Noise Reduction for Low-Dose Single-Slice Helical CT Sinograms.
Helical computed tomography (HCT) has several advantages over conventional step-and-shoot CT for imaging a relatively large object, especially for dynamic studies. However, HCT may increase X-ray exposure significantly. This work aims to reduce the radiation by lowering X-ray tube current (mA) and filtering low-mA (or dose) sinogram noise of HCT. The noise reduction method is based on three observations on HCT: (1) the axial sampling of HCT projections is nearly continuous as detection system rotates; (2) the noise distribution in sinogram space is nearly a Gaussian after system calibration (including logarithmic transform); and (3) the relationship between the calibrated data mean and variance can be expressed as an exponential functional across the field-of-view. Based on the second and third observations, a penalized weighted least-squares (PWLS) solution is an optimal choice, where the weight is given by the mean-variance relationship. The first observation encourages the use of Karhunen-Loève (KL) transform along the axial direction because of the associated correlation. In the KL domain, the eigenvalue of each principal component and the derived data variance provide the signal-to-noise ratio (SNR) information, resulting in a SNR-adaptive noise reduction. The KL-PWLS noise-reduction method was implemented analytically for efficient restoration of large volume HCT sinograms. Simulation studies showed a noticeable improvement, in terms of image quality and defect detectability, of the proposed noise-reduction method over the Ordered-Subsets Expectation-Maximization reconstruction and the conventional low-pass noise filtering with optimal cutoff frequency and/or other filter parameters.
Wang
Jing
J
J. Wang and Z. Liang are with the Departments of Radiology and Physics and Astronomy, State University of New York, Stony Brook, NY 11794 USA (telephone: 631-444-2736, e-mail:  jzl@mil.sunysb.edu ).T. Li and H. Lu were with the Department of Radiology, State University of New York, Stony Brook, NY 11794 USA. T. Li is now with the Department of Radiation Oncology, Stanford University, Stanford, CA 94305 USA. H. Lu is now with the Department of Biomedical Engineering, the Fourth Military Medical University, Xi'An, Shaanxi 710032, China.
Li
Tianfang
T
Lu
Hongbing
H
Liang
Zhengrong
Z