On the performance of the noise power spectrum from the gain-corrected radiography images

Dong Sik Kim; Eunae Lee

doi:10.1117/1.JMI.5.1.013508

30 March 2018 On the performance of the noise power spectrum from the gain-corrected radiography images

Dong Sik Kim, Eunae Lee

Author Affiliations +

Journal of Medical Imaging, Vol. 5, Issue 1, 013508 (March 2018). https://doi.org/10.1117/1.JMI.5.1.013508

Abstract

Fixed pattern noise due to nonuniform amplifier gains and scintillator sensitivity should be alleviated in radiography imaging to acquire low-noise x-ray images from detectors. Here, the noise property of the detector is usually evaluated observing the noise power spectrum (NPS). A gain-correction scheme, in which uniformly illuminated images are averaged to design a gain map, can be applied to alleviate the fixed pattern noise problem. The normalized NPS (NNPS) of the gain-corrected image decreases as the number of images for the average increases and converges to an infimum, which can be achieved if the fixed pattern noise is completely removed. If we know the NNPS infimum of the detector, then we can determine the performance of the gain-corrected images compared with the achievable lower bound. We first construct an image-formation model considering the nonuniform gain and then consider two measurement methods based on subtraction and division to estimate the NNPS infimum of the detector. In order to obtain a high-precision NNPS infimum estimate, we consider a time-averaging method. For several flat-panel radiography detectors, we constructed the NNPS infimum measurements and compared them with NNPS values of the gain-corrected images. We observed that the NNPS values of the gain-corrected images approached the NNPS infimum as the number of images for the average increased.

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Dong Sik Kim and Eunae Lee "On the performance of the noise power spectrum from the gain-corrected radiography images," Journal of Medical Imaging 5(1), 013508 (30 March 2018). https://doi.org/10.1117/1.JMI.5.1.013508

Received: 26 September 2017; Accepted: 12 March 2018; Published: 30 March 2018

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