PyPhase – a Python package for X-ray phase imaging

Abstract

X-ray propagation-based imaging techniques are well established at synchrotron radiation and laboratory sources. However, most reconstruction algorithms for such image modalities, also known as phase-retrieval algorithms, have been developed specifically for one instrument by and for experts, making the development and diffusion of such techniques difficult. Here, PyPhase, a free and open-source package for propagation-based near-field phase reconstructions, which is distributed under the CeCILL license, is presented. PyPhase implements some of the most popular phase-retrieval algorithms in a highly modular framework supporting its deployment on large-scale computing facilities. This makes the integration, the development of new phase-retrieval algorithms, and the deployment on different computing infrastructures straightforward. Its capabilities and simplicity are presented by application to data acquired at the synchrotron source MAX IV (Lund, Sweden).

Fast algorithms for nonlinear and constrained phase retrieval in near-field X-ray holography based on Tikhonov regularization

“…The proposed algorithms bear similarities to several previous work in the literature. In [18,29,32], gradient-descent schemes are proposed to iteratively minimize the distance to the hologram data (or rather to square-root-data √︁ 𝐼 𝑗 in [32]) based on the nonlinear model, i.e. the first term on right-hand side of (7b).…”

“…While the early phase retrieval algorithms have been reported solely in the literature without providing usable implementations, it has become customary to publish the source code as well [27][28][29]. We follow this trend and provide Matlab and Python implementations for the proposed algorithms.…”

Dose-efficient multimodal microscopy of human tissue at a hard X-ray nanoprobe beamline

“…3) required a few hours of computation time. The continuous development of the PyPhase package (Langer et al, 2021) will further increase user friendliness and enable novice users to generate converged holography reconstructions. However, it is expected that experiment design and setup will still require a solid understanding of holography and should hence be carried out by or in collaboration with experienced users or beamline staff.…”

An In-House Cone-Beam Tomographic Reconstruction Package for Laboratory X-ray Phase-Contrast Imaging

“…Although there is a plethora of literature regarding phase-retrieval algorithms, especially for propagation-based PCI, access to implementations of those algorithms is relatively limited [17][18][19][20][21][22]. Some of the packages work following the conventional pipeline and start with a phase retrieval step on the 2D projection images, which are then back projected using mostly filtered back projection (FBP) or iterative reconstruction methods [18,19,22]. It was also shown by Ruhlandt and Salditt [23] that phase retrieval and reconstruction are interchangeable also when considering approaches other than FBP, such as the Algebraic Reconstruction Technique (ART).…”

“…Only few packages wrap the phase-retrieval module with other codes for the full 3D tomographic reconstruction pipeline [18,19,21,22], which are available in open source form to the community. These, except for [21], which is a toolbox coupled to the ASTRA package [24], are developed exclusively for imaging at synchrotrons in parallel beam geometry.…”