An information theoretic approach to system optimization accounting for material variability

David Coccarelli, Joel A. Greenberg, Ratchaneekorn Thamvichai, Jay Voris, Ahmad Masoudi, Amit Ashok, Michael Gehm

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

1 Scopus citations

Abstract

Differentiating material anomalies requires a measurement system that can reliably inform the user/classifier of pertinent material characteristics. In past work, we have developed a simulation framework capable of making simulated x-ray transmission and scatter measurements of virtual baggage. Using this simulated data, we have demonstrated how an information-theoretic approach to x-ray system design and analysis provides insight into system performance. Moreover, we have shown how performance limits relate to architectural variations in source fluence, view number, spectral resolution, spatial resolution, etc. However, our previous investigations did not include material variability in the description of the materials which make up the virtual baggage. One would expect the material variability to dramatically affect the results of the information-theoretic metric, and thus we now include it in our analysis. Previously, material information was captured as energy-dependent mean attenuation values. Because of this, material differentiation can always become easier with an improvement in SNR. When there is no variation to obscure class differences, improvements in SNR will indefinitely improve performance. Therefore, we saw a monotonic increase of the metric with source fluence. However there is inherent variability in materials from chemical impurities, texturing, or macroscopic variation. When this variability is accounted for, we better understand system performance limits at higher SNR as well as better represent the distributions of material characteristics. We will report on the analysis of real world system geometries and the fundamental limits of performance limits after incorporating these material variability improvements.

Original languageEnglish (US)
Title of host publicationAnomaly Detection and Imaging with X-Rays (ADIX) III
PublisherSPIE
Volume10632
ISBN (Electronic)9781510617759
DOIs
StatePublished - Jan 1 2018
EventAnomaly Detection and Imaging with X-Rays (ADIX) III 2018 - Orlando, United States
Duration: Apr 17 2018Apr 18 2018

Other

OtherAnomaly Detection and Imaging with X-Rays (ADIX) III 2018
CountryUnited States
CityOrlando
Period4/17/184/18/18

Keywords

  • High Dimensionality
  • Information Theory
  • Material Classification
  • X-Ray System Architecture

ASJC Scopus subject areas

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

Fingerprint Dive into the research topics of 'An information theoretic approach to system optimization accounting for material variability'. Together they form a unique fingerprint.

  • Cite this

    Coccarelli, D., Greenberg, J. A., Thamvichai, R., Voris, J., Masoudi, A., Ashok, A., & Gehm, M. (2018). An information theoretic approach to system optimization accounting for material variability. In Anomaly Detection and Imaging with X-Rays (ADIX) III (Vol. 10632). [106320F] SPIE. https://doi.org/10.1117/12.2305227