IMPROVED ESTIMATION OF LOCAL CEREBRAL GLUCOSE METABOLIC RATE USING BAYES REGRESSION ANALYSIS OF PET SCAN DATA.

P. D. Wilson, S. C. Huang, Jonathan M Links

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

Abstract

The current method for measurement of local cerebral metabolic rate of glucose (LCMRG) has relatively small errors when applied to normal healthy tissue. When applied to ischemic regions in brains of stroke patients, the method gives estimates which average about 50% too low. Therefore, the authors introduce a modified Bayes regression (BR) to compute the LCMRG, and use computer simulation studies to demonstrate that BR has relatively small errors for either ischemic or normal tissue. These improved estimates are within the clinical constraints of a one-hour data collection period.

Original languageEnglish (US)
Title of host publicationProceedings - Annual Symposium on Computer Applications in Medical Care
EditorsGerald S. Cohen
PublisherIEEE
Pages128-131
Number of pages4
ISBN (Print)0818605650
Publication statusPublished - 1984
Externally publishedYes

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Wilson, P. D., Huang, S. C., & Links, J. M. (1984). IMPROVED ESTIMATION OF LOCAL CEREBRAL GLUCOSE METABOLIC RATE USING BAYES REGRESSION ANALYSIS OF PET SCAN DATA. In G. S. Cohen (Ed.), Proceedings - Annual Symposium on Computer Applications in Medical Care (pp. 128-131). IEEE.