A method for identifying an object represented in image data comprising a selected image slice generated by a radiographic examination, characterized by: applying a Fourier transform to at least a portion of the selected image slice to generate a 2-dimensional Fourier domain image; generating a one-dimensional spectral signature of the object using the Fourier domain image by computing a magnitude of the 2-dimensional Fourier domain image at respective voxels, and computing a standard deviation of the magnitude of the 2-dimensional Fourier domain image along circles with different radial frequency dimensions, wherein the radial frequency dimension corresponds to the radius of the circle and wherein the circles are centered at the origin of the Fourier domain image, wherein a x-axis of the one-dimensional spectral signature is indicative of the radial frequency dimension and a y-axis of the one-dimensional spectral signature is indicative of the standard deviation of the magnitude of the Fourier domain image located along the circle with the corresponding radius; extracting features from the one-dimensional spectral signature; and comparing the features extracted from the one-dimensional spectral signature to corresponding features for a known object to determine a probability that the object is granular, the probability utilized to identify the object. applying a Fourier transform to at least a portion of the selected image slice to generate a 2-dimensional Fourier domain image; generating a one-dimensional spectral signature of the object using the Fourier domain image by computing a magnitude of the 2-dimensional Fourier domain image at respective voxels, and computing a standard deviation of the magnitude of the 2-dimensional Fourier domain image along circles with different radial frequency dimensions, wherein the radial frequency dimension corresponds to the radius of the circle and wherein the circles are centered at the origin of the Fourier domain image, wherein a x-axis of the one-dimensional spectral signature is indicative of the radial frequency dimension and a y-axis of the one-dimensional spectral signature is indicative of the standard deviation of the magnitude of the Fourier domain image located along the circle with the corresponding radius; computing a magnitude of the 2-dimensional Fourier domain image at respective voxels, and computing a standard deviation of the magnitude of the 2-dimensional Fourier domain image along circles with different radial frequency dimensions, wherein the radial frequency dimension corresponds to the radius of the circle and wherein the circles are centered at the origin of the Fourier domain image, wherein a x-axis of the one-dimensional spectral signature is indicative of the radial frequency dimension and a y-axis of the one-dimensional spectral signature is indicative of the standard deviation of the magnitude of the Fourier domain image located along the circle with the corresponding radius; extracting features from the one-dimensional spectral signature; and comparing the features extracted from the one-dimensional spectral signature to corresponding features for a known object to determine a probability that the object is granular, the probability utilized to identify the object.