Maximum-likelihood calibration of an x-ray computed tomography system

Jared W. Moore, Roel Van Holen, Harrison H. Barrett, Lars R. Furenlid

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

Abstract

We present a maximum-likelihood (ML) method for calibrating the geometrical parameters of an x-ray computed tomography (CT) system. This method makes use of the full image data and not a reduced set of data. This algorithm is particularly useful for CT systems that change their geometry during the CT acquisition, such as an adaptive CT scan. Our ML search method uses a contracting-grid algorithm that does not require initial starting values to perform its estimate, thus avoiding problems associated with choosing initialization values.

Original languageEnglish (US)
Title of host publicationIEEE Nuclear Science Symposuim and Medical Imaging Conference, NSS/MIC 2010
Pages2614-2616
Number of pages3
DOIs
StatePublished - Dec 1 2010
Event2010 IEEE Nuclear Science Symposium, Medical Imaging Conference, NSS/MIC 2010 and 17th International Workshop on Room-Temperature Semiconductor X-ray and Gamma-ray Detectors, RTSD 2010 - Knoxville, TN, United States
Duration: Oct 30 2010Nov 6 2010

Publication series

NameIEEE Nuclear Science Symposium Conference Record
ISSN (Print)1095-7863

Other

Other2010 IEEE Nuclear Science Symposium, Medical Imaging Conference, NSS/MIC 2010 and 17th International Workshop on Room-Temperature Semiconductor X-ray and Gamma-ray Detectors, RTSD 2010
CountryUnited States
CityKnoxville, TN
Period10/30/1011/6/10

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ASJC Scopus subject areas

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

Cite this

Moore, J. W., Van Holen, R., Barrett, H. H., & Furenlid, L. R. (2010). Maximum-likelihood calibration of an x-ray computed tomography system. In IEEE Nuclear Science Symposuim and Medical Imaging Conference, NSS/MIC 2010 (pp. 2614-2616). [5874262] (IEEE Nuclear Science Symposium Conference Record). https://doi.org/10.1109/NSSMIC.2010.5874262