Abstract:
:Dual spectral computed tomography (DSCT) has a superior material distinguishability than the conventional single spectral computed tomography (SSCT). However, the decomposition process is an illposed problem, which is sensitive to noise. Thus, the decomposed image quality is degraded, and the corresponding signal-to-noise ratio (SNR) is much lower than that of directly reconstructed image of SSCT. In this work, we establish a locally linear relationship between the decomposed results of DSCT and SSCT. Based on this constraint, we propose an optimization model for DSCT and develop an iterative method with image guided filtering. To further improve the image quality, we employ a preprocessing method based on the relative total variation regularization. Both numerical simulations and real experiments are performed, and the results confirm the effectiveness of our proposed approach.
journal_name
Phys Med Bioljournal_title
Physics in medicine and biologyauthors
Wang Q,Zhu Y,Yu Hdoi
10.1088/1361-6560/aa8e13subject
Has Abstractpub_date
2017-10-19 00:00:00pages
8314-8340issue
21eissn
0031-9155issn
1361-6560journal_volume
62pub_type
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