Pixel-to-pixel variation in outputs of photon-counting detectors (PCDs) is a significant challenge in computed tomography (CT) imaging, leading to ring artifacts. This study presents a novel calibration framework to address this issue. Our approach involves a streamlined data acquisition strategy using CT scans of calibration phantoms, enabling comprehensive phantom thickness data acquisition across all pixels, coupled with three dedicated calibration steps. This process generates two correction coefficient tables: one for pixel-to-pixel variation correction and the other for both pixel-to-pixel variation and additional count-rate non-linearity correction using water as the calibration material. For experimental validation, we utilized a prototype PCD-based CT system and quantitatively evaluated the performance with high-frequency (ring artifact) and low-frequency (cupping/doming artifact) radial mean standard deviations (RMSDs) on both total count data and individual energy bin count data. Compared to a conventional calibration method, the proposed approach achieved substantial reductions in RMSDs, with improvements of 95.7% for total counts and 93.6% for energy bin counts in high-frequency RMSDs, and 97.2% for total counts and 55.7% for energy bin counts in low-frequency RMSDs. We anticipate that this calibration method will serve as an effective solution for addressing pixel-to-pixel variation in PCDs.
Lee et al. (Wed,) studied this question.
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