A Distributed Artificial Immune Network for Optimizing Tracer Kinetic Models with MATLAB Distributed Computing Engine

Artificial immune network (AIN) as a branch of artificial immune system has been widely used in many application fields, and shows good ability of global optimization, especially in parameters optimization of the pharmacokinetic models. The search process of AIN for global optimum is based on the principles of clonal selection and immune network. However, as one of the heuristic-based optimal algorithms, the evolution of memory cells in the AIN is more time consuming compared with gradient-based optimal algorithms. In this paper, an AIN with distributed clonal selection strategy is proposed to improve the efficiency of the AIN. Then the distributed AIN is implemented with MATLAB Distributed Computing Engine (MDCE). One of the advantages of MDCE is that it is convenient to run optimal algorithms programmed with MATLAB platform. In the experiments, parameters of the [ 18 F] Fluoro-2-deoxy2D-glucose (FDG) tracer kinetic model are optimized with the distributed AIN algorithms, theory analysis and experiments results indicate the algorithm is capable of improving search speed significantly in successful rate and algorithm stability.