=['in_file', 'snr'], output_names=['out_file'], function=image_gradient), name='Grad')
        thresh = pe.Node(niu.Function(
            input_names=['in_file', 'in_segm'], output_names=['out_file'], function=gradient_threshold),
                         name='GradientThreshold')

        workflow.connect([
            (inputnode, estsnr, [('in_file', 'in_file'),
                                 ('in_segm', 'seg_file')]),
            (estsnr, denoise, [('out_snr', 'snr')]),
            (inputnode, enhance, [('in_file', 'in_file')]),
            (enhance, denoise, [('out_file', 'in_file')]),
            (estsnr, gradient, [('out_snr', 'snr')]),
            (denoise, gradient, [('out_file', 'in_file')]),
            (inputnode, thresh, [('in_segm', 'in_segm')]),
            (gradient, thresh, [('out_file', 'in_file')]),
            (thresh, outputnode, [('out_file', 'out_file')])
        ])

    return workflow