niftynet.evaluation.pairwise_measures module¶
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class
niftynet.evaluation.pairwise_measures.
PairwiseMeasures
(seg_img, ref_img, measures=None, num_neighbors=8, pixdim=[1, 1, 1], empty=False, list_labels=None)¶ Bases:
object
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accuracy
()¶
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border_distance
¶ this provides a decorator to cache function outputs to avoid repeating some heavy function computations
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com_dist
()¶
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com_ref
()¶
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com_seg
()¶
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connected_elements
()¶
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connected_errormaps
¶ this provides a decorator to cache function outputs to avoid repeating some heavy function computations
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detection_error
()¶
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dice_score
()¶
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false_positive_rate
()¶
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fn
¶ this provides a decorator to cache function outputs to avoid repeating some heavy function computations
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fp
¶ this provides a decorator to cache function outputs to avoid repeating some heavy function computations
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header_str
()¶
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informedness
()¶
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intersection_over_union
()¶
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jaccard
()¶
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list_labels
()¶
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markedness
()¶
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measured_average_distance
()¶
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measured_distance
()¶
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measured_hausdorff_distance
()¶
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n_intersection
¶ this provides a decorator to cache function outputs to avoid repeating some heavy function computations
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n_neg_ref
¶ this provides a decorator to cache function outputs to avoid repeating some heavy function computations
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n_neg_seg
¶ this provides a decorator to cache function outputs to avoid repeating some heavy function computations
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n_pos_ref
¶ this provides a decorator to cache function outputs to avoid repeating some heavy function computations
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n_pos_seg
¶ this provides a decorator to cache function outputs to avoid repeating some heavy function computations
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n_union
¶ this provides a decorator to cache function outputs to avoid repeating some heavy function computations
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negative_predictive_values
()¶
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outline_error
()¶
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positive_predictive_values
()¶
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sensitivity
()¶
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specificity
()¶
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tn
¶ this provides a decorator to cache function outputs to avoid repeating some heavy function computations
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to_string
(fmt='{:.4f}')¶
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tp
¶ this provides a decorator to cache function outputs to avoid repeating some heavy function computations
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vol_diff
()¶
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