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DESCRIPTION (provided by applicant): X-ray dose is a growing concern in advanced medical imaging technologies like CT and PET as these techniques are increasingly applied to a broader set of medical problems. Dose reduction can only be achieved by increasing the sensitivity of the detector system. Black Silicon is a novel optical detector material with a 100x responsivity enhancement over conventional silicon photo detectors. Coupled with standard scintillator crystals, Black Silicon photo detectors provide a promising new sensor technology that can reduce patient dose by improving the quantum efficiency within the signal chain. To realize this vision it will be necessary to develop photodiode devices that integrate the Black Silicon pulsed laser process. Black Silicon is formed by femtosecond laser processing of silicon wafers in a controlled sulfur hexafluoride atmosphere. Remarkably, prototype devices fabricated from Black Silicon exhibit photoconductive gain properties, producing as much as 100 electrons for every 1 photon absorbed. It is the objective of this work to develop optimized Black Silicon photo detectors with enhanced sensitivity to blue colored light, where industry standard x-ray scintillator crystals emit. With higher photon sensitivity, fewer x-rays are required to make the same measurement, thereby lowering the patient dose. PUBLIC HEALTH RELEVANCE: The outcome of this work will be a much higher sensitivity detector that when integrated into advanced radiographic imaging systems will improve imaging performance and reduce overall system cost. Improving the imaging performance can lead to reduced x-ray dose to the patient or improved the image fidelity and resolution at equal dose levels.
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Energy Sensitive Digital Radiography
  • 批准号:
    6788483
  • 项目类别:
  • 资助金额:
    $9.73万
  • 财政年份:
    2004
  • 负责人:
    Martin U Pralle
  • 依托单位:
国内基金
海外基金
Identification and quantification of primary phytoplankton functional types in the global oceans from hyperspectral ocean color remote sensing
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    160万元
  • 批准年份:
    2022
  • 负责人:
    李忠平
  • 依托单位: