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17 October 2022 Likelihood-based bilateral filtration in material decomposition for photon counting CT
Okkyun Lee
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Proceedings Volume 12304, 7th International Conference on Image Formation in X-Ray Computed Tomography; 123040X (2022) https://doi.org/10.1117/12.2647049
Event: Seventh International Conference on Image Formation in X-Ray Computed Tomography (ICIFXCT 2022), 2022, Baltimore, United States
Abstract
The maximum likelihood (ML) principle has been a gold standard for estimating basis line-integrals due to the optimal statistical property. However, the estimates are sensitive to noise from large attenuations or low dose levels. One may apply filtering in the estimated basis sinograms or model-based iterative reconstruction. Both methods effectively reduce noise, but the degraded spatial resolution is a concern. In this study, we propose a likelihood-based bilateral filter (LBF) for the estimated basis sinograms to reduce noise while preserving spatial resolution. It is a post-processing filtration applied to the ML-based basis line-integrals, the estimates with a high noise level but minimal degradation of spatial resolution. The proposed filter considers likelihood in neighbours instead of weighting by pixel values as in the original bilateral filtration. Two-material decomposition (water and bone) results demonstrate that the proposed method shows improved noise-to-spatial resolution tendency compared to conventional methods.
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Okkyun Lee "Likelihood-based bilateral filtration in material decomposition for photon counting CT", Proc. SPIE 12304, 7th International Conference on Image Formation in X-Ray Computed Tomography, 123040X (17 October 2022); https://doi.org/10.1117/12.2647049
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KEYWORDS
Computed tomography
Statistical analysis
Spatial resolution
Photon counting
Image filtering
Gaussian filters
Signal attenuation
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