DocumentCode :
2555213
Title :
A comparison study of low-dose CT image reconstruction strategies by adapted weighted total variation regularization
Author :
Yan Liu ; Jianhua Ma ; Hao Zhang ; Jing Wang ; Zhengrong Liang
Author_Institution :
Depts. of Radiol. & Electr. & Comput. Eng., Stony Brook Univ., Stony Brook, NY, USA
fYear :
2012
fDate :
Oct. 27 2012-Nov. 3 2012
Firstpage :
2456
Lastpage :
2462
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 - eighted TV penalty is an optimal choice for the PWLS minimization. Further evaluation is needed to answer this open question.
Keywords :
computerised tomography; image denoising; image reconstruction; iterative methods; medical image processing; minimisation; phantoms; statistical analysis; AwTV constrained penalized weighted least-squares; AwTV-POCS algorithm; AwTV-PWLS; CBCT; CNR; CatPhan 600 phantom; FWHM; LDCT imaging; PWLS minimization; adapted weighted total variation regularization; anthropomorphic head phantom; contrast-to-noise ratios; convex set; data constraints; data fidelity term; data noise; full-width at half-maximum measurement; image quality; image reconstruction; iterative reconstruction problem; low-dose CT image reconstruction; low-dose computed tomography; low-mA cone-beam CT; low-mA sparse view projection data; low-rnA full view projection data; normal-mA sparse view projection data; quantitative measurements; sparse angle projection data; statistical iterative reconstruction; theoretical models; visualization evaluation; weighted TV minimization; weighted TV penalty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2012 IEEE
Conference_Location :
Anaheim, CA
ISSN :
1082-3654
Print_ISBN :
978-1-4673-2028-3
Type :
conf
DOI :
10.1109/NSSMIC.2012.6551559
Filename :
6551559
Link To Document :
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