Medical Image Enhancement Algorithm Based On Artificial Immune Algorithm

In recent years, as a young research field, artificial immune system (AIS) is very active andhas become an important branch of computer science. Based on mechanism and characteristics ofbiological immune system, AIS can solve the problems of engineering calculation and informationsystems. AIS is originated in the expanding of immunology theory. People attempt to simulate themechanism if biological immune system to solve the problems of computer security, faultdiagnosis and industrial control. This paper discusses the algorithm of medical image processingbased on artificial immune system.In this paper, MRI brain images in Harvard whole brain database is the main object. Inmedicine, the disease’s location and shape can be separated from the MRI image, whichdetermines the accuracy of the clinical diagnosis. So the accuracy is important for pathogens,diagnosis and treatment.In medical imaging system, however, due to image acquisition devices existing disturbanceand the influence of the surrounding environment, medical images are always with noise anddistortion. This caused the decreasing of the images’ quality, affected the accuracy of imageinformation. The image quality sometimes can’t meet the requirements of clinical application.Therefore, we usually need to take some measures to improve image quality. The measures forimage enhancement technique namely provide reliable guarantee for follow-up medical diagnosticanalysis.This paper discusses the principle of artificial immune system, detailed introduces someimportant theories of artificial immune system, such as: antigen, antibody, immune recognition,learning, immune memory and clonal selection, etc. In this paper, it introduces the basic artificialimmune algorithm, including the negative selection algorithm, clonal selection algorithm and thenormal model algorithm. And then, an improved clonal selection algorithm is introduced. At thesame time, it expounds the principle and processing of the commonly used method of imageenhancement, including gray level transformation method, frequency domain processing methodsand spatial processing method. This paper introduces some basic enhancement methods that arecommonly used in medical image enhancement, and has carried on the simulation with MATLABR2010a in Windows7. The process of artificial immune algorithm using in image enhancementand the possibilities of application are also been discussed in this paper. Aiming at the defects ofexisting artificial immune algorithm, this paper puts forward an improved algorithm based onclonal selection principle and the algorithm has been applied to image enhancement. In this paper,actual images are used for simulation with MATLAB R2010a platform, the simulation results are given and the results are analyzed. Finally, the experimental results are compared with those of theprevious algorithm.