Python工具箱实现X射线全息断层成像，支持多种相位恢复算法。
HoToPy: A toolbox for X-ray holo-tomography in Python
- 统一接口整合非线性相位恢复算法与正则化策略。
- 在德国汉堡PETRA III光束线实测催化纳米颗粒，验证成像能力。
- 模块化设计适合算法开发或同步辐射/XFEL仪器集成使用。
我们介绍一个用于全息和断层X射线成像的Python工具箱。它包含适用于深度全息和直接对比成像模式的相位恢复算法，涵盖非线性方法以及扩展的正则化、约束集与优化器选择，均通过统一且直观的接口实现。此外，还提供用于（断层）对齐、图像处理及成像实验仿真的辅助函数。该工具箱的能力通过在德国汉堡DESY的PETRA III储存环P10光束线'GINIX'装置上，对催化纳米颗粒在深度全息模式下的成像案例得到验证。由于其模块化设计，该工具箱可灵活用于算法开发与基准测试，也可集成到其他同步辐射或XFEL仪器的传播型相位成像重建流程中。
原文摘要 · Abstract (English)
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 the 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). 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 XFEL instruments for phase imaging based on propagation.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。