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A multiscale sparse representation scheme based on wavelet and contourlet transforms is employed to describe four patterns of diffuse lung disease patterns: normal, emphysema, ground glass opacity (GGO) and honey-combing based on HRCT lung images. First, using sparse representation, four discriminative dictionaries are trained for the four patterns respectively. After that, in the classification phase,...
A novel algorithm is presented for classification of four patterns of diffuse lung disease: normal, emphysema, honeycombing and ground glass opacity, on the basis of textural analysis of high resolution computed tomography (HRCT) lung images. The algorithm incorporates scale-space features based on Gaussian derivative filters and multi-dimensional multi-scale features based on wavelet and contourlet...
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