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Projection-based dual-energy digital tomosynthesis and its image characteristics
Digital tomosynthesis (DTS) images reconstructed from the limited-angle scanned projections are often limited in image performance due mainly to superimposed shadow artifacts caused by high attenuation of dense material of the examined object, which makes image contrast of soft tissue distorted. In...
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Published in: | Instrumentation science & technology 2019-05, Vol.47 (3), p.248-263 |
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Main Authors: | , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Digital tomosynthesis (DTS) images reconstructed from the limited-angle scanned projections are often limited in image performance due mainly to superimposed shadow artifacts caused by high attenuation of dense material of the examined object, which makes image contrast of soft tissue distorted. In this study, we investigated a projection-based dual-energy DTS method incorporated with a new software scheme for scatter correction, the so-called weighted l
1
-norm contextual regularization algorithm, in an attempt to solve the image contrast problem of soft tissue in conventional DTS. The proposed dual-energy DTS process consisted of two main steps: creation of a scatter-corrected decomposition function and separation for soft- and dense-material images in the projection domain followed by DTS reconstruction. We implemented the proposed algorithm and performed a simulation and experiment to demonstrate the feasibility of using the algorithm in DTS. Two sets of projection images were acquired at an angular range of θ = ±40° and X-ray tube voltages of 80 kV
p
and 140 kV
p
and scatter-corrected prior to the filtered-backprojection-based DTS reconstruction. The results indicate that our proposed dual-energy DTS method produced cross-sectional images of better contrast characteristics for soft tissue than the conventional single-energy DTS method. |
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ISSN: | 1073-9149 1525-6030 |
DOI: | 10.1080/10739149.2018.1521829 |