Quantitative material decomposition using linear iterative near-field phase retrieval dual-energy x-ray imaging

Area of Science:

• Medical Imaging
• Biomedical Engineering
• Materials Science

Background:

• Propagation-based phase contrast x-ray imaging offers significant signal-to-noise ratio (SNR) improvements over conventional methods.
• Phase retrieval is crucial for enhancing image quality in low-dose biomedical imaging.
• Single-measurement phase retrieval often requires assumptions about the sample, limiting its quantitative accuracy.

Purpose of the Study:

• To develop a quantitative material thickness decomposition method using dual-energy phase retrieval.
• To expand the linear iterative near-field phase retrieval (LIPR) formalism for material decomposition.
• To enable accurate phase retrieval without prior assumptions about the object's composition.

Main Methods:

• Utilized dual-energy x-ray measurements at the same propagation distance.
• Incorporated the Alvarez-Macovski (AM) model to differentiate photoelectric and Compton scattering.
• Applied the LIPR formalism to monochromatic experimental x-ray projections at two energies.

Main Results:

• Successfully separated objects into projected thicknesses of two known materials.
• Achieved SNR improvements of 2 to 10 times.
• Demonstrated no visible loss in spatial resolution.
• Indicated potential x-ray dose reduction by a factor of 4 to 100.

Conclusions:

• Dual-energy phase retrieval with the AM model provides quantitative material decomposition.
• The method enhances image quality and enables significant dose reduction in x-ray imaging.
• This technique advances biomedical imaging by allowing for precise material analysis with reduced radiation exposure.