A review on segmentation of positron emission tomography images

Brent Foster, Ulas Bagci*, Awais Mansoor, Ziyue Xu, Daniel J. Mollura

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

205 Scopus citations

Abstract

Positron Emission Tomography (PET), a non-invasive functional imaging method at the molecular level, images the distribution of biologically targeted radiotracers with high sensitivity. PET imaging provides detailed quantitative information about many diseases and is often used to evaluate inflammation, infection, and cancer by detecting emitted photons from a radiotracer localized to abnormal cells. In order to differentiate abnormal tissue from surrounding areas in PET images, image segmentation methods play a vital role; therefore, accurate image segmentation is often necessary for proper disease detection, diagnosis, treatment planning, and follow-ups. In this review paper, we present state-of-the-art PET image segmentation methods, as well as the recent advances in image segmentation techniques. In order to make this manuscript self-contained, we also briefly explain the fundamentals of PET imaging, the challenges of diagnostic PET image analysis, and the effects of these challenges on the segmentation results.

Original languageEnglish (US)
Pages (from-to)76-96
Number of pages21
JournalComputers in Biology and Medicine
Volume50
DOIs
StatePublished - Jul 1 2014
Externally publishedYes

Keywords

  • Image segmentation
  • MRI-PET
  • PET
  • PET-CT
  • Review
  • SUV
  • Thresholding

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

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