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Abstract

A method and system for automated analysis of digital radiographic images in which regions-of-interest (ROI's) are first determined, and subsequently analyzed for abnormalities. To locate the ROI's, the outer ribcage and midline boundary locations of the chest image are determined from the digital image data. Vertical profiles are then selected and background trend is then removed from each vertical profile. A shift-variant sinusoidal function is fitted to each vertical profile and ROI's are selected based on the fitted functions. The non-uniform background trend is removed from the original image data of each selected ROI to obtain corrected data. The power spectrum of the lung texture is obtained from the 2D Fourier transform of the corrected data and is filtered by the human visual response. Finally, the root-mean-square (rms) variation, R, and the first moment of the power spectrum, M, are determined as quantitative texture measures for the magnitude and coarseness (or fineness), respectively, of the lung texture.

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