Voltage-Thickness-Gray imaging physical model in X-ray energy auto-modulation
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Updated: Apr 26, 2026

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
Published on: September 11, 2011
Ping Chen1, Yan Han2, Jinxiao Pan2
1National Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan, Shanxi, China Key Laboratory of Instrumentation Science and Dynamic Measurement, North University of China, Taiyuan, Shanxi, China State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Abstract:
Energy auto-modulation is an important tool in X-ray imaging, as it can improve the quality and longevity of an x-ray imaging system. Because of the complex nature of imaged objects, X-ray energy auto-modulation may be difficult. If there is a physical model about imaging mechanism, one can forecast the best imaging parameters using a pre-scan that can be fed into this model. This paper offers a physical model, which is called the Voltage-Thickness-Gray (VTG) model. Based on equivalent single-energy, this paper uses the empirical formula of X-ray attenuation and X-ray photon intensity to build this VTG model. Then use linear regression to estimate the model's parameters, by multi-voltage imaging about the steel wedge block. At last, by the experiment of the steel step block, verify this model and forecast the imaging tube voltage. The result shows this model can better reflect X-ray attenuation imaging properties, and can be used to forecast the imaging voltage. Also the forecast precision can achieve 90% or so.
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