Feature selection and classification of breast MRI lesions based on multi classifier

This paper aims to increase the classification specificity by using multi classifier system. First, a novel pixel search approach is applied to find significant region in images. Fuzzy C-means is utilized to determine the clear boundary of tumor. Then, shape and texture features are extracted from region of interest. Genetic algorithm is applied to select the best feature used for classifiers. Several neural networks and support vector machine are considered as classifiers that classify the data into benign and malignant group. To improve the performance of classification, three classifiers that have the best results among all applied methods are combined together that they have been named as multi classifier system. For each lesion, final detection as malignant or benign has been evaluated, when the same results are achieved from two classifiers of multi classifier system. Notice that the Jack-Knife technique is applied in this study, because it is useful for small data base as ours gotten from Milad Hospital in Tehran, Iran.