Coding and sampling for compressive x-ray diffraction tomography

Joel A. Greenberg, Kalyani Krishnamurthy, Manu Lakshmanan, Kenneth MacCabe, Scott Wolter, Anuj Kapadia, David Brady

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

12 Scopus citations

Abstract

Coded apertures and energy resolving detectors may be used to improve the sampling efficiency of x-ray tomography and increase the physical diversity of x-ray phenomena measured. Coding and decompressive inference enable increased molecular specificity, reduced exposure and scan times. We outline a specific coded aperture x-ray coherent scatter imaging architecture that demonstrates the potential of such schemes. Based on this geometry, we develop a physical model using both a semi-analytic and Monte Carlo-based framework, devise an experimental realization of the system, describe a reconstruction algorithm for estimating the object from raw data, and propose a classification scheme for identifying the material composition of the object at each location.

Original languageEnglish (US)
Title of host publicationWavelets and Sparsity XV
DOIs
StatePublished - 2013
Externally publishedYes
EventWavelets and Sparsity XV - San Diego, CA, United States
Duration: Aug 26 2013Aug 29 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8858
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceWavelets and Sparsity XV
Country/TerritoryUnited States
CitySan Diego, CA
Period8/26/138/29/13

Keywords

  • Coded aperture
  • Medical imaging
  • Molecular imaging
  • X-ray diffraction imaging
  • X-ray tomography

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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