Abstract: A method for analyzing a three-dimensional (3D) image representative of an initial volume of interest (VOI) containing a lesion is disclosed. The 3D image has an associated binary map having voxels associated with a thresholded variance map of the initial VOI. The initial VOI has boundaries that may be defined by a cube. A final VOI is determined that is less than the initial VOI, where the final VOI is a function of the number of transitions from a boundary voxel to a filtered voxel at an outer boundary of the lesion. The final VOI is then analyzed to determine a nodule consistency class, classified based upon the computed nodule consistency class by applying a voxel-clustering algorithm, and displayed with respect to three classifications of tissue.

Abstract: A method for analyzing a three-dimensional (3D) image representative of an initial volume of interest (VOI) containing a lesion is disclosed. The 3D image has an associated binary map having voxels associated with a thresholded variance map of the initial VOI. The initial VOI has boundaries that may be defined by a cube. A final VOI is determined that is less than the initial VOI, where the final VOI is a function of the number of transitions from a boundary voxel to a filtered voxel at an outer boundary of the lesion. The final VOI is then analyzed to determine a nodule consistency class, classified based upon the computed nodule consistency class by applying a voxel-clustering algorithm, and displayed with respect to three classifications of tissue.