A Hybrid Maximum Likelihood Position Computer for Scintillation Cameras

Clinthorne, N.H.; Rogers, W.L.; Shao, L. G.; Koral, Kenneth F.

doi:10.1109/tns.1987.4337309

Cited by 55 publications

(27 citation statements)

References 5 publications

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“…We have previously investigated a continuous miniature crystal element (cMiCE) detector composed of a 50 mm by 50 mm by 8 mm thick slab of LYSO coupled to a 52 mm square, 64-channel flat panel photomultiplier tube (PMT, Hamamatsu H8500, Japan) as a lower cost alternative to high resolution discrete crystal designs [9]. A statistics based positioning (SBP) algorithm [10], similar to previously proposed Maximum-likelihood (ML) methods [11]- [13], is used which improves the positioning characteristics of the detector versus using standard or modified Anger positioning schemes. This improvement is most dramatic near the edges and corners of the crystal.…”

Section: Introductionmentioning

confidence: 99%

Effect of Number of Readout Channels on the Intrinsic Spatial Resolution Performance of a Continuous Miniature Crystal Element (cMiCE) Detector

Miyaoka

Ling

Lewellen

2007

IEEE Trans. Nucl. Sci.

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In this work we investigate how the intrinsic spatial resolution varies with the number of digitized readout channels for a 64 (8×8) channel detector using a statistics-based positioning algorithm. We report results for both 6 mm and 8 mm thick crystals. Three channel reduction schemes are explored. The simplest scheme is row and column summing (R-C sum) of the photomultiplier tube channels. The second method is to only use channels with signals above a 1% threshold of the total signal (1% thres). The third method is to acquire a subset of PMT channels determined by the maximum signal channel (zone mask). The full width at half maximum (FWHM) intrinsic spatial resolution results for the central and corner sections of the detector are presented for each of the methods. All methods except R-C sum performed well for the central section of the detector. The 1% thres and zone mask schemes showed significant improvement for the corner section of the 6 mm thick crystal. All methods using a single depth look-up table had difficulty in the corner region for the 8 mm thick crystal. We believe this is caused by depth dependent edge effects on the light response function. Initial results using a depth dependent look-up table show improved positioning performance.

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Section: Introductionmentioning

confidence: 99%

Effect of Number of Readout Channels on the Intrinsic Spatial Resolution Performance of a Continuous Miniature Crystal Element (cMiCE) Detector

Miyaoka

Ling

Lewellen

2007

IEEE Trans. Nucl. Sci.

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“…(2) reduces to (3) The maximum likelihood solution is achieved by minimizing the quantity inside the bracket in Eq. (3).…”

Section: Statistics-based Positioning (Sbp) Methodsmentioning

confidence: 99%

“…In principle, one cannot directly measure the threedimensional light response function (LRF) and systems are characterized using twodimensional light distribution characteristics. [2][3][4] Milster et al 4) used a 5-bit compressed energy signal as part of their light response characterization. Gagnon et al 5) and Tomitani et al 6) have proposed methods to characterize DOI for large NaI(Tl) detectors using maximum likelihood positioning methods.…”

Section: Introductionmentioning

confidence: 99%

Detector Light Response Modeling for a Thick Continuous Slab Detector

Miyaoka

Joo

Lee

2008

J. Nucl. Sci. Technol.

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We investigate a method to improve the position decoding for thick crystal versions (i.e., ≥8 mm) of the continuous miniature crystal element (cMiCE) PET detector by more accurately modeling the detector light response function (LRF). The LRF for continuous detectors varies with the depth of interaction (DOI) of the detected photon. This variation in LRF can result in a positioning error for two-dimensional positioning algorithms. We explore a method to improve positioning performance by deriving two lookup tables, corresponding to the front and back regions of the crystal. The DETECT2000 simulation package was used to investigate the light response characteristics for a 48.8 mm by 48.8 mm by 10 (8) mm slab of LSO coupled to a 64-channel, flat-panel PMT. The data are then combined to produce the two-dimensional light collection histograms. Light collection histograms that have markedly non-Gaussian distributions are characterized as a combination of two Gaussian functions, where each Gaussian function corresponds to a DOI region of the crystal. The results indicate that modest gains in positioning accuracy are achieved near the central region of the crystal. However, significant improvements in spatial resolution and positioning bias are achieved for the corner section of the detector.

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“…The probability of producing N optical scintillation photons given energy E deposited is modeled as a discrete normal distribution with mean and variance . In the simulations, because the mean and variance of this discrete normal distribution are relatively large, the probability of N is approximated by a sampled continuous normal distribution [25] given by (10) Even if Q is a function of the deposited gamma-ray energy, the relationship between the deposited gamma-ray energy and average number of scintillation photons emitted is a monotonically increasing function; as we increase the energy of the gamma-ray photons, on average, a larger number of scintillation photons are emitted. Therefore, instead of estimating the position of interaction and the deposited gamma-ray photon energy (x,y,z,E), we can estimate the position of interaction and the mean number of scintillation photons emitted .…”

Section: A Modeling the Scintillation Processmentioning

confidence: 99%

Impact of fano factor on position and energy estimation in scintillation detectors

et al. 2013

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The Fano factor for an integer-valued random variable is defined as the ratio of its variance to its mean. Light from various scintillation crystals have been reported to have Fano factors from subPoisson (Fano factor < 1) to super-Poisson (Fano factor > 1). For a given mean, a smaller Fano factor implies a smaller variance and thus less noise. We investigated if lower noise in the scintillation light will result in better spatial and energy resolutions. The impact of Fano factor on the estimation of position of interaction and energy deposited in simple gamma-camera geometries is estimated by two methods -calculating the Cramér-Rao bound and estimating the variance of a maximum likelihood estimator. The methods are consistent with each other and indicate that when estimating the position of interaction and energy deposited by a gamma-ray photon, the Fano factor of a scintillator does not affect the spatial resolution. A smaller Fano factor results in a better energy resolution.

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A Hybrid Maximum Likelihood Position Computer for Scintillation Cameras

Cited by 55 publications

References 5 publications

Effect of Number of Readout Channels on the Intrinsic Spatial Resolution Performance of a Continuous Miniature Crystal Element (cMiCE) Detector

Effect of Number of Readout Channels on the Intrinsic Spatial Resolution Performance of a Continuous Miniature Crystal Element (cMiCE) Detector

Detector Light Response Modeling for a Thick Continuous Slab Detector

Impact of fano factor on position and energy estimation in scintillation detectors

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