# Segment statistics¶

This is a module for the calculation of statistics related to the structure of segmentations, such as volume, surface area, mean intensity, and various other metrics for each segment.

## Labelmap statistics¶

Labelmap statistics are calculated using the binary labelmap representation of the segment.

• Voxel count: the number of voxels in the segment

• Volume mm3 the volume of the segment in mm3

• Volume cm3 the volume of the segment in cm3

• Centroid: the center of mass of the segment in RAS coordinates

• Feret diameter: the diameter of a sphere that can encompass the entire segment

• Surface area mm2: the volume of the segment in mm2

• Roundness: the roundness of the segment. Calculated from ratio of the area of the sphere calculated from the Feret diameter by the actual area. Value of 1 represents a spherical structure. See detailed definition here.

• Flatness: the flatness of the segment. Calculated from square root of the ratio of the second smallest principal moment by the smallest. Value of 0 represents a flat structure. See detailed definition here.

• Elongation: the elongation of the segment. Calculated from square root of the ratio of the second largest principal moment by the second smallest. See detailed definition here.

• Principal moments: the principal moments of inertia for each axes of the segment

• Principal axes: the principal axes of rotation of the segment

• Oriented bounding box: the non-axis aligned bounding box that encompasses the segment. Principal axis directions are used to orient the bounding box.

## Scalar volume statistics¶

• Voxel count: the number of voxels in the segment

• Volume mm3 the volume of the segment in mm3

• Volume cm3 the volume of the segment in cm3

• Minimum: the minimum scalar value in the segment

• Maximum: the maximum scalar value in the segment

• Mean: the mean scalar value in the segment

• Median: the median scalar value in the segment

• Standard deviation: the standard deviation of scalar values in the segment (computed using corrected sample standard deviation formula)

## Closed surface statistics¶

• Surface area mm2: the volume of the segment in mm2

• Volume mm3 the volume of the segment in mm3

• Volume cm3 the volume of the segment in cm3

## Information for developers¶

See examples for calculating statistics from your own modules in the Slicer script repository. Additional plugins for computation of other statistical measurements may be registered by subclassing SegmentStatisticsPluginBase.py, and registering the plugin with SegmentStatisticsLogic.

## Contributors¶

Authors:

• Csaba Pinter (PerkLab, Queen’s University)

• Andras Lasso (PerkLab, Queen’s University)

• Christian Bauer (University of Iowa)

• Steve Pieper (Isomics Inc.)

• Kyle Sunderland (PerkLab, Queen’s University)

## Acknowledgements¶

This module is partly funded by an Applied Cancer Research Unit of Cancer Care Ontario with funds provided by the Ministry of Health and Long-Term Care and the Ontario Consortium for Adaptive Interventions in Radiation Oncology (OCAIRO) to provide free, open-source toolset for radiotherapy and related image-guided interventions. The work is part of the National Alliance for Medical Image Computing (NA-MIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149.