Use of characteristic functionals to analyze molecular images in targeted cancer therapy

Harrison H Barrett, Kyle J. Myers, Eric W Clarkson, Nick Henscheid

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

Abstract

This paper presents a comprehensive mathematical framework for analyzing medical images in terms of interacting random processes that evolve in time. The key mathematical concept is the characteristic functional, which encapsulates all possible statistical properties of a random process, yet can often be expressed analytically. It is shown how molecular images can be used to tailor the analytic expressions to a particular patient and to relate the results to the predicted outcome of therapy.

Original languageEnglish (US)
Title of host publication2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538622827
DOIs
StatePublished - Nov 12 2018
Event2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Atlanta, United States
Duration: Oct 21 2017Oct 28 2017

Other

Other2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017
CountryUnited States
CityAtlanta
Period10/21/1710/28/17

ASJC Scopus subject areas

  • Instrumentation
  • Radiology Nuclear Medicine and imaging
  • Nuclear and High Energy Physics

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  • Cite this

    Barrett, H. H., Myers, K. J., Clarkson, E. W., & Henscheid, N. (2018). Use of characteristic functionals to analyze molecular images in targeted cancer therapy. In 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings [8532599] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NSSMIC.2017.8532599