Keywords:
local linear constraint, optimization model, image guided filtering, dual spectral computed tomography
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 local 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. Both numerical simulations and real experiments are performed to validate the effectiveness of the proposed approach.
- Qian Wang
- University of Massachusetts Lowell
- Yining Zhu
- Capital Normal University
- Hengyong Yu
- University of Massachusetts Lowell
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