Title :
Improved immune algorithm for medical image enhancement
Author :
Tao Gong;Tiantian Fan;Lei Pei;Zixing Cai
Author_Institution :
College of Information Science and Technology, Engr. Research Center of Digitized Textile & Fashion Tech., for Ministry of Education, Donghua University, Shanghai 201620, China
fDate :
7/1/2015 12:00:00 AM
Abstract :
Traditional clonal selection algorithm gives us some inspiration for many applications, but in the medical image enhancement application we found some defects of this algorithm. So we improved the clonal selection algorithm in three ways. First, we designed the real coding of the MRI brain image, instead of binary coding. Second, we added the mutation distance to control the mutation progress and avoid only the local optimization. In addition, we adjust the clone selection and the mutation together in the Gauss distribution, the uniform distribution, and the chaotic distribution, rather than in only the Gauss distribution. Then we use the real MRI brain images to test the image enhancement of our improved clonal selection algorithm. The experimental results show that our approach outperform the median filtering (MF) and the adaptive template filtering (ATF) in enhancing the MRI brain images.
Keywords :
"Magnetic resonance imaging","Brain","Biomedical imaging","Image enhancement","Algorithm design and analysis","Cloning","Filtering"
Conference_Titel :
Artificial Immune Systems (AIS), 2015 International Workshop on
DOI :
10.1109/AISW.2015.7469241