An improved prior image constrained compressed sensing reconstruction for low-dose computed tomography.
- Author:
Hong GUO
1
;
Zhaoying BIAN
;
Jing HUANG
;
Jianhua MA
Author Information
1. Department of Radiology, General Hospital, Tianjin Medical University, Tianjin 300052, China.E-mail: guohong99@163.com.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Computer Simulation;
Data Compression;
methods;
Image Processing, Computer-Assisted;
methods;
Least-Squares Analysis;
Phantoms, Imaging;
Radiation Dosage;
Signal-To-Noise Ratio;
Tomography, X-Ray Computed;
methods
- From:
Journal of Southern Medical University
2013;33(11):1620-1623
- CountryChina
- Language:Chinese
-
Abstract:
Low-dose computed tomography (CT) reconstruction has become the focus of X-ray CT imaging study. In this paper, we propose an improved prior image constrained compressed sensing (PICCS) reconstruction approach. A penalized weighted least-squares approach was adopted to realize the line integral projection (sinogram) data restoration, followed by filtered back-projection (FBP) of the restored sinogram data for image reconstruction. Finally, the FBP image as the prior image was used for PICCS approach for dose reduction. Qualitative and quantitative evaluations were carried out with computer simulation. The results showed that the present approach yielded noticeable gains over the original PICCS approach for dose reduction in terms of noise-induced artifacts suppression and edge detail preservation.
