• Spectroscopy and Spectral Analysis
  • Vol. 38, Issue 12, 3929 (2018)
HE Peng1、2, WU Xiao-chuan1, AN Kang2, DENG Gang3, WANG Xing3, ZHOU Zhong-xing4, WEI Biao1、2, and FENG Peng1、2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • 4[in Chinese]
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    DOI: 10.3964/j.issn.1000-0593(2018)12-3929-05 Cite this Article
    HE Peng, WU Xiao-chuan, AN Kang, DENG Gang, WANG Xing, ZHOU Zhong-xing, WEI Biao, FENG Peng. Experimental Study of Material K-Edge Characteristics Identification Based on X-ray Photon-Counting Detection Technique[J]. Spectroscopy and Spectral Analysis, 2018, 38(12): 3929 Copy Citation Text show less

    Abstract

    X-ray photon-counting detector is the core of the spectral CT imaging technique, and it could choose to record different energy X-ray photons by detector energy threshold, which is helpful to analyze the physical properties of different materials. In this paper, we used a spectral CT system based on photon-counting detector to study the K-edge characteristics of high purity metallic materials. By setting different energy thresholds for the detector, we could obtain the projection images of the metallic materials in different energy ranges. The attenuation characteristics of different energy X-ray could be analyzed by the gray information of projection images to identify the K-edge characteristics of metallic materials. The final experimental results demonstrated that the X-ray spectral CT system based on photon-counting detector can recognize the K-edge characteristics of metallic materials interacting with specific energy X-ray photons. The energy threshold for photon-counting detector can be calibrated by calculating the linear correspondence between K-edge peak energy threshold and K-edge theoretical energy value.
    HE Peng, WU Xiao-chuan, AN Kang, DENG Gang, WANG Xing, ZHOU Zhong-xing, WEI Biao, FENG Peng. Experimental Study of Material K-Edge Characteristics Identification Based on X-ray Photon-Counting Detection Technique[J]. Spectroscopy and Spectral Analysis, 2018, 38(12): 3929
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