期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2013
卷号：10
期号：1
出版社：IJCSI Press
摘要：Segmentation is applied in medical images when the brightness of the images becomes weaker so that making different in recognizing the tissues borders. Thus, the exact segmentation of medical images is an essential process in recognizing and curing an illness. Thus, it is obvious that the purpose of clustering in medical images is the recognition of damaged areas in tissues. Different techniques have been introduced for clustering in different fields such as engineering, medicine, data mining and so on. However, there is no standard technique of clustering to present ideal results for all of the imaging applications. In this paper, a new method combining genetic algorithm and k-means algorithm is presented for clustering medical images. In this combined technique, variable string length genetic algorithm (VGA) is used for the determination of the optimal cluster centers. The proposed algorithm has been compared with the k-means clustering algorithm. The advantage of the proposed method is the accuracy in selecting the optimal cluster centers compared with the above mentioned technique.
