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公开(公告)号:EP2796897A1
公开(公告)日:2014-10-29
申请号:EP14150977.8
申请日:2014-01-13
发明人: Li, Yuanjing , Zhang, Lan , Li, Yulan , Liu, Yinong , Fu, Jianqiang , Jiang, Hao , Deng, Zhi , Xue, Tao , Zhang, Wei , Li, Jun
IPC分类号: G01T1/24
摘要: The invention provides a semiconductor detector (100), and the semiconductor detector (100) comprises a semiconductor crystal (101), a cathode (102), an anode (103) and at least one ladder electrode (104); the semiconductor crystal (101) comprises a top surface (101-2), a bottom surface (101-1) and at least one side (101-3); the cathode (102), the anode (103) and the ladder electrode (104) are conductive thin films deposited on a surface of the semiconductor crystal (101); the cathode (102) is disposed on the bottom surface (101-1) of the semiconductor crystal (101), the anode (103) is disposed on the top surface (101-2) of the semiconductor crystal (101), the ladder electrode (104) is disposed on the at least one side (101-3) of the semiconductor crystal (101); and the ladder electrode (104) comprises a plurality of sub-electrodes. As compared to the prior art, the semiconductor detector can improve the energy resolution.
摘要翻译: 本发明提供一种半导体检测器(100),半导体检测器(100)包括半导体晶体(101),阴极(102),阳极(103)和至少一个梯形电极(104) 半导体晶体(101)包括顶表面(101-2),底表面(101-1)和至少一个侧面(101-3); 阴极(102),阳极(103)和梯形电极(104)是沉积在半导体晶体(101)的表面上的导电薄膜; 阴极(102)设置在半导体晶体(101)的底表面(101-1)上,阳极(103)设置在半导体晶体(101)的顶表面(101-2)上,梯子 电极(104)设置在半导体晶体(101)的至少一个侧面(101-3)上; 并且梯形电极(104)包括多个子电极。 与现有技术相比,半导体检测器可以提高能量分辨率。
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公开(公告)号:EP2796897B1
公开(公告)日:2019-04-17
申请号:EP14150977.8
申请日:2014-01-13
发明人: Li, Yuanjing , Zhang, Lan , Li, Yulan , Liu, Yinong , Fu, Jianqiang , Jiang, Hao , Deng, Zhi , Xue, Tao , Zhang, Wei , Li, Jun
IPC分类号: G01T1/24
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3.
公开(公告)号:EP3632328A1
公开(公告)日:2020-04-08
申请号:EP19762285.5
申请日:2019-05-16
发明人: Xing, Yuxiang , Huang, Kaixin , Zhang, Li , Shen, Le , Deng, Zhi , Chen, Zhiqiang , Liu, Yinong
摘要: The present application provides a method, apparatus, device and medium for optimizing thresholds based on K-edge imaging. The method comprises: pre-scanning, by using a photon counting detector, an object to be detected according to a preset threshold group, to obtain first detection data; determining, according to the first detection data, line integral values of decomposition coefficients of individual basis functions in a basis function combination of each ray, wherein each ray has a fixed basis function combination; selecting, according to the line integral values of the decomposition coefficients of individual basis functions in the basis function combination of the each ray, rays of which a line integral value of a contrast agent material basis function in the fixed basis function combination is greater than a preset line integration threshold; inputting detection data corresponding to each of the selected rays to a pre-trained neural network model, to obtain a local optimal threshold group of each of the selected rays; and determining, based on local optimal threshold groups, a global optimal threshold group for the K-edge imaging of the photon counting detector.
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