Abstract: Application of the Adaptive Multiple Feature Method (AMFM) to identify early changes in a smoking population is discussed. This method was specifically applied to determine if differences in CT images of smokers (with normal lung function) and non-smokers (with normal lung function) could be found through computerized texture analysis. Results demonstrated that these groups could be differentiated with over 80.0% accuracy. Further, differences on CT images between normal appearing lung from non-smokers (with normal lung function) and normal appearing lung from smokers (with abnormal lung function) were also investigated. These groups were differentiated with over 89.5% accuracy. In analyzing the whole lung region by region, the AMFM characterized 38.6% of a smoker lung (with normal lung function) as mild emphysema. We can conclude that the AMFM detects parenchymal patterns in the lungs of smokers which are different from normal patterns occurring in healthy non-smokers. These patterns could perhaps indicate early smoking-related changes. !7
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