Adorym: A multi-platform generic X-ray image reconstruction framework based on automatic differentiation

Ming Du*, Saugat Kandel, Junjing Deng, Xiaojing Huang, Arnaud Demortiere, Tuan Tu Nguyen, Remi Tucoulou, Vincent De Andrade, Qiaoling Jin, Chris Jacobsen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We describe and demonstrate an optimization-based X-ray image reconstruction framework called Adorym. Our framework provides a generic forward model, allowing one code framework to be used for a wide range of imaging methods ranging from near-field holography to fly-scan ptychographic tomography. By using automatic differentiation for optimization, Adorym has the flexibility to refine experimental parameters including probe positions, multiple hologram alignment, and object tilts. It is written with strong support for parallel processing, allowing large datasets to be processed on high-performance computing systems. We demonstrate its use on several experimental datasets to show improved image quality through parameter refinement.

Original languageEnglish (US)
Pages (from-to)10000-10035
Number of pages36
JournalOptics Express
Volume29
Issue number7
DOIs
StatePublished - Mar 29 2021

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

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