Precise System Models using Crystal Penetration Error Compensation for Iterative Image Reconstruction of Preclinical Quad-Head PET

Sooyoung Lee, Seungbin Bae, Hakjae Lee, Kwangdon Kim, Kisung Lee, Kyeong Min Kim, Jaekeon Bae

Research output: Contribution to journalArticle

Abstract

A-PET is a quad-head PET scanner developed for use in small-animal imaging. The dimensions of its volumetric field of view (FOV) are 46.1 × 46.1 × 46.1 mm3 and the gap between the detector modules has been minimized in order to provide a highly sensitive system. However, such a small FOV together with the quad-head geometry causes image quality degradation. The main factor related to image degradation for the quad-head PET is the mispositioning of events caused by the penetration effect in the detector. In this paper, we propose a precise method for modelling the system at the high spatial resolution of the A-PET using a LOR (line of response) based ML-EM (maximum likelihood expectation maximization) that allows for penetration effects. The proposed system model provides the detection probability of every possible ray-path via crystal sampling methods. For the ray-path sampling, the sub-LORs are defined by connecting the sampling points of the crystal pair. We incorporate the detection probability of each sub-LOR into the model by calculating the penetration effect. For comparison, we used a standard LOR-based model and a Monte Carlo-based modeling approach, and evaluated the reconstructed images using both the National Electrical Manufacturers Association NU 4–2008 standards and the Geant4 Application for Tomographic Emission simulation toolkit (GATE). An average full width at half maximum (FWHM) at different locations of 1.77 mm and 1.79 mm are obtained using the proposed system model and standard LOR system model, which does not include penetration effects, respectively. The standard deviation of the uniform region in the NEMA image quality phantom is 2.14% for the proposed method and 14.3% for the LOR system model, indicating that the proposed model out-performs the standard LOR-based model.

Original languageEnglish
Pages (from-to)1764-1773
Number of pages10
JournalJournal of the Korean Physical Society
Volume73
Issue number11
DOIs
Publication statusPublished - 2018 Dec 1

Fingerprint

image reconstruction
penetration
crystals
sampling
field of view
lunar orbital rendezvous
rays
degradation
detectors
scanners
animals
standard deviation
modules
spatial resolution
causes
high resolution
geometry

Keywords

  • Detector modelling and simulations (interaction of photons with matter)
  • Image reconstruction in medical imaging
  • Positron emission tomography (PET)

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Precise System Models using Crystal Penetration Error Compensation for Iterative Image Reconstruction of Preclinical Quad-Head PET. / Lee, Sooyoung; Bae, Seungbin; Lee, Hakjae; Kim, Kwangdon; Lee, Kisung; Kim, Kyeong Min; Bae, Jaekeon.

In: Journal of the Korean Physical Society, Vol. 73, No. 11, 01.12.2018, p. 1764-1773.

Research output: Contribution to journalArticle

Lee, Sooyoung ; Bae, Seungbin ; Lee, Hakjae ; Kim, Kwangdon ; Lee, Kisung ; Kim, Kyeong Min ; Bae, Jaekeon. / Precise System Models using Crystal Penetration Error Compensation for Iterative Image Reconstruction of Preclinical Quad-Head PET. In: Journal of the Korean Physical Society. 2018 ; Vol. 73, No. 11. pp. 1764-1773.
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AB - A-PET is a quad-head PET scanner developed for use in small-animal imaging. The dimensions of its volumetric field of view (FOV) are 46.1 × 46.1 × 46.1 mm3 and the gap between the detector modules has been minimized in order to provide a highly sensitive system. However, such a small FOV together with the quad-head geometry causes image quality degradation. The main factor related to image degradation for the quad-head PET is the mispositioning of events caused by the penetration effect in the detector. In this paper, we propose a precise method for modelling the system at the high spatial resolution of the A-PET using a LOR (line of response) based ML-EM (maximum likelihood expectation maximization) that allows for penetration effects. The proposed system model provides the detection probability of every possible ray-path via crystal sampling methods. For the ray-path sampling, the sub-LORs are defined by connecting the sampling points of the crystal pair. We incorporate the detection probability of each sub-LOR into the model by calculating the penetration effect. For comparison, we used a standard LOR-based model and a Monte Carlo-based modeling approach, and evaluated the reconstructed images using both the National Electrical Manufacturers Association NU 4–2008 standards and the Geant4 Application for Tomographic Emission simulation toolkit (GATE). An average full width at half maximum (FWHM) at different locations of 1.77 mm and 1.79 mm are obtained using the proposed system model and standard LOR system model, which does not include penetration effects, respectively. The standard deviation of the uniform region in the NEMA image quality phantom is 2.14% for the proposed method and 14.3% for the LOR system model, indicating that the proposed model out-performs the standard LOR-based model.

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