Locally linear constraint based optimization model for material decomposition.

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 Biol

authors

Wang Q,Zhu Y,Yu H

doi

10.1088/1361-6560/aa8e13

subject

Has Abstract

pub_date

2017-10-19 00:00:00

pages

8314-8340

issue

21

eissn

0031-9155

issn

1361-6560

journal_volume

62

pub_type

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