Adaptive filtering method for reducing signal saturation induced artifacts in X-ray dark-field tomography

Area of Science:

• Physics
• Materials Science
• Medical Imaging

Background:

• X-ray dark-field imaging utilizes small-angle scattering for contrast, originating from micron/sub-micron structures.
• Talbot-Lau interferometers enable dark-field imaging with conventional X-ray tubes.
• Strong scattering can saturate dark-field signals, hindering accurate phase retrieval and tomographic reconstruction.

Purpose of the Study:

• To develop an adaptive filtering approach to improve signal-to-noise ratio in X-ray dark-field and phase-contrast projections.
• To address limitations in tomographic reconstruction caused by strong scattering effects.

Main Methods:

• An adaptive filtering technique was applied to dark-field and phase-contrast projection images.
• The filtering specifically targets image areas where the dark-field signal approaches saturation.

Main Results:

• The adaptive filtering markedly improved projection images.
• Enhanced signal-to-noise ratios were achieved in areas with high scattering.
• Successful tomographic reconstruction was demonstrated for samples with strong scatterers.

Conclusions:

• The proposed adaptive filtering method effectively overcomes signal saturation issues in X-ray dark-field imaging.
• This approach significantly enhances the accuracy of tomographic reconstruction for challenging samples.
• The technique broadens the applicability of X-ray dark-field imaging in materials science and medical diagnostics.