. Author manuscript; available in PMC: 2014 Feb 14.

Published in final edited form as: IEEE Trans Med Imaging. 2012 Aug 7;31(10):1965–1976. doi: 10.1109/TMI.2012.2211887

Table 1.

One hundred and fifty-seven automated tumor features were computed for the tumor candidates. Edge refers to the two pixel-wide band of liver tissue surrounding the tumor.

3D Features	Descriptor	Explanation
Tumor Volume	Size	Volumetric size.
Tumor Diameter	Size	Linear size
Tumor Size Region Ratio	Shape	Ratio of the size of the object bounding box and the real size of the object
Tumor Binary Elongation	Shape	Ratio of the largest principal moment by the smallest principal moment
Tumor Roundness	Shape	Sphericity
Tumor Hessian Eigenvalues	Shape	Local extrema and stationary points
Tumor Blobness Measures	Shape	Roundness from the Hessian eigenvalues
Tumor Intensity^*	Enhancement	Enhancement of tumor
Edge Intensity^*	Enhancement	Enhancement of healthy parenchyma
Tumor Cluster Prominence^*	Texture	Skewness / asymmetry
Edge Cluster Prominence^*	Texture	Skewness / asymmetry
Tumor Cluster Shade^*	Texture	Skewness / asymmetry
Edge Cluster Shade^*	Texture	Skewness / asymmetry
Tumor Correlation^*	Texture	Correlation / complexity
Edge Correlation^*	Texture	Correlation / complexity
Tumor Energy^*	Texture	Uniformity
Edge Energy^*	Texture	Uniformity
Tumor Entropy^*	Texture	Randomness
Edge Entropy^*	Texture	Randomness
Tumor Haralick Correlation^*	Texture	Linear dependence between the voxels relative to each other.
Edge Haralick Correlation^*	Texture	Linear dependence between the voxels relative to each other.
Tumor Inertia^*	Texture	Local heterogeneity
Edge Inertia^*	Texture	Local heterogeneity
Tumor Inverse Difference Moment^*	Texture	Local homogeneity
Edge Inverse Difference Moment^*	Texture	Local homogeneity

indicates that the min, max, mean, standard deviation, variance, median, kurtosis and skewness were computed for the feature. For definitions of the texture features computed from the co-occurrence matrix please refer to [19].