Medical signal processing by means of immune algorithms

Medical signals are increasingly being used within healthcare for diagnosis, planning treatment, guiding treatment and monitoring disease evolution. Medical imaging mainly treats and processes missing, ambiguous, complementary, redundant, contradictory, distorted data, and information has a strong structural character. This paper reports two “immune algorithms” based approaches for medical signal processing. Immune algorithms belong to the Artificial Immune Systems field. The first proposed approach uses the Clonal Selection Algorithm (CSA) for geometric transform estimation in image registration (IR). The second approach, the Dendritic Cell Algorithm (DCA) is used for automatic driver stress detection using biomedical signals.