Title :
A Nonlinear Variational Model for PET Reconstruction
Author :
Yan, Jianhua ; Yu, Jun
Author_Institution :
Dept. of Electron. Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan
Abstract :
PET image was often influenced by noise. In this paper, we proposed a nonlinear variational model for improving reconstruction of PET images. The use of variational model was due to its effectiveness for reducing noise in 2D images while preserving edges. Our results indicated that the proposed method application to computer-simulated and real PET phantom outperformed the conventional method in terms of both visual quality and quantitative accuracy
Keywords :
Poisson distribution; Radon transforms; image denoising; image reconstruction; medical image processing; positron emission tomography; variational techniques; PET image reconstruction; edge preservation; image noise reduction; nonlinear variational; phantom; Application software; Computer applications; Detectors; Electron emission; Event detection; Image reconstruction; Imaging phantoms; Iterative algorithms; Noise reduction; Positron emission tomography;
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2521-0
DOI :
10.1109/ICPR.2006.131
