Medical Images Classification Based on Least Square Support Vector Machines

The paper proposed a novel method for breast cancer detection using least square support vector machines. To overcome the high computational complexity of traditional support vector machines, recently a new technique, the least square SVM (LSSVM) has been introduced. In this method LSSVM simplifies the required computation to solving linear equation set. This equation set embodies all available information about the learning process. The traditional support vector machines algorithm is improved. Experiments on images of mammography with different noise levels were conducted and results show that the proposed method is able to classify the breast cancer in the images of mammography with high precision. In application of this method the cost and time of computation can also be reduced.