X-ray measurement model and information-theoretic metric incorporating material variability with energy correlations

Yijun Ding, Amit Ashok

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

Abstract

Extending our prior work, we propose a multi-energy X-ray measurement model incorporating material variability with energy correlations to enable the analysis and exploration of the performance of X-ray imaging and sensing systems. Based on this measurement model we provide analytical expressions for the Cauchy-Schwarz mutual information (ICS) measure that quantifies the performance limits of an X-ray measurement system for the threat-detection task. We analyze the performance of a prototypical X-ray measurement system to demonstrate the utility of our proposed material variability measurement model.

Original languageEnglish (US)
Title of host publicationAnomaly Detection and Imaging with X-Rays (ADIX) IV
EditorsAmit Ashok, Joel A. Greenberg, Michael E. Gehm
PublisherSPIE
ISBN (Electronic)9781510626638
DOIs
StatePublished - Jan 1 2019
EventAnomaly Detection and Imaging with X-Rays (ADIX) IV 2019 - Baltimore, United States
Duration: Apr 15 2019Apr 16 2019

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10999
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceAnomaly Detection and Imaging with X-Rays (ADIX) IV 2019
CountryUnited States
CityBaltimore
Period4/15/194/16/19

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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  • Cite this

    Ding, Y., & Ashok, A. (2019). X-ray measurement model and information-theoretic metric incorporating material variability with energy correlations. In A. Ashok, J. A. Greenberg, & M. E. Gehm (Eds.), Anomaly Detection and Imaging with X-Rays (ADIX) IV [109990J] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 10999). SPIE. https://doi.org/10.1117/12.2518552