FDG-PET parametric imaging by total variation minimization

Hongbin Guo, Rosemary Renaut, Kewei Chen, Eric Reiman

Research output: Contribution to journalArticle

13 Scopus citations

Abstract

Parametric imaging of the cerebral metabolic rate for glucose (CMRGlc) using [18F]-fluoro deoxyglucose positron emission tomography is considered. Traditional imaging is hindered due to low signal-to-noise ratios at individual voxels. We propose to minimize the total variation of the tracer uptake rates while requiring good fit of traditional Patlak equations. This minimization guarantees spatial homogeneity within brain regions and good distinction between brain regions. Brain phantom simulations demonstrate significant improvement in quality of images by the proposed method as compared to Patlak images with post-filtering using Gaussian or median filters.

Original languageEnglish (US)
Pages (from-to)295-303
Number of pages9
JournalComputerized Medical Imaging and Graphics
Volume33
Issue number4
DOIs
StatePublished - Jun 1 2009

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Keywords

  • Alzheimer's disease
  • FDG
  • Graphical analysis
  • PET quantification
  • Parametric imaging
  • Patlak plot
  • Total variation
  • Uptake rate

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Graphics and Computer-Aided Design

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