This package provides a number of metric measures that e.g. can be used for testing
and/or evaluation purposes on two binary masks (i.e. measuring their similarity) or
distance between histograms.
Metrics to compare binary objects and classification results.
Compare two binary objects
dc (result, reference) |
Dice coefficient |
jc (result, reference) |
Jaccard coefficient |
hd (result, reference[, voxelspacing, …]) |
Hausdorff Distance. |
asd (result, reference[, voxelspacing, …]) |
Average surface distance metric. |
assd (result, reference[, voxelspacing, …]) |
Average symmetric surface distance. |
precision (result, reference) |
Precison. |
recall (result, reference) |
Recall. |
sensitivity (result, reference) |
Sensitivity. |
specificity (result, reference) |
Specificity. |
true_positive_rate (result, reference) |
True positive rate. |
true_negative_rate (result, reference) |
True negative rate. |
positive_predictive_value (result, reference) |
Positive predictive value. |
ravd (result, reference) |
Relative absolute volume difference. |
Compare two sets of binary objects
obj_tpr (result, reference[, connectivity]) |
The true positive rate of distinct binary object detection. |
obj_fpr (result, reference[, connectivity]) |
The false positive rate of distinct binary object detection. |
obj_asd (result, reference[, voxelspacing, …]) |
Average surface distance between objects. |
obj_assd (result, reference[, voxelspacing, …]) |
Average symmetric surface distance. |
Compare to sequences of binary objects
chebyshev (h1, h2) |
Chebyshev distance. |
chebyshev_neg (h1, h2) |
Chebyshev negative distance. |
chi_square (h1, h2) |
Chi-square distance. |
correlate (h1, h2) |
Correlation between two histograms. |
correlate_1 (h1, h2) |
Correlation distance. |
cosine (h1, h2) |
Cosine simmilarity. |
cosine_1 (h1, h2) |
Cosine simmilarity. |
cosine_2 (h1, h2) |
Cosine simmilarity. |
cosine_alt (h1, h2) |
Alternative implementation of the cosine distance measure. |
euclidean (h1, h2) |
Equal to Minowski distance with \(p=2\). |
fidelity_based (h1, h2) |
Fidelity based distance. |
histogram_intersection (h1, h2) |
Calculate the common part of two histograms. |
histogram_intersection_1 (h1, h2) |
Turns the histogram intersection similarity into a distance measure for normalized, positive histograms. |
jensen_shannon (h1, h2) |
Jensen-Shannon divergence. |
kullback_leibler (h1, h2) |
Kullback-Leibler divergence. |
manhattan (h1, h2) |
Equal to Minowski distance with \(p=1\). |
minowski (h1, h2[, p]) |
Minowski distance. |
noelle_1 (h1, h2) |
Extension of fidelity_based proposed by [R39]. |
noelle_2 (h1, h2) |
Extension of fidelity_based proposed by [R40]. |
noelle_3 (h1, h2) |
Extension of fidelity_based proposed by [R41]. |
noelle_4 (h1, h2) |
Extension of fidelity_based proposed by [R42]. |
noelle_5 (h1, h2) |
Extension of fidelity_based proposed by [R43]. |
quadratic_forms (h1, h2) |
Quadrativ forms metric. |
relative_bin_deviation (h1, h2) |
Calculate the bin-wise deviation between two histograms. |
relative_deviation (h1, h2) |
Calculate the deviation between two histograms. |