Title
A Nonlinear Variational Model for PET Reconstruction
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.
Year
DOI
Venue
2006
10.1109/ICPR.2006.131
ICPR (4)
Keywords
Field
DocType
poisson distribution,phantom,computer simulation,image reconstruction
Iterative reconstruction,Computer vision,Image noise reduction,Nonlinear system,Computer science,Imaging phantom,Variational model,Positron emission tomography,Image denoising,Artificial intelligence,Poisson distribution
Conference
Volume
Issue
ISSN
4
null
1051-4651
ISBN
Citations 
PageRank 
0-7695-2521-0
0
0.34
References 
Authors
3
2
Name
Order
Citations
PageRank
Jianhua Yan100.34
Jun Yu211120.07