Radiographic measurements of foot deformities are used to determine, among other things, such conditions as flatfoot, high arch, or calcaneal fracture. Those measurements are achieved by estimating four angles. Manual assessment of those angles is time-consuming not to mention inevitable errors of such approximation. To the best of the authors knowledge, currently there is no research focusing on finding those four angles. In this paper an algorithm for automatic assessment of those angles, based on extremely randomized trees, is being proposed. Moreover this diagnostic assisting system was intended to be as generic as possible and could be applied, to some degree, to other similar problems. To demonstrate usefulness of this method, correlations of automated measurements with manual ones against correlations of manual measurements with manual ones are being compared. The significance level for manual-manual measurements comparison is less than 0.001 in case of all four angles. The significance level for automated-manual measurements comparison is also less than 0.001 in all cases. The results show that the search for the aforementioned angles can be automated. Even with the use of a generic algorithm a high degree of precision can be achieved, allowing for a more efficient diagnosis.

The research was intended to solve the travelling salesman problem by means of genetic algorithms. The implementation of the algorithm was by virtue of CUDA technology. The research was focused on checking how much the system can improve if instead of classical CPU processors one uses GPU graphical processors enabled to perform the operations parallel. The algorithm was implemented in the high level CUDA C language. Thus, measuring the pure time of performance of the algorithm could be the single but reliable point of comparison between two above mentioned types of processors. Making some operations mutually independent and using CUDA technology makes the task much faster to execute. Due to it complex issues can be solved in a shorter time.

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