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  • Title: Imaging performance of amorphous selenium based flat-panel detectors for digital mammography: characterization of a small area prototype detector.
    Author: Zhao W, Ji WG, Debrie A, Rowlands JA.
    Journal: Med Phys; 2003 Feb; 30(2):254-63. PubMed ID: 12607843.
    Abstract:
    Our work is to investigate and understand the factors affecting the imaging performance of amorphous selenium (a-Se) flat-panel detectors for digital mammography. Both theoretical and experimental methods were developed to investigate the spatial frequency dependent detective quantum efficiency [DQE(f)] of a-Se flat-panel detectors for digital mammography. Since the K edge of a-Se is 12.66 keV and within the energy range of a mammographic spectrum, a theoretical model was developed based on cascaded linear system analysis with parallel processes to take into account the effect of K fluorescence on the modulation transfer function (MTF), noise power spectrum (NPS), and DQE(f) of the detector. This model was used to understand the performance of a small-area prototype detector with 85 microm pixel size. The presampling MTF, NPS, and DQE(f) of the prototype were measured, and compared to the theoretical calculation of the model. The calculation showed that K fluorescence accounted for a 15% reduction in the MTF at the Nyquist frequency (fNy) of the prototype detector, and the NPS at fNy was reduced to 89% of that at zero spatial frequency. The measurement of presampling MTF of the prototype detector revealed an additional source of blurring, which was attributed to charge trapping in the blocking layer at the interface between a-Se and the active matrix. This introduced a drop in both presampling MTF and NPS at high spatial frequency, and reduced aliasing in the NPS. As a result, the DQE(f) of the prototype detector at fNy approached 40% of that at zero spatial frequency. The measured and calculated DQE(f) using the linear system model have reasonable agreement, indicating that the factors controlling image quality in a-Se based mammographic detectors are fully understood, and the model can be used to further optimize detector imaging performance.
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