Early recognition of lung´s air sacs wall collapsing

The paper discusses the possibility of applying a non-liner analysis approach on air density distribution within lung airways tree at any level of branching1. Computed Tomography (CT) 2 source images of the lung are subjected to two phases of treatment in order to produce a fractal coefficient of the air density distribution. In the first phase, raw pixel values from source images, corresponding to all possible air densities, are processed by a software tool, developed in order to, construct a product image. This is done through Cascading Elimination of Unwanted Elements (CEUE): a preprocessing analysis step of the source image. It identifies values of air density within the airways tree, while eliminating all non-air-density values. Then, during the second phase, in an iterative manner, a process of Resolution Diminution Iterations (RDI) takes place. Every resolution reduction produces a new resultant histogram. A resultant histogram is composed of a number of peaks, each of which corresponding to a cluster of air densities. A curve is plotted for each resolution reduction versus the number of peaks counted at this particular resolution. It permits the calculation of the fractal dimension from the regression slope of log-log power law plot.