Evaluation of several quantum genetic algorithms in medical image registration applications

Registration is an important problem and a fundamental task in image processing. Recently, quantum-inspired evolutionary algorithms(QEA) have been proposed and applied to many optimization problems. However, few people study the application of QEA for image registration. This paper evaluate three kinds of QGAs in medical image registration applications, in which QGAs are implemented to find approximate solutions that maximizes the maximum mutual information(MI), and the experimental results are compared and analyzed.