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Local Linear Constraint based Optimization Model for Material Decomposition

Qian Wang, Yining Zhu, Hengyong Yu

DOI:10.12059/Fully3D.2017-11-3112006

Published in:Fully3D 2017 Proceedings

Pages:352-358

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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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