NDLI: A comparison study of low-dose CT image reconstruction strategies by adapted weighted total variation regularization

Content Provider	IEEE Xplore Digital Library
Author	Yan Liu Jianhua Ma Hao Zhang Jing Wang Zhengrong Liang
Copyright Year	2012
Description	Author affiliation: Depts. of Radiol. & Electr. & Comput. Eng., Stony Brook Univ., Stony Brook, NY, USA (Yan Liu) \|\| Depts. of Radiol., Comput. Sci. & Biomed. Eng., Stony Brook Univ., Stony Brook, NY, USA (Zhengrong Liang) \|\| Depts. of Radiol. & Biomed. Eng., Stony Brook Univ., Stony Brook, NY, USA (Hao Zhang) \|\| Dept. of Radiol., Stony Brook Univ., Stony Brook, NY, USA (Jianhua Ma) \|\| Dept. of Radiat. Oncology, Univ. of Texas Southwestern Med. Center at Dallas, Dallas, TX, USA (Jing Wang)
Abstract	This paper aims to investigate the iterative reconstruction problem of low-dose computed tomography (LDCT) by adapted weighted total variation (AwTV) regularization. The motivation is based on the observation that statistical iterative reconstruction (SIR) has shown improvement of image quality in reconstruction from low-mA cone-beam CT (CBCT). More specifically, the iterative algorithm of projection onto convex set with total variation regularization (TV-POCS) has demonstrated the gains in image reconstruction from sparse angle projection data for LDCT imaging. Two approaches related to the sparse concept for LDCT imaging were investigated, one is AwTV constrained penalized weighted least-squares (AwTV-PWLS) and the other is AwTV-POCS. These two approaches were compared by experimental data from $CatPhan^{®}$ 600 phantom and anthropomorphic head phantom at the following conditions: (1) low-mA full view projection data, (2) normal-mA sparse view projection data, and (3) low-mA sparse view projection data. The comparison was based on the visualization evaluation and the quantitative measurements using the contrast-to-noise ratios (CNRs) merit and full-width at half-maximum measurement (FWHM) on selected regions-of-interest (ROIs) from the reconstructed images. The results indicated that the AwTV-PWLS approach can outperform the AwTV-POCS for condition (1) at 10 mA level, while the AwTV-POCS algorithm has advantages for condition (2) at 80 mA level. Under the condition (3) at 10 mA level, both approaches could not yield satisfactory images. These results concur with the expectation from the theoretical models of these two approaches. The AwTV-PWLS emphasizes the data fidelity term with weighted TV penalty and is more robust for data noise while the AwTV-POCS emphasizes the sparsity nature and requires good data constraints. While the AwTV-POCS seems to serve the purpose of weighted TV minimization, a remaining open question for AwTV-PWLS is whether the weighted TV penalty is an optimal choice for the PWLS minimization. Further evaluation is needed to answer this open question.
Sponsorship	IEEE Nucl. Plasma Sci. Soc
Starting Page	2456
Ending Page	2462
File Size	2424984
Page Count	7
File Format	PDF
ISBN	9781467320283
ISSN	10823654
e-ISBN	9781467320306
DOI	10.1109/NSSMIC.2012.6551559
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Content Type	Text
Resource Type	Article

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