Reduction of noise amplification in SPECT using smaller detector bin size

Do Sik Hwang, Gengsheng L. Zeng

Research output: Contribution to journalConference article

1 Citation (Scopus)

Abstract

In SPECT iterative reconstruction methods, such as the ML-EM (Maximum Likelihood Expectation Maximization) algorithm, the noise propagation from the projection measurements into the reconstructed image has been a difficult problem to control as the algorithm iterates. In this paper, we show that the noise amplification can be reduced by using a detector whose bin size is smaller than the image pixel size without applying any regularization methods or changing any other factors. We compare different detector system characteristics using SVD (Singular Value Decomposition) analysis, show the noise properties in each detector system through both simulation studies and physical phantom studies, and finally compare how the noise amplification affects the image quality in different detector systems. The ML-EM algorithm when used in conjunction with a smaller detector bin size has better convergent properties, reduces noise amplification, and produces better image quality.

Original languageEnglish
Pages (from-to)2543-2547
Number of pages5
JournalIEEE Nuclear Science Symposium Conference Record
Volume4
Publication statusPublished - 2004 Dec 1

Fingerprint

Single-Photon Emission-Computed Tomography
Noise
detectors
noise propagation
projection
pixels
decomposition
simulation

All Science Journal Classification (ASJC) codes

  • Radiation
  • Nuclear and High Energy Physics
  • Radiology Nuclear Medicine and imaging

Cite this

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abstract = "In SPECT iterative reconstruction methods, such as the ML-EM (Maximum Likelihood Expectation Maximization) algorithm, the noise propagation from the projection measurements into the reconstructed image has been a difficult problem to control as the algorithm iterates. In this paper, we show that the noise amplification can be reduced by using a detector whose bin size is smaller than the image pixel size without applying any regularization methods or changing any other factors. We compare different detector system characteristics using SVD (Singular Value Decomposition) analysis, show the noise properties in each detector system through both simulation studies and physical phantom studies, and finally compare how the noise amplification affects the image quality in different detector systems. The ML-EM algorithm when used in conjunction with a smaller detector bin size has better convergent properties, reduces noise amplification, and produces better image quality.",
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Reduction of noise amplification in SPECT using smaller detector bin size. / Hwang, Do Sik; Zeng, Gengsheng L.

In: IEEE Nuclear Science Symposium Conference Record, Vol. 4, 01.12.2004, p. 2543-2547.

Research output: Contribution to journalConference article

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