Tsallis entropy-based prior for PET reconstruction.
- Author:
Yuanyuan GAO
1
;
Lijun LU
;
Jianhua MA
;
Zhaoying BIAN
;
Qingwen LU
;
Lei CAO
;
Shaoying GAO
Author Information
1. School of Biomedical Engineering, Southern Medical University , Guangzhou 510515, China.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Artifacts;
Entropy;
Image Processing, Computer-Assisted;
methods;
Phantoms, Imaging;
Positron-Emission Tomography;
methods
- From:
Journal of Biomedical Engineering
2013;30(3):455-459
- CountryChina
- Language:Chinese
-
Abstract:
Maximum a Posteriori (MAP) method has been widely applied to the ill-posed problem of image reconstruction. The choice of prior is the crucial point on MAP methods. However, the most conventional priors will lead to a blurring of the whole image or cause ladder-like artifacts. We therefore proposed a Tsallis entropy-based prior for positron emission tomography (PET) iterative reconstruction in MAP framework. The method uses a Tsallis entropy-based prior to eliminate the uncertainty between prior information and the estimated images. We tested this method in the phantom image, compared it with the traditional prior methods. the results showed that the proposed algorithm could suppress noise and obtain better reconstructed image quality.
