A New Method for Medical Image Clustering Using Genetic Algorithm
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.
Keywords: Medical Image, Clustering, Genetic Algorithm, K-means.
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ABOUT THE AUTHORS
Akbar Shahrzad Khashandarag
was born in Tabriz, Iran, in 1978. He received the B.Sc. degree in computer engineering from the Islamic Azad University Bonab Branch, Iran in 2009. He is currently M.Sc. student in Mechatronics engineering at the Islamic Azad University Tabriz Branch. His research interests include image processing, signal processing and wireless sensor network.
Mirkamal Mirnia
received the B.Sc. degree in mathematical Physics from Ferdowsi University, Mashhad, Iran in 1967, and M.Sc. degree in pure mathematics from teacher training University of Tehran in 1969 also M.Sc. degree in numerical analysis and computing from Owen university of Manchester, UK in 1975 and PhD. in applied mathematics (optimization) from university of St.Andrews, UK in 1979. He is a member of the Mathematical society of Iran, Iranian operations researches, institute of applied mathematics, UK and member of SIAM.
Aidin Sakhavati
was born in Orumieh, Iran, in 1978. He received his BS, MS and Ph.D. degrees in 2000, 2003 and 2010 from Islamic Azad university-Tabriz branch (IAUT), and Tabriz University, Tabriz, Iran, and Islamic Azad University, science and research branch, Tehran, Iran, respectively. He has been holding the Assistant Professor position at IAUT since 2010. He is the author of more than 30 journal and conference papers. His teaching and research interest include power system and transformers transients and power electronics applications in power systems. His researching interests include power systems dynamic and control application of Quantitative Feedback Theory, Particle Swarm Optimization and Genetic Algorithm in FACTS devices and Load Frequency control.
Akbar Shahrzad Khashandarag
was born in Tabriz, Iran, in 1978. He received the B.Sc. degree in computer engineering from the Islamic Azad University Bonab Branch, Iran in 2009. He is currently M.Sc. student in Mechatronics engineering at the Islamic Azad University Tabriz Branch. His research interests include image processing, signal processing and wireless sensor network.
Mirkamal Mirnia
received the B.Sc. degree in mathematical Physics from Ferdowsi University, Mashhad, Iran in 1967, and M.Sc. degree in pure mathematics from teacher training University of Tehran in 1969 also M.Sc. degree in numerical analysis and computing from Owen university of Manchester, UK in 1975 and PhD. in applied mathematics (optimization) from university of St.Andrews, UK in 1979. He is a member of the Mathematical society of Iran, Iranian operations researches, institute of applied mathematics, UK and member of SIAM.
Aidin Sakhavati
was born in Orumieh, Iran, in 1978. He received his BS, MS and Ph.D. degrees in 2000, 2003 and 2010 from Islamic Azad university-Tabriz branch (IAUT), and Tabriz University, Tabriz, Iran, and Islamic Azad University, science and research branch, Tehran, Iran, respectively. He has been holding the Assistant Professor position at IAUT since 2010. He is the author of more than 30 journal and conference papers. His teaching and research interest include power system and transformers transients and power electronics applications in power systems. His researching interests include power systems dynamic and control application of Quantitative Feedback Theory, Particle Swarm Optimization and Genetic Algorithm in FACTS devices and Load Frequency control.
