Preparing initial population of genetic algorithm for region growing parameter optimization

The processing of microscopic tissue images is nowadays done more and more using special immunodiagnostic-evaluation software products. Often to evaluate the samples, the first step is determining the number and location of cell nuclei. To do this, one of the most promising methods is the region growing, but this algorithm is very sensitive to the appropriate setting of different parameters. Due to the large number of parameters and due to the big set of possible values setting those parameters manually is a quite hard task, so we developed a genetic algorithm to optimize these values. The first step of the development is the statistical analysis of the parameters, and the determination of the important features, to extract valuable information for a to-be-implemented genetic algorithm that will perform the optimization.