Abstract
The increasing radiation dose in dual-energy CT (DE-CT) scanning due to the double exposures at 80 kVp and 140 kVp is a major concern in the application of DE-CT. This paper presents a novel image-space denoising method, called piecewise structural diffusion (PSD), for the reduction of noise in low-dose DE-CT images. Three principle structures (plate, ridge, and cap) and their corresponding diffusion tensors are formulated based on the eigenvalues of a Hessian matrix. The local diffusion tensor that is piecewise-defined on the domain of shape index is composed by a linear combination of two diffusion tensors of the associated principle structures. A single diffusion tensor calculated from the fused DE-CT image is applied to both high- and low-energy images. In the DE-CT colon phantom study, we demonstrated that DE-CT images filtered by PSD yielded the similar image quality with half of radiation doses.
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Cai, W., Lee, JG., Zhang, D., Piel, C., Yoshida, H. (2012). Piecewise Structural Diffusion Defined on Shape Index for Noise Reduction in Dual-Energy CT Images. In: Yoshida, H., Hawkes, D., Vannier, M.W. (eds) Abdominal Imaging. Computational and Clinical Applications. ABD-MICCAI 2012. Lecture Notes in Computer Science, vol 7601. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33612-6_10
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DOI: https://doi.org/10.1007/978-3-642-33612-6_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33611-9
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