Contains classical quality metrics for globally assessing the quality of a segmentation relative to a ground truth.
Information about the measurement named measurement can be accessed by using the method
measurementInformation() which returns a
FieldInformation
Information about the measurement named measurement can be accessed by using the property
measurementInformation which returns a
FieldInformation
Information about the measurement named measurement can be accessed by using the property
measurement_information which returns a
FieldInformation
Object members
Measurement name
Description
Element type
Indexing
Physical Information
truePositive
The number of positive results in input image that are defined as such in the ground truth image (TP).
Unsigned integer
[time]
COUNT
falsePositive
The number of positive results in input image that are not defined as such in the ground truth image (FP).
Unsigned integer
[time]
COUNT
trueNegative
The number of negative results in input image that are defined as such in the ground truth image (TN).
Unsigned integer
[time]
COUNT
falseNegative
The number of negative results in input image that are not defined as such in the ground truth image (FN).
Unsigned integer
[time]
COUNT
sensitivity
The proportion of actual positives that are correctly identified as such in the ground truth image.
This metric is also called recall or true positive rate. $$\frac{TP}{TP+FN}$$
Floating point
[time]
COEFFICIENT
specificity
The proportion of actual negatives that are correctly identified as such in the ground truth image.
$$ \frac{TN}{TN+FP}$$
Floating point
[time]
COEFFICIENT
precision
The fraction of relevant results (true positives) among positive results (true and false positives).
$$\frac{TP}{TP+FP}$$
Floating point
[time]
COEFFICIENT
accuracy
The percentage of correct classification among all results.
$$ \frac{TP+TN}{TP+FN+TN+FP} $$
Floating point
[time]
PERCENTAGE
dice
The Sorensen Dice coefficient, comparing the similarity of two samples. This metric is also called F1 score.
$$ \frac{2TP}{2TP+FP+FN} $$
Floating point
[time]
COEFFICIENT
jaccard
The mean Intersection-Over-Union metric.
$$ \frac{TP}{TP+FP+FN} $$
Floating point
[time]
COEFFICIENT
panopticQuality
Metric used to evaluate the performance of a Panoptic Segmentation model.
$$ \frac{ \sum{jaccard}}{TP+0.5FP+0.5FN} $$