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Practical implementations of speckle-based phase-retrieval methods in Python and GPU for tomography

  • Nghia T. Vo
  • , Hongchang Wang
  • , Lingfei Hu
  • , Tunhe Zhou
  • , Marie Christine Zdora
  • , Hans Deyhle
  • , Robert C. Atwood
  • , Michael Drakopoulos

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

Abstract

X-ray phase-contrast tomography (X-PCT) techniques are capable of imaging samples with small differences in densities. They enable scientists to study biological or medical samples using high energy X-rays, which means less X-ray absorption and less sample damage, with high contrast quality. One branch of these techniques known as speckle-based methods have been well developed and demonstrated on real applications by different groups of developers using their own codes. However, there is lack of collective effort to package these methods into an open-source software which is easy-to-install, easy-to-use, well-documented, and optimized for speed. Such software is crucial to make the X-PCT techniques accessible to generic users and become regular tools. This report demonstrates the effort which implements speckle-based phase-retrieval methods in Python and GPU.

Original languageEnglish
Title of host publicationDevelopments in X-Ray Tomography XIV
EditorsBert Muller, Ge Wang
PublisherSPIE - International Society for Optical Engineering
Number of pages12
ISBN (Electronic)9781510654686
DOIs
Publication statusPublished - 14 Oct 2022
Externally publishedYes
EventDevelopments in X-Ray Tomography 2022 - San Diego, United States of America
Duration: 22 Aug 202224 Aug 2022

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12242
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceDevelopments in X-Ray Tomography 2022
Country/TerritoryUnited States of America
CitySan Diego
Period22/08/2224/08/22

Keywords

  • phase-contrast imaging
  • speckle tracking
  • tomography
  • X-ray speckle-based phase-contrast tomography

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