Improved X-ray Cargo imaging by innovative background scattering quantification
Improved X-ray Cargo imaging by innovative background scattering quantification
批准号:
ST/T003324/1
负责人:
David Matthew Cullen
金额:
$2.79万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --
中文摘要
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英文摘要
X-ray screening is high priority for securing borders from the influx of firearms, narcotics, and contraband. The ability of anx-ray screening system to detect photons attenuated by dense cargo directly affects the radiographic image quality that anoperator uses to identify such illicit material. When screening cargo and vehicles, high-energy high-dose pulsed linearaccelerators are used to generate the x rays. The detection package integrates the signal over the duration of a singlepulse and this forms the basis of each pixel value in the image. However, with no means to reject low-energy photonsscattered into the detectors or electronic dark current, the signals include a large degree of noise that distorts the finalradiographic images. The technological advances in recent years and the exploitation of spectroscopic techniques presentan opportunity to utilise novel detector material and off-the-shelf fast electronic components to identify individual photons.This will vastly improve the performance of screening systems and increase image quality, particularly in areas of highattenuation. To this end, this project seeks to investigate new detector material, design, construct and test a prototypedetection system capable of photon counting in such high x-ray flux environments. Detector characterisation and design willbe carried out at the University of Manchester. Experimental investigations will require the use of the new Compact Linacfacility at Daresbury laboratory, capable of producing low-dose x-ray pulses so that algorithms to control the detectionpackage can be developed and the limitations obtained. The detection package will then be used at Rapiscan Systemsfacility at Stoke using a field-ready linac to prove its capabilities.
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