PET kinetic analysis: Wavelet denoising of dynamic PET data with application to parametric imaging

Miho Shidahara, Yoko Ikoma, Jeff Kershaw, Yuichi Kimura, Mika Naganawa, Hiroshi Watabe

Research output: Contribution to journalReview articlepeer-review

20 Citations (Scopus)

Abstract

Physiological functions (e.g., cerebral blood flow, glucose metabolism, and neuroreceptor binding) can be investigated as parameters estimated by kinetic modeling using dynamic positron emission tomography (PET) images. Imaging of these physiological parameters, called parametric imaging, can locate the regional distribution of functionalities. However, the most serious technical issue affecting parametric imaging is noise in dynamic PET data. This review describes wavelet denoising of dynamic PET images for improving image quality in estimated parametric images. Wavelet denoising provides significantly improved quality directly to dynamic PET images and indirectly to estimated parametric images. The application of wavelet denoising to radio-ligand and kinetic analysis is still in the development stage, but even so, it is thought that wavelet techniques will have a substantial impact on nuclear medicine in the near future.

Original languageEnglish
Pages (from-to)379-386
Number of pages8
JournalAnnals of Nuclear Medicine
Volume21
Issue number7
DOIs
Publication statusPublished - 2007 Sep 1
Externally publishedYes

Keywords

  • Denoising
  • Kinetic analysis
  • PET
  • Parametric imaging
  • Wavelet transform

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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