Difference between revisions of "Documentation/Nightly/Modules/HeterogeneityCAD"
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**'''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.  **'''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.  **'''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.  
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*'''Shape and Morphology Metrics'''  *'''Shape and Morphology Metrics'''  
**'''Volume mm^3: '''The volume of the specified ROI of the image in cubic millimeters.  **'''Volume mm^3: '''The volume of the specified ROI of the image in cubic millimeters.  
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**'''Spherical Disproportion: '''The ratio of the surface area of the image ROI to the surface area of a sphere with the same volume as the image ROI.  **'''Spherical Disproportion: '''The ratio of the surface area of the image ROI to the surface area of a sphere with the same volume as the image ROI.  
**'''Sphericity: '''A measure of the roundness or spherical nature of the image ROI, where the sphericity of a sphere is the maximum value of 1.  **'''Sphericity: '''A measure of the roundness or spherical nature of the image ROI, where the sphericity of a sphere is the maximum value of 1.  
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*'''Renyi Dimensions'''  *'''Renyi Dimensions'''  
**'''BoxCounting Dimension: '''Part of the family of Renyi Dimensions, where q=0 for Renyi Entropy calculations. This represents the fractal dimension or the slope of the curve on a plot of log(N) vs. log(1/s) where 'N' is the number of boxes occupied by the image ROI at each scale, 's', of an overlaid grid.  **'''BoxCounting Dimension: '''Part of the family of Renyi Dimensions, where q=0 for Renyi Entropy calculations. This represents the fractal dimension or the slope of the curve on a plot of log(N) vs. log(1/s) where 'N' is the number of boxes occupied by the image ROI at each scale, 's', of an overlaid grid. 
Revision as of 21:37, 23 July 2014
Home < Documentation < Nightly < Modules < HeterogeneityCAD
For the stable Slicer documentation, visit the 4.10 page. 
Introduction and Acknowledgements
Extension: OpenCAD  
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.

Tutorials
Data sets
Quick Instructions for Use
 Add an image or parameter map (.nrrd file) to the Nodes List
 Select a corresponding segmentation label map to use as ROI
 Click "Apply HeterogeneityCAD"
Image Features and Metrics


 Renyi Dimensions
 BoxCounting Dimension: Part of the family of Renyi Dimensions, where q=0 for Renyi Entropy calculations. This represents the fractal dimension or the slope of the curve on a plot of log(N) vs. log(1/s) where 'N' is the number of boxes occupied by the image ROI at each scale, 's', of an overlaid grid.
 Information Dimension: Part of the family of Renyi Dimensions, where q=1 for Renyi Entropy calculations.
 Correlation Dimension: Part of the family of Renyi Dimensions, where q=2 for Renyi Entropy calculations.
 Geometrical Measures
 Extruded Surface Area: The surface area of the binary object when the image ROI is "extruded" into 4D, where the parameter or intensity value defines the shape of the Fourth dimension.
 Extruded Volume: The volume of the binary object when the image ROI is 'extruded' into 4D, where the parameter or intensity value defines the shape of the Fourth dimension
 Extruded Surface:Volume Ratio: The ratio of the surface area to the volume of the binary object when the image ROI is 'extruded' into 4D, where the parameter or intensity value defines the shape of the Fourth dimension.
 Extruded BoxDimension:
 Texture: GrayLevel Cooccurrence Matrix (GLCM)
 Autocorrelation: A measure of the magnitude of the fineness and coarseness of texture.
\sum_{i=1}^{Ng}\sum_{j=1}^{Ng}{ij\mathbf{P}\(i j)}
 Cluster Prominence: A measure of the skewness and asymmetry of the GLCM. A higher values implies more asymmetry about the mean value while a lower value indicates a peak around the mean value and less variation about the mean.
 Cluster Shade: A measure of the skewness and uniformity of the GLCM. A higher cluster shade implies greater asymmetry.
 Cluster Tendency: Indicates the number of potential clusters present in the image.
 Contrast: A measure of the local intensity variation, favoring P(i,j) values away from the diagonal (i != j), with a larger value correlating with larger image variation.
 Correlation: A value between 0 (uncorrelated) and 1 (perfectly correlated) showing the linear dependency of gray level values in the GLCM. For a symmetrical GLCM, ux = uy (means of px and py) and sigx = sigy (standard deviations of px and py).
 Difference Entropy:
 Dissimilarity:
 Energy (GLCM): Also known as the Angular Second Moment and is a measure of the homogeneity of an image. A homogeneous image will contain less discrete gray levels, producing a GLCM with fewer but relatively greater values of P(i,j), and a greater sum of the squares.
 Entropy(GLCM): Indicates the uncertainty of the GLCM. It measures the average amount of information required to encode the image values.
 Homogeneity 1: A measure of local homogeneity that increases with less contrast in the window.
 Homogeneity 2: A measure of local homogeneity.
 Informational Measure of Correlation 1 (IMC1):
 Informational Measure of Correlation 2 (IMC2):
 Inverse Difference Moment Normalized (IDMN): A measure of the local homogeneity of an image. IDMN weights are the inverse of the Contrast weights (decreasing exponentially from the diagonal i=j in the GLCM). Unlike Homogeneity 2, IDMN normalizes the square of the difference between values by dividing over the square of the total number of discrete values.
 Inverse Difference Normalized (IDN): Another measure of the local homogeneity of an image. Unlike Homogeneity 1, IDN normalizes the difference between the values by dividing over the total number of discrete values.
 Inverse Variance:
 Maximum Probability:
 Sum Average:
 Sum Entropy:
 Sum Variance: Weights elements that differ from the average value of the GLCM.
 Variance (GLCM): The dispersion of the parameter values around the mean of the combinations of reference and neighborhood pixels, with values farther from the mean weighted higher. A high variance indicates greater distances of values from the mean.
 Texture: GrayLevel Run Length Matrix (GLRL)
 Short Run Emphasis (SRE): A measure of the distribution of short run lengths, with a greater value indicative of shorter run lengths and more fine textural textures.
 Long Run Emphasis (LRE): A measure of the distribution of long run lengths, with a greater value indicative of longer run lengths and more coarse structural textures.
 Gray Level NonUniformity (GLN): Measures the similarity of graylevel intensity values in the image, where a lower GLN value correlates with a greater similarity in intensity values.
 Run Length NonUniformity (RLN): Measures the similarity of run lengths throughout the image, with a lower value indicating more homogeneity among run lengths in the image.
 Run Percentage (RP): Measures the homogeneity and distribution of runs of an image for a certain direction
 Low Gray Level Run Emphasis (LGLRE): Measures the distribution of low graylevel values, with a higher value indicating a greater concentration of low graylevel values in the image.
 High Gray Level Run Emphasis (HGLRE): Measures the distribution of the higher graylevel values, with a higher value indicating a greater concentration of high graylevel values in the image.
 Short Run Low Gray Level Emphasis (SRLGLE): Measures the joint distribution of shorter run lengths with lower graylevel values.
 Short Run High Gray Level Emphasis (SRHGLE): Measures the joint distribution of shorter run lengths with higher graylevel values.
 Long Run Low Gray Level Emphasis (LRLGLE): Measures the joint distribution of long run lengths with lower graylevel values.
 Long Run High Gray Level Emphasis (LRHGLE)Measures the joint distribution of long run lengths with higher graylevel values.
Similar Modules
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References
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Information for Developers
Source code: https://github.com/vnarayan13/SlicerOpenCAD