Texture classification of SARS infected region in radiographic image

In this paper, we conduct the first study on SARS radiographic image processing. In order to distinguish SARS infected regions from normal lung regions using texture features, we propose several improvements to the traditional gray-level co-occurrence texture features (R. M. Haralick et al., 1973). We use a multi-level feature selection approach to extract texture features from a multi-resolution region based co-occurrence matrix directly for texture classification. The selected texture features can preserve most of the discriminant information in the texture image. Satisfactory results are obtained on a large set of chest radiographic images of SARS patients.