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Experimental Study of Material K-Edge Characteristics Identification Based on X-ray Photon-Counting Detection Technique |
HE Peng1,2, WU Xiao-chuan1, AN Kang2, DENG Gang3, WANG Xing3, ZHOU Zhong-xing4, WEI Biao1,2, FENG Peng1,2* |
1. The Key Lab of Optoelectronic Technology and Systems of Ministry of Education, Chongqing University, Chongqing 400044, China
2. ICT-NOT Engineering Research Center of Ministry of Education, Chongqing University, Chongqing 400044, China
3. The Key Laboratory of Rheological Science and Technology of Ministry of Education, Chongqing University, Chongqing 400044, China
4. School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China |
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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.
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Received: 2017-12-07
Accepted: 2018-04-12
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Corresponding Authors:
FENG Peng
E-mail: coe-fp@cqu.edu.cn
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[1] |
REN Xue-zhi1, HE Peng1, 2*, LONG Zou-rong1, GUO Xiao-dong1, AN Kang2, LÜ Xiao-jie1, WEI Biao1, 2, FENG Peng1, 2*. Research on Spectral CT Image Denoising Via Fully Convolution Pyramid Residual Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(09): 2950-2955. |
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