期刊名称：International Journal of Computer Information Systems and Industrial Management Applications
印刷版ISSN：2150-7988
电子版ISSN：2150-7988
出版年度：2014
期号：6
页码：381-390
出版社：Machine Intelligence Research Labs (MIR Labs)
摘要：This paper addresses a comparative analysis of PET Brain image reconstruction based on iterative and weighted least-square (WLS) algorithms. In previous years, the analytical approach was used to reconstruct the Positron Emission Tomography (PET). This approach requires a minimization of a convex cost function and accompanied by many problems related to the computational complexity. The poles apart iteration methods are Conjugate Gradient (CG), Coordinate Descent (CD) and Image Space Reconstruction Algorithm (ISRA). It has many advantages compared to conventional approach. The functional protocol used here is neural network based segmentation of PET brain image using CG method to improve the CG algorithm. In this step of process, the image was segmented using Neural Network and reconstructed with CG algorithm. This statistical fashion can provide better and high PSNR along with lowest noise in the PET Brain image. An assortment of image quality parameters is considered to analyze the PET brain image in this algorithm. The PET brain image is constructed and simulated in MATLAB /Simulink package.
