Fractal analysis in digital histology
Digital images are increasingly used in medicine, especially in digital pathology. Histological techniques are well established and modern digitalization systems yield high resolution digital images. Evaluation of these images is regularly accomplished by subjective inspection, but objective or numerical methods are still rare. Biological patterns and textures are mathematically hard to measure or to simulate and therefore, fractal methods and non-Euclidean geometry are very suitable to solve these tasks.
Digital images inherently have many advantages and fractal measures can be calculated by various methods, but care has to be taken in order to gain reliable and robust results. Digital images are discrete representations of specimen and can be noisy. Furthermore, an image is not always totally filled by the specimen and consequently background pixels must be considered, too. If appropriately considered, these issues do not decline the power of fractal analyses.