4.7 Article

Biomedical x-ray imaging with a GaAs photon-counting detector: A comparative study

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APL PHOTONICS
卷 5, 期 10, 页码 -

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AMER INST PHYSICS
DOI: 10.1063/5.0020262

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  1. Deutsche Forschungsgemeinschaft (DFG) [GRK 2274]
  2. Karlsruhe Nano Micro Facility (KNMF)
  3. DECTRIS Ltd. (Switzerland)
  4. Helmholtz Research Infrastructure at Karlsruhe Institute of Technology (KIT)

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Photon-counting detectors provide several potential advantages in biomedical x-ray imaging including fast and readout noise free data acquisition, sharp pixel response, and high dynamic range. Grating-based phase-contrast imaging is a biomedical imaging method, which delivers high soft-tissue contrast and strongly benefits from photon-counting properties. However, silicon sensors commonly used in photon-counting detectors have low quantum efficiency for mid- to high-energies, which limits high throughput capabilities when combined with grating-based phase contrast imaging. In this work, we characterize a newly developed photon-counting prototype detector with a gallium arsenide sensor, which enables imaging with higher quantum efficiency, and compare it with a silicon-based photon-counting and a scintillation-based charge integrating detector. In detail, we calculated the detective quantum efficiency (DQE) of all three detectors based on the experimentally measured modulation transfer function, noise power spectrum, and photon fluence. In addition, the DQEs were determined for two different spectra, namely, for a 28 kVp and a 50 kVp molybdenum spectrum. Among all tested detectors, the gallium arsenide prototype showed the highest DQE values for both x-ray spectra. Moreover, other than the comparison based on the DQE, we measured an ex vivo murine sample to assess the benefit using this detector for grating-based phase contrast computed tomography. Compared to the scintillation-based detector, the prototype revealed higher resolving power with an equal signal-to-noise ratio in the grating-based phase contrast computed tomography experiment. (c) 2020 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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