Application of communication ant colony optimization for lymph node classification

In recent years, ultrasound imaging was widely used in the diagnosis of lymph nodes. Most lymph nodes tend to have various internal echogenicities in the sonogram, which makes a definite diagnosis difficult. To overcome this problem, we propose a new image feature selection method based on ant colony optimization (ACO) for different imaging systems. The selected significant features are then applied to classify lymph node into six categories by support vector machine (SVM). Experimental results show that the proposed approach has high accuracy.