Fractal analysis for discrimination of overlapped structures in radiological images

A quantitative methodology for the analysis of pulmonary radiological images by using the fractal approach to texture analysis is proposed. Through the analysis of the fractal distribution, some parameters are defined; the histogram is identified with Gaussian and Rayleigh-like functions, in the case of real pulmonary tissue, simulated pathologies, and their overlapped images. By analyzing the superimposition of pathological tissues upon normal ones, it is generally found that the average fractal dimension exhibits an intermediate value between those of the two isolated tissues. Analogously, the variance of an overlapping structure has a value ranging between those for the two original tissues. Since the fractal dimension seems to be more discriminant than intensity information, segmentation can be applied to the extracted images, thus making it possible to isolate normal from pathological areas in the same radiological image.<>