Voltage-Thickness-Gray imaging physical model in X-ray energy auto-modulation

Area of Science:

• Medical Physics
• Materials Science
• Imaging Technology

Background:

• X-ray energy auto-modulation enhances imaging system quality and lifespan.
• Complex object imaging presents challenges for accurate X-ray energy auto-modulation.
• Physical models can forecast optimal imaging parameters via pre-scans.

Purpose of the Study:

• To introduce a physical model, the Voltage-Thickness-Gray (VTG) model, for X-ray imaging.
• To enable accurate forecasting of imaging parameters for improved X-ray systems.
• To enhance the understanding of X-ray attenuation properties.

Main Methods:

• Developed the VTG model based on equivalent single-energy principles.
• Utilized empirical formulas for X-ray attenuation and photon intensity.
• Employed linear regression with multi-voltage imaging of a steel wedge block to estimate parameters.
• Verified the model and forecasted imaging voltage using a steel step block experiment.

Main Results:

• The VTG model effectively represents X-ray attenuation imaging properties.
• The model accurately forecasts imaging tube voltage.
• Achieved a voltage forecasting precision of approximately 90%.

Conclusions:

• The developed VTG model is a valuable tool for X-ray imaging parameter optimization.
• The model contributes to improving X-ray imaging quality and system longevity.
• Accurate voltage forecasting is achievable with the VTG model.