Depeursinge, A.Sage, D.Hidki, A.Platon, A.Poletti, P.-A.Unser, M.Müller, H.2015-09-182015-09-182015-09-18200710.1109/IEMBS.2007.4353786https://infoscience.epfl.ch/handle/20.500.14299/118134We describe a texture classification system that identifies lung tissue patterns from high-resolution computed tomography (HRCT) images of patients affected with interstitial lung diseases (ILD). This pattern recognition task is part of an image-based diagnostic aid system for ILDs. Five lung tissue patterns (healthy, emphysema, ground glass, fibrosis and microdules) selected from a multimedia database are classified using the overcomplete discrete wavelet frame decompostion combined with grey-level histogram features. The overall multiclass accuracy reaches 92.5% of correct matches while combining the two types of features, which are found to be complementary.text::conference output::conference proceedings::conference paper