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)
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class
HistogramNormalisationLayer
(image_name, modalities, model_filename=None, binary_masking_func=None, norm_type='percentile', cutoff=(0.05, 0.95), name='hist_norm')[source]¶