Work

XPCIpy: A Python toolkit for X-ray phase-contrast imaging

Year: 2025

Type: article

Abstract: X-ray absorption-based imaging often yields insufficient contrast for materials with low atomic numbers. X-ray phase-contrast imaging (PCI) offers a solution by leveraging the phase shift induced by different materials, enabling enhanced visualization of structures with minimal absorption differences. However, extracting phase information from intensity measurements is a non-trivial task, requiring specialized techniques. We present XPCIpy, an open-source software developed in Python, designed for both the simulation of X-ray PCI, including propagation-based imaging (PBI) and Talbot-Lau phase-contrast Imaging (TLPCI), and the reconstruction of TLPCI images. XPCIpy implements the phase stepping method for image retrieval, offering both least-squares and fast Fourier transform (FFT)-based reconstruction algorithms. It notably includes an algorithm for correcting phase step and dose fluctuations, which helps mitigate reconstruction artifacts like Moiré patterns. The software's modular architecture enhances extensibility, and a user-friendly graphical user interface (GUI) improves accessibility for researchers. Validated through both simulations and experimental data, XPCIpy provides a versatile framework to optimize experimental setups, test new reconstruction algorithms, and serve as an accessible tool for the scientific community in X-ray phase-contrast imaging. The code is publicly available at https://github.com/PREDICO-Project/XPCIpy.

Source: Optics Express

DOI: 10.1364/oe.573918

Authors: Victor Sanchez-Lara, Diego Garcia-Pinto

Language: English

Topic: Advanced X-ray Imaging Techniques

Subfield: Radiation

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,270

Funder: Ministerio de Ciencia, Innovación y Universidades

Award: G6231948074