Method of automatic ROI selection on lung CT images

We developed a method of automatic ROI selection on two-dimensional slices of computed tomography of the lungs for further computer diagnostics of emphysema. The method is based on a greedy forward selection using local texture features as an indicator of similarity with regions of interest from the learning sample. An experimental study of the method was performed on the set of 160 real digital images. The estimation of the error probability with automatic ROI selection was 0.03, which is less than in the case of manual selection.