niftynet.layer.histogram_normalisation module

This class computes histogram based normalisation. A training process is first used to find an averaged histogram mapping from all training volumes. This layer maintains the mapping array, and the layer_op maps the intensity of new volumes to a normalised version. The histogram is computed from foreground if a definition is provided for foreground (by binary_masking_func or a mask matrix)

class niftynet.layer.histogram_normalisation.HistogramNormalisationLayer(image_name, modalities, model_filename, binary_masking_func=None, norm_type='percentile', cutoff=(0.05, 0.95), name='hist_norm')

Bases: niftynet.layer.base_layer.DataDependentLayer

is_ready()

layer_op(image, mask=None)

train(image_list)