Penalized weighted least-squares approach for low-dose X-ray computed tomography

Jing Wang, Tianfang Li, Hongbing Lu, Zhengrong Liang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

The noise of low-dose computed tomography (CT) sinogram follows approximately a Gaussian distribution with nonlinear dependence between the sample mean and variance. The noise is statistically uncorrelated among detector bins at any view angle. However the correlation coefficient matrix of data signal indicates a strong signal correlation among neighboring views. Based on above observations, Karhunen-Loève (KL) transform can be used to de-correlate the signal among the neighboring views. In each KL component, a penalized weighted least-squares (PWLS) objective function can be constructed and optimal sinogram can be estimated by minimizing the objective function, followed by filtered backprojection (FBP) for CT image reconstruction. In this work, we compared the KL-PWLS method with an iterative image reconstruction algorithm, which uses the Gauss-Seidel iterative calculation to minimize the PWLS objective function in image domain. We also compared the KL-PWLS with an iterative sinogram smoothing algorithm, which uses the iterated conditional mode calculation to minimize the PWLS objective function in sinogram space, followed by FBP for image reconstruction. Phantom experiments show a comparable performance of these three PWLS methods in suppressing the noise-induced artifacts and preserving resolution in reconstructed images. Computer simulation concurs with the phantom experiments in terms of noise-resolution tradeoff and detectability in low contrast environment. The KL-PWLS noise reduction may have the advantage in computation for low-dose CT imaging, especially for dynamic high-resolution studies.

Original languageEnglish (US)
Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume6142 III
DOIs
StatePublished - 2006
EventMedical Imaging 2006: Physics of Medical Imaging - San Diego, CA, United States
Duration: Feb 12 2006Feb 16 2006

Other

OtherMedical Imaging 2006: Physics of Medical Imaging
CountryUnited States
CitySan Diego, CA
Period2/12/062/16/06

Fingerprint

Dosimetry
Tomography
Image reconstruction
X rays
Gaussian distribution
Bins
Noise abatement
Experiments
Detectors
Imaging techniques
Computer simulation

Keywords

  • KL transform
  • Low-dose CT
  • Noise-resolution tradeoff
  • Penalized weighted least-squares (PWLS)
  • ROC curve

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Wang, J., Li, T., Lu, H., & Liang, Z. (2006). Penalized weighted least-squares approach for low-dose X-ray computed tomography. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE (Vol. 6142 III). [614247] https://doi.org/10.1117/12.653903

Penalized weighted least-squares approach for low-dose X-ray computed tomography. / Wang, Jing; Li, Tianfang; Lu, Hongbing; Liang, Zhengrong.

Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 6142 III 2006. 614247.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wang, J, Li, T, Lu, H & Liang, Z 2006, Penalized weighted least-squares approach for low-dose X-ray computed tomography. in Progress in Biomedical Optics and Imaging - Proceedings of SPIE. vol. 6142 III, 614247, Medical Imaging 2006: Physics of Medical Imaging, San Diego, CA, United States, 2/12/06. https://doi.org/10.1117/12.653903
Wang J, Li T, Lu H, Liang Z. Penalized weighted least-squares approach for low-dose X-ray computed tomography. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 6142 III. 2006. 614247 https://doi.org/10.1117/12.653903
Wang, Jing ; Li, Tianfang ; Lu, Hongbing ; Liang, Zhengrong. / Penalized weighted least-squares approach for low-dose X-ray computed tomography. Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 6142 III 2006.
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