Penalized-likelihood sinogram smoothing for low-dose CT
- Department of Radiology, University of Chicago, Chicago, Illinois 60637 (United States)
We have developed a sinogram smoothing approach for low-dose computed tomography (CT) that seeks to estimate the line integrals needed for reconstruction from the noisy measurements by maximizing a penalized-likelihood objective function. The maximization is performed by an algorithm derived by use of the separable paraboloidal surrogates framework. The approach overcomes some of the computational limitations of a previously proposed spline-based penalized-likelihood sinogram smoothing approach, and it is found to yield better resolution-variance tradeoffs than this spline-based approach as well an existing adaptive filtering approach. Such sinogram smoothing approaches could be valuable when applied to the low-dose data acquired in CT screening exams, such as those being considered for lung-nodule detection.
- OSTI ID:
- 20726066
- Journal Information:
- Medical Physics, Journal Name: Medical Physics Journal Issue: 6 Vol. 32; ISSN 0094-2405; ISSN MPHYA6
- Country of Publication:
- United States
- Language:
- English
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