An improved prior image constrained compressed sensing reconstruction for low-dose computed tomography
GUO Hong
BIAN Zhaoying
HUANG Jing
MA Jianhua
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.
Keywords：X-ray CTlow-doseprior informationpenalized weighted least-squarescompressed sensing
Publication Date：2013-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 1620-1623 )