Abstract

In recent years, the use of photon-counting detection technology has resulted in significant X-ray imaging research. This advanced technology holds considerable promise for enhancing Computed Tomography (CT) scanners, offering a potential solution to the limitations inherent in traditional CT detectors. The ongoing studies are dedicated to assessing the effectiveness and sensitivity of semiconductor detector materials in photon counting detectors, particularly in their ability to detect soft tissue contrasts. This study aimed to characterize the performance of the Cadmium Zinc Telluride (CZT) photon counting detector in identifying various tissues with a focus on assessing its sensitivity in distinguishing tissue types in X-ray imaging. An optimal frame rate per second (FPS) of the CZT detector was evaluated by setting the X-ray tube voltage and current at 25 keV and 35 keV and 0.5 mA, 1.0 mA respectively. By keeping the optimum FPS fixed, the detector energy thresholds were set in small steps from 15 keV to 35 keV and the tube currents were set for X-ray tubes in ranges of 0.1 mA–1.0 mA to evaluate the relationship between voltage and current of the X-ray source and counts per second (CPS). The specimens, including fat, liver, muscles, paraffin wax, and contrast media were placed on a stair-step chamber constructed from Plexi-glass, spanning six distinct thickness levels. We investigated X-ray transmission across these tissue samples at varying thicknesses, exploring five energy thresholds: 21 keV, 25 keV, 29 keV, 31 keV, and 45 keV to evaluate their impact on the CPS. This study found that a frame rate of 12 frames per second optimally aligns with the spectral response of the X-ray source. Furthermore, a linear correlation is present between the CPS and the X-ray tube current. The transmission of X-rays through a sample depends on its thickness, a phenomenon observed across different energy thresholds in this study. The detectors exhibit high sensitivity and linearity, ensuring accurate and reliable measurements in diverse imaging scenarios, making them invaluable tools for precise data acquisition in both research and clinical applications.

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