Evaluation of Photon Processing Detectors using the Fourier Crosstalk Matrix

Nick Henscheid, Abhinav K. Jha, Harrison H Barrett

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

1 Scopus citations

Abstract

Advances in emission imaging detector hard-ware and modeling have allowed on-the-fly maximum likelihood photon event attribute estimation [1]. Such detectors lead to an infinite d imensional s ystem m odel c alled the Photon Processing model [2], [3], [4]. In this work we extend the Fourier crosstalk matrix formalism [5] to photon processing systems to compare the performance of such detectors to classical pixelated photon-counting detectors for the task of estimating object Fourier coefficients. In a preliminary study we have computed crosstalk matrices for a class of 2D pinhole SPECT systems; in this setting, the photon processing detector outperforms a pixelated detector with pixel size equal to the full width half maximum of the position estimation blur.

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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    Henscheid, N., Jha, A. K., & Barrett, H. H. (2018). Evaluation of Photon Processing Detectors using the Fourier Crosstalk Matrix. In 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings [8533055] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NSSMIC.2017.8533055