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This work presents an approach to extend the dynamic range of x-ray flat panel detectors by combining two acquisitions of the same sample taken with two different x-ray photon flux levels and the same beam spectral configuration. In order to combine both datasets, the response of detector pixels was modelled in terms of mean and variance using a linear model. The model was extended to take into account the effect of pixel saturation. We estimated a joint probability density function (j-pdf) of the pixel values by assuming that each dataset follows an independent Gaussian distribution. This j-pdf was used for estimating the final pixel value of the high-dynamic-range dataset using a maximum likelihood method. The suitability of the pixel model for the representation of the detector signal was assessed using experimental data from a small-animal cone-beam micro-CT scanner equipped with a flat panel detector. The potential extension in dynamic range offered by our method was investigated for generic flat panel detectors using analytical expressions and simulations. The performance of the proposed dual-exposure approach in realistic imaging environments was compared with that of a regular single-exposure technique using experimental data from two different phantoms. Image quality was assessed in terms of signal-to-noise ratio, contrast, and analysis of profiles drawn on the images. The dynamic range, measured as the ratio between the exposure for saturation and the exposure equivalent to instrumentation noise, was increased from 76.9 to 166.7 when using our method. Dual-exposure results showed higher contrast-to-noise ratio and contrast resolution than the single-exposure acquisitions for the same x-ray dose. In addition, image artifacts were reduced in the combined dataset. This technique to extend the dynamic range of the detector without increasing the dose is particularly suited to image samples that contain both low and high attenuation regions.
computed radiography; non-ionizing radiation equipment and techniques; image quality; image analysis; medical physics