Selecting regional features in ultrasound images of lymph nodes is important for clinical diagnosis. Most of the current feature selection algorithms are time-consuming and lead easily to a premature convergence. In this paper

a new novel discrete differential evolution (DDE) algorithm based on virus-evolution is presented to solve the cervical lymph nodes features selection problem.We call it virus-evolutionary discrete differential evolution (VEDDE) algorithm. Biological virus mechanism and the infection-based operation between host and virus are introduced in the DDE which can maintain the diversity of individuals while retaining the best search information and improve the fitness function value and the speed of evolution. The proposed algorithm has been tested on many clinical ultrasound images of cervical lymph nodes. The classification accuracy is 98% and the average number of iterations is only 30 times

which indicates that the proposed algorithm is valid.