Accelerating x-ray fluorescence computed tomography

P. J. La Riviere, P. Vargas, G. Fu, L. J. Meng

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

Abstract

This paper presents new approaches to accelerating x-ray fluorescence tomography (XFCT) that are grounded in both novel image acquisition strategies that improve the quality of the data acquired and in image reconstruction strategies that reduce the amount of data acquired. First, we introduce an alternative imaging scheme that uses an emission tomography (ET) system to collect the fluorescence photons representing an entire 2D slice or volumetric projection of the object at one time. Preliminary results indicate that this could achieve a ten to hundredfold improvement in imaging speed. Secondly, novel image reconstruction algorithms are introduced that allow for improved quantitative accuracy as well as for imaging of regions of interest, which will lead to further reduction in data-acquisition time.

Original languageEnglish (US)
Title of host publicationProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEngineering the Future of Biomedicine, EMBC 2009
Pages1000-1003
Number of pages4
DOIs
StatePublished - 2009
Event31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 - Minneapolis, MN, United States
Duration: Sep 2 2009Sep 6 2009

Publication series

NameProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009

Other

Other31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
Country/TerritoryUnited States
CityMinneapolis, MN
Period9/2/099/6/09

Keywords

  • SPECT aperture
  • Synchrotron radiation
  • X-ray fluorescence computed tomography

ASJC Scopus subject areas

  • Cell Biology
  • Developmental Biology
  • Biomedical Engineering
  • Medicine(all)
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Health Informatics

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