STAPLE

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The STAPLE node implements the Simultaneous Truth and Performance Level Estimation algorithm for generating ground truth volumes from a set of binary expert segmentations.

The STAPLE algorithm treats segmentation as a pixelwise classification, which leads to an averaging scheme that accounts for systematic biases in the behavior of experts in order to generate a fuzzy ground truth volume and simultaneous accuracy assessment of each expert. The ground truth volumes produced by this filter contain values between zero and one that indicate probability of each pixel being in the object targeted by the segmentation.

Inputs

Inputs

Input list of masks containing segmentations of the same object. Must contain at least two masks of the same size.

Type: Mask, List, Required, Single

Outputs

Probability Map

An image with the same spatial properties as the input mask, with values between zero and one that indicate the probability of each pixel is a part of the object targeted by the segmentation.

Type: Image

Statistics

A table that summarizes the Sensitivity and Specificity of each mask.

Type: Table

Settings

Analysis Selection

Within List assumes that the input is a list containing segmentations of the same object, and performs the analysis within the input list.

Across Lists assumes that there are at least two corresponding list inputs, where element n in each list are segmentations of the same object and performs the analysis across lists.

Values: Within List, Across Lists

See also

Keywords: sensitivity, specificity