Blind deblurring reconstruction technique with applications in PET imaging

Heng Li, Feng Qiao, Osama R. Mawlawt, Yibin Zheng, Ronald X. Zhu

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

Abstract

In this study, an empirical PET system model taking account for system blurring is developed and a blind iterative reconstruction scheme that estimate of both the actual image and the PSF of the system is derived based on the system model. Reconstruction images with higher quality can be acquired by applying the proposed reconstruction technique for both synthetic and experimental data. In the synthetic data study, the algorithm reduces image blurring and preserves the edges without introducing extra artifacts. The localized measurement shows that the performance of reconstruction image improved by up to 50%. In experimental studies, the contrast and quality of reconstruction is substantially improved. The proposed method shows promising in tumor localization and quantification.

Original languageEnglish (US)
Title of host publication2007 4th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro - Proceedings
Pages173-176
Number of pages4
DOIs
StatePublished - 2007
Externally publishedYes
Event2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07 - Arlington, VA, United States
Duration: Apr 12 2007Apr 15 2007

Publication series

Name2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings

Other

Other2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07
CountryUnited States
CityArlington, VA
Period4/12/074/15/07

Keywords

  • Deblurring
  • Iterative reconstruction
  • PET

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Medicine(all)

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