GLDZM#

class zrad.radiomics.gldzm.GLDZM(aggr_dim, slice_weight=False, slice_median=False)[source]#

Grey level distance zone matrix features.

GLDZM features describe connected grey-level zones together with their distance from the ROI border. They summarize how grey-level zones are distributed from boundary-adjacent to deeper ROI regions.

Parameters:

  • aggr_dim ({"2D", "2.5D", "3D"}) – Spatial dimensionality used to define zones and border distances.

  • slice_weight (bool, default=False) – Weight 2D slice-wise averages by slice ROI voxel count.

  • slice_median (bool, default=False) – Aggregate 2D slice-wise values by median instead of mean.

Methods

calculate_features(discretized_image_array, ...)

Calculate GLDZM features for prepared discretized intensities and a morphology mask.

get_feature_names()

Return the GLDZM feature names produced by this calculator.

get_params()

Return the configuration parameters of this GLDZM calculator.
GLDZM.calculate_features(discretized_image_array, mask_array)[source]#

Calculate GLDZM features for prepared discretized intensities and a morphology mask.

Parameters:

  • discretized_image_array (numpy.ndarray) – Prepared discretized intensity array with voxels outside the ROI set to NaN.

  • mask_array (numpy.ndarray) – Morphological ROI mask aligned with discretized_image_array.

Returns:

Mapping of GLDZM feature names to calculated values.

Return type:

dict

GLDZM.get_feature_names()[source]#

Return the GLDZM feature names produced by this calculator.

Returns:

Feature names defined for the GLDZM family.

Return type:

list of str

GLDZM.get_params()[source]#

Return the configuration parameters of this GLDZM calculator.

Returns:

Parameter names mapped to their configured values.

Return type:

dict