Correcting statistical CT number biases without access to raw detector counts: Applications to high spatial resolution photon counting CT imaging

Dalton Griner; Nikou Lei; Guang-Hong Chen; Ke Li

doi:10.1002/mp.16657

Correcting statistical CT number biases without access to raw detector counts: Applications to high spatial resolution photon counting CT imaging

Med Phys. 2023 Oct;50(10):6022-6035. doi: 10.1002/mp.16657. Epub 2023 Jul 30.

Authors

Dalton Griner¹, Nikou Lei¹, Guang-Hong Chen^{1

2}, Ke Li^{1

2}

Affiliations

¹ Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
² Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.

Abstract

Background: Due to the nonlinear nature of the logarithmic operation and the stochastic nature of photon counts (N), sinogram data of photon counting detector CT (PCD-CT) are intrinsically biased, which leads to statistical CT number biases. When raw counts are available, nearly unbiased statistical estimators for projection data were developed recently to address the CT number bias issue. However, for most clinical PCD-CT systems, users' access to raw detector counts is limited. Therefore, it remains a challenge for end users to address the CT number bias issue in clinical applications.

Purpose: To develop methods to correct statistical biases in PCD-CT without requiring access to raw PCD counts.

Methods: (1) The sample variance of air-only post-log sinograms was used to estimate air-only detector counts, ${\bar{N}}_{0}$ . (2) If the post-log sinogram data, y, is available, then N of each detector pixel was estimated using $N = {\bar{N}}_{0} e^{- y}$ . Once N was estimated, a closed-form analytical bias correction was applied to the sinogram. (3) If a patient's post-log sinogram data are not archived, a forward projection of the bias-contaminated CT image was used to perform a first-order bias correction. Both the proposed sinogram domain- and image domain-based bias correction methods were validated using experimental PCD-CT data.

Results: Experimental results demonstrated that both sinogram domain- and image domain-based bias correction methods enabled reduced-dose PCD-CT images to match the CT numbers of reference-standard images within [-5, 5] HU. In contrast, uncorrected reduced-dose PCD-CT images demonstrated biases ranging from -25 to 55 HU, depending on the material. No increase in image noise or spatial resolution degradation was observed using the proposed methods.

Conclusions: CT number bias issues can be effectively addressed using the proposed sinogram or image domain method in PCD-CT, allowing PCD-CT acquired at different radiation dose levels to have consistent CT numbers desired for quantitative imaging.

Keywords: CT number accuracy; photon counting CT; statistical bias.

Abstract

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