
Proceedings Paper
Implementation of an effective KL domain penalized weighted least-squares sinogram restoration for low-dose CT colonographyFormat | Member Price | Non-Member Price |
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Paper Abstract
Currently available spiral/helical computed tomography (HCT) technologies have demonstrated the potential for CTbased
virtual colonoscopy or CT-colonography (CTC). However, a major limitation for this clinical application is
associated with the risk of high radiation exposure, especially for its use for screening purpose at a large population. In
this work, we presented an improved Karhunen-Loeve (KL) domain penalized weighted least-squares (PWLS) strategy
which considers the data correlation among the nearby angular views and nearby axial slices simultaneously so that a
fully three-dimensional (3D) restoration problem can be reduced to a 1D operation and therefore an analytical calculation
is feasible for highest computing efficiency. The KL-PWLS strategy was implemented and tested on computer
simulated sinograms which mimic low-dose CT scans at different noise levels characterized by 50, 40, 30, 20 and 10
mAs respectively. The reconstructed images by the presented strategy demonstrated the potential of ultra low-dose CT
at as low as 10 mAs for VC application. Further evaluation by receiver operating characteristic study is needed and is
under progress.
Paper Details
Date Published: 13 March 2009
PDF: 7 pages
Proc. SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging, 725856 (13 March 2009); doi: 10.1117/12.811670
Published in SPIE Proceedings Vol. 7258:
Medical Imaging 2009: Physics of Medical Imaging
Ehsan Samei; Jiang Hsieh, Editor(s)
PDF: 7 pages
Proc. SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging, 725856 (13 March 2009); doi: 10.1117/12.811670
Show Author Affiliations
Hongbing Lu, Fourth Military Medical Univ. (China)
Zhengrong Liang, Stony Brook Univ. (United States)
Zhengrong Liang, Stony Brook Univ. (United States)
Published in SPIE Proceedings Vol. 7258:
Medical Imaging 2009: Physics of Medical Imaging
Ehsan Samei; Jiang Hsieh, Editor(s)
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