Novel positioning method using Gaussian mixture model for a monolithic scintillator-based detector in positron emission tomography

Seungbin Bae, Kisung Lee, Changwoo Seo, Jungmin Kim, Joo Sung-Kwan Joo, Jinhun Joung

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

We developed a high precision position decoding method for a positron emission tomography (PET) detector that consists of a thick slab scintillator coupled with a multichannel photomultiplier tube (PMT). The DETECT2000 simulation package was used to validate light response characteristics for a 48.8 mm×48.8 mm×10 mm slab of lutetium oxyorthosilicate coupled to a 64 channel PMT. The data are then combined to produce light collection histograms. We employed a Gaussian mixture model (GMM) to parameterize the composite light response with multiple Gaussian mixtures. In the training step, light photons acquired by N PMT channels was used as an N-dimensional feature vector and were fed into a GMM training model to generate optimal parameters for M mixtures. In the positioning step, we decoded the spatial locations of incident photons by evaluating a sample feature vector with respect to the trained mixture parameters. The average spatial resolutions after positioning with four mixtures were 1.1 mm full width at half maximum (FWHM) at the corner and 1.0 mm FWHM at the center section. This indicates that the proposed algorithm achieved high performance in both spatial resolution and positioning bias, especially at the corner section of the detector.

Original languageEnglish
Article number093606
JournalOptical Engineering
Volume50
Issue number9
DOIs
Publication statusPublished - 2011 Sep

Keywords

  • Continuous crystal
  • Flat panel photomultiplier tube
  • Gaussian mixture
  • Positioning algorithm
  • Positron emission tomography

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering(all)

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