Optimization of K-edge imaging with spectral CT

被引:58
作者
He, Peng [1 ,2 ]
Wei, Biao [2 ]
Cong, Wenxiang [1 ]
Wang, Ge [1 ]
机构
[1] Virginia Tech, Biomed Imaging Div, VT WFU Sch Biomed Engn & Sci, Blacksburg, VA 24061 USA
[2] Chongqing Univ, Educ Minist China, Key Lab Optoelect Technol & Syst, Chongqing 400044, Peoples R China
关键词
spectral/multienergy CT; K-edge imaging; energy bins; image reconstruction; signal difference to noise ratio (SDNR); PHOTON-COUNTING DETECTORS; COMPUTED-TOMOGRAPHY; CONTRAST AGENT; MICRO-CT; MEDIPIX2; SYSTEM; RECONSTRUCTION; IODINE; MODEL;
D O I
10.1118/1.4754587
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: Spectral/multienergy CT has the potential to distinguish different materials by K-edge characteristics. K-edge imaging involves the two energy bins on both sides of a K-edge. The authors propose a K-edge imaging optimization model to determine these two energy bins. Methods: K-edge image contrast with spectral CT depends on the specifications of the two energy bins on both sides of a K-edge in the attenuation profile of a relatively high atomic number material. The wider the energy bin width is, the lower the noise level is, and the poorer the reconstructed image contrast is. Here the authors introduce the signal difference to noise ratio (SDNR) criterion to optimize the energy bin widths on both sides of the K-edge for the maximum SDNR. Results: The authors study K-edge imaging with spectral CT, analyze the effect of K-edge energy bins on the resultant image quality, and establish guidelines for the optimization of energy thresholds. In simulation, the authors demonstrate that our K-edge imaging optimization approach maximizes SDNR in reconstructed images. Conclusions: This proposed approach can be readily generalized to deal with more general settings and determine the best energy bins for K-edge imaging. (C) 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4754587]
引用
收藏
页码:6572 / 6579
页数:8
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