Estimating scatter from sparsely measured primary signal.

J Med Imaging (Bellingham)

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.

Published: January 2017

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 ([Formula: see text]-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 [Formula: see text]-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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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5370239PMC
http://dx.doi.org/10.1117/1.JMI.4.1.013508DOI Listing

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