A likelihood-based framework for quantification of brain receptor PET studies in the pixel domain

Z. Jane Wang, Zsolt Szabo, Zhu Han, Jozsef Varga, K. J.Ray Liu

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

Abstract

Quantification of receptor binding studies obtained with PET is complicated by tissue heterogeneity in the sampling image elements pixels and voxels. This effect is caused by a limited spatial resolution of the PET scanner. On the other hand, spatial heterogeneity is often essential in understanding the underlying receptor binding process. In this paper, we propose a likelihood-based framework in the pixel domain for quantitative imaging with or without the input function. Radioligand kinetic parameters are estimated together with the input function. The parameters are initialized by a subspace-based algorithm, and further refined by an iterative likelihood-based estimation procedure. The performances of the proposed scheme is examined by simulations. Real brain PET data are also examined to show the performance in determining the time activity curves and the underlying factor images.

Original languageEnglish (US)
Title of host publication2004 2nd IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationMacro to Nano
Pages1381-1384
Number of pages4
StatePublished - Dec 1 2004
Event2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano - Arlington, VA, United States
Duration: Apr 15 2004Apr 18 2004

Publication series

Name2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano
Volume2

Other

Other2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano
CountryUnited States
CityArlington, VA
Period4/15/044/18/04

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Wang, Z. J., Szabo, Z., Han, Z., Varga, J., & Liu, K. J. R. (2004). A likelihood-based framework for quantification of brain receptor PET studies in the pixel domain. In 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (pp. 1381-1384). (2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano; Vol. 2).