<i>HoToPy</i> : a toolbox for X-ray holo-tomography in Python
We present a Python toolbox for holographic and tomographic X-ray imaging. It comprises a collection of phase retrieval algorithms for the deeply holographic and direct contrast imaging regimes, including non-linear approaches and extended choices of regularization, constraint sets and optimizers, all implemented with a unified and intuitive interface. Moreover, it features auxiliary functions for (tomographic) alignment, image processing and simulation of imaging experiments. The capability of the toolbox is illustrated by an example of a catalytic nanoparticle, imaged in the deeply holographic regime at the `GINIX' instrument of the P10 beamline at the PETRA III storage ring (DESY, Hamburg, Germany). Due to its modular design, the toolbox can be used for algorithmic development and benchmarking in a lean and flexible manner, or be interfaced and integrated in the reconstruction pipeline of other synchrotron or X-ray free-electron laser instruments for phase imaging based on propagation.
Authors
- Paul Meyer (ORCID: https://orcid.org/0000-0002-9193-2000)
- Tim Salditt (ORCID: https://orcid.org/0000-0003-4636-0813)
- Leon Merten Lohse (ORCID: https://orcid.org/0000-0001-5058-7215)
- Jens Lucht (ORCID: https://orcid.org/0000-0003-4447-7882)
Institutions
- Universität Hamburg (DE)
- Max Planck Institute for the Structure and Dynamics of Matter (DE)
- University of Göttingen (DE)
Publication Details
- Journal
- Journal of Synchrotron Radiation
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1107/s1600577525008550
- Citations
- 2
- Primary Topic
- Advanced X-ray Imaging Techniques
- Type
- article
- Field-Weighted Citation Impact
- 3.77