Abstract:

This article investigates the suitability of local intensity distributions to analyze six emphysema classes in 342 CT scans obtained from 16 sites hosting scanners by 3 vendors and a total of 9 specific models in subjects with Chronic Obstructive Pulmonary Disease (COPD). We propose using kernel density estimation to deal with the inherent sparsity of local intensity histograms obtained from scarcely populated regions of interest. We validate our approach by leave-one-subject-out classification experiments and full-lung analyses. We compare our results with recently published LBP texture-based methodology. We demonstrate the efficacy of using intensity information alone in multi-scanner cohorts, which is a simpler, more intuitive approach.