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Spectral CT reconstruction algorithm based on adaptive tight frame wavelet and total variation
Author(s): Huihua Kong; Lei Lei; Ping Chen
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Paper Abstract

With the fast development of photon counting detection techniques, spectral computed tomography (CT) has attracted considerable attention. Considering the fact that a narrowing energy bin has high noise which degrades the imaging quality of spectral CT, a new algorithm based tight frame wavelet and total variation (TV) is proposed. This algorithm can not only preserve the edges in the reconstructed image by minimizing TV, but also preserve the sharp features as well as smoothness by tight frame wavelet. And an anisotropic diffusion operator based on Perona-Malik (PM) diffusion model is applied to this algorithm in order to adaptively adjust the degree of smoothing of the reconstruction image. The Split-Bregman algorithm was used to solve the objective function. Experiments showed the proposed algorithm can further improve the quality of reconstructed image and preserve the edge and detail features of the image for spectral CT.

Paper Details

Date Published: 28 May 2019
PDF: 7 pages
Proc. SPIE 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 110723B (28 May 2019); doi: 10.1117/12.2534488
Show Author Affiliations
Huihua Kong, North Univ. of China (China)
Lei Lei, North Univ. of China (China)
Ping Chen, North Univ. of China (China)


Published in SPIE Proceedings Vol. 11072:
15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine
Samuel Matej; Scott D. Metzler, Editor(s)

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