A novel scatter separation method for multi-energy x-ray imaging

Area of Science:

• Medical Imaging
• Photon Counting Detectors
• Radiation Physics

Background:

• Photon counting detectors enable material differentiation in X-ray imaging.
• Scattered radiation degrades image quality, causing contrast loss and artifacts in CT.
• Accurate material decomposition and thickness estimation require precise imaging.

Purpose of the Study:

• To introduce and evaluate a partial attenuation spectral scatter separation approach (PASSSA).
• To adapt PASSSA for multi-energy imaging applications.
• To assess the effectiveness of PASSSA in reducing scatter-induced artifacts and improving image accuracy.

Main Methods:

• Utilized numerical simulations with the Sindbad-SFFD tool.
• Employed a simplified numerical thorax phantom in a CT geometry.
• Applied the partial attenuation spectral scatter separation approach (PASSSA) to multi-energy data.

Main Results:

• Corrected attenuation images and CT slices showed improved local contrast and structure detectability.
• Scatter-induced bias was substantially decreased.
• Normalized root-mean-square error in projections reduced from ~23% to ~5%.
• Voxel value accuracy increased by a factor of >10 for inspected volumes.

Conclusions:

• PASSSA effectively separates scattered radiation in multi-energy X-ray imaging.
• The developed approach significantly enhances image accuracy and quantitative performance.
• PASSSA improves material differentiation and thickness estimation capabilities in medical imaging.