Physics of Medical Imaging

Estimating scatter from sparsely measured primary signal

[+] Author Affiliations
Gongting Wu

University of North Carolina at Chapel Hill, Department of Physics and Astronomy, Chapel Hill, United States

Christina R. Inscoe, Jianping Lu

University of North Carolina at Chapel Hill, Department of Physics and Astronomy, Chapel Hill, United States

University of North Carolina at Chapel Hill, Department of Applied Physical Sciences, Chapel Hill, United States

Jabari Calliste

University of North Carolina at Chapel Hill, Department of Applied Physical Sciences, Chapel Hill, United States

Jing Shan

XinVivo, Morrisville, United States

Yueh Z. Lee

University of North Carolina at Chapel Hill, Department of Physics and Astronomy, Chapel Hill, United States

University of North Carolina at Chapel Hill, Department of Radiology, Chapel Hill, United States

Otto Zhou

University of North Carolina at Chapel Hill, Department of Physics and Astronomy, Chapel Hill, United States

University of North Carolina at Chapel Hill, Department of Applied Physical Sciences, Chapel Hill, United States

University of North Carolina at Chapel Hill, Lineberger Cancer Center, Chapel Hill, United States

J. Med. Imag. 4(1), 013508 (Mar 29, 2017). doi:10.1117/1.JMI.4.1.013508
History: Received June 19, 2016; Accepted March 13, 2017
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Abstract.  Scatter radiation severely degrades the image quality. Measurement-based scatter correction methods sample the scatter signal at sparsely distributed points, from which the scatter profile is estimated and deterministically removed from the projection image. The estimation of the scatter profile is generally done through a spline interpolation and the resulting scatter profile is quite smooth. Consequently, the noise is intact and the signal-to-noise ratio is reduced in the projection image after scatter correction, leading to image artifacts and increased noise in the reconstruction images. We propose a simple and effective method, referred to as filtered scatter-to-primary ratio (f-SPR) estimation, to estimate the scatter profile using the sparsely sampled scatter signal. Using the primary sampling device and the stationary digital tomosynthesis systems previously developed in our lab, we evaluated and compared the f-SPR method in comparison with existing methods in terms of contrast ratio, signal difference-to-noise ratio, and modulation transfer function. A significant improvement in image quality is observed in both the projection and the reconstruction images using the proposed method.

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© 2017 Society of Photo-Optical Instrumentation Engineers

Citation

Gongting Wu ; Christina R. Inscoe ; Jabari Calliste ; Jing Shan ; Yueh Z. Lee, et al.
"Estimating scatter from sparsely measured primary signal", J. Med. Imag. 4(1), 013508 (Mar 29, 2017). ; http://dx.doi.org/10.1117/1.JMI.4.1.013508


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