Documentation/Nightly/Modules/HeterogeneityCAD

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Introduction and Acknowledgements

Extension: OpenCAD This work is supported by NA-MIC, NCIGT, and the Slicer Community. Author: Vivek Narayan, Jayender Jagadeesan Contact: Jayender Jagadeesan <email> jayender@bwh.harvard.edu</email>

NA-MIC   NCIGT   SPL   This project is supported by P41 RR019703/RR/NCRR NIH HHS/United States, P01 CA067165/CA/NCI NIH HHS/United States and P41 EB015898/EB/NIBIB NIH HHS/United States

Module Description

The HeterogeneityCAD module is an image feature extraction toolbox primarily to quantify the heterogeneity of tumor images and their label maps.

Image Features and Metrics

• First-Order and Distribution Statistics
  • Data Node: The name of the input node - either an image volume or parameter map
  • Voxel Count: The total number of voxels within the ROI of the grayscale image or parameter map.
  • Energy: A measure of the magnitude of values in an image. A greater amount larger values implies a greater sum of the squares of these values.
  • Entropy: Specifies the uncertainty in the image values. It measures the average amount of information required to encode the image values
  • Minimum Intensity: The value of the voxel(s) in the image ROI with the least value.
  • Maximum Intensity: The value of the voxel(s) in the image ROI with the greatest value.
  • Mean Intensity: The mean of the intensity or parameter values within the image ROI.
  • Median Intensity: The median of the intensity or parameter values within the image ROI.
  • Range: The difference between the highest and lowest voxel values within the image ROI.
  • Mean Deviation: The mean of the distances of each image value from the mean of all the values in the image ROI.
  • Root Mean Square: The square-root of the mean of the squares of the values in the image ROI. It is another measure of the magnitude of the image values.
  • Standard Deviation: Measures the amount of variation or dispersion from the mean of the values in the image ROI.
  • Skewness: Measures the asymmetry of the distribution of values in the image ROI about the mean of the values. Depending on where the tail is elongated and the mass of the distribution is concentrated, this value can be positive or negative.
  • Kurtosis: A measure of the 'peakedness' of the distribution of values in the image ROI. A higher kurtosis implies that the mass of the distribution is concentrated towards the tail(s) rather than towards the mean. A lower kurtosis implies the reverse, that the mass of the distribution is concentrated towards a spike the mean
  • Variance: The mean of the squared distances of each value in the image ROI from the mean of the values. This is a measure of the spread of the distribution about the mean.
  • Uniformity: A measure of the sum of the squares of each discrete value in the image ROI. This is a measure of the heterogeneity of an image, where a greater uniformity implies a greater heterogeneity or a greater range of discrete image values.

• Shape and Morphology Metrics
  • Volume mm^3
  • Volume cc
  • Surface Area mm^2
  • Surface:Volume Ratio
  • Compactness 1
  • Compactness 2
  • Maximum 3D Diameter
  • Spherical Disproportion
  • Sphericity

• Renyi Dimensions
  • Box-Counting Dimension
  • Information Dimension
  • Correlation Dimension

• Geometrical Measures
  • Extruded Surface Area
  • Extruded Volume
  • Extruded Surface:Volume Ratio
  • Extruded Box-Dimension

• Texture: Gray-Level Co-occurrence Matrix (GLCM)
  • Autocorrelation
  • Cluster Prominence
  • Cluster Shade
  • Cluster Tendency
  • Contrast
  • Correlation
  • Difference Entropy
  • Dissimilarity
  • Energy (GLCM)
  • Entropy(H)
  • Homogeneity 1
  • Homogeneity 2
  • Informational Measure of Correlation 1 (IMC1)
  • Informational Measure of Correlation 2 (IMC2)
  • Inverse Difference Moment Normalized (IDMN)
  • Inverse Difference Normalized (IDN)
  • Inverse Variance
  • Maximum Probability
  • Sum Average
  • Sum Entropy
  • Sum Variance
  • Variance (GLCM)

• Texture: Gray-Level Run Length Matrix (GLRL)
  • Short Run Emphasis (SRE)
  • Long Run Emphasis (LRE)
  • Gray Level Non-Uniformity (GLN)
  • Run Length Non-Uniformity (RLN)
  • Run Percentage (RP)
  • Low Gray Level Run Emphasis (LGLRE)
  • High Gray Level Run Emphasis (HGLRE)
  • Short Run Low Gray Level Emphasis (SRLGLE)
  • Short Run High Gray Level Emphasis (SRHGLE)
  • Long Run Low Gray Level Emphasis (LRLGLE)
  • Long Run High Gray Level Emphasis (LRHGLE)

Panels and their use

Quick Instructions for Use Select a nrrd volume Select a segmentation label map to use as ROI Click "Apply HeterogeneityCAD" Module Output Similar Modules N/A References N/A Information for Developers Source code: https://github.com/vnarayan13/Slicer-OpenCAD