Randoms variance reduction in 3D PET

Ramsey D Badawi, M. P. Miller, D. L. Bailey, P. K. Marsden

Research output: Contribution to journalArticle

54 Citations (Scopus)

Abstract

In positron emission tomography (PET), random coincidence events must be removed from the measured signal in order to obtain quantitatively accurate data. The most widely implemented technique for estimating the number of random coincidences on a particular line of response is the delayed coincidence channel method. Estimates obtained in this way are subject to Poisson noise, which then propagates into the final image when the estimates are subtracted from the prompt signal. However, this noise may be reduced if variance reduction techniques similar to those used in normalization of PET detectors are applied to the randoms estimates prior to use. We have investigated the effects of randoms variance reduction on noise-equivalent count (NEC) rates on a whole-body PET camera operating in 3D mode. NEC rates were calculated using a range of phantoms representative of situations that might be encountered clinically. We have also investigated the properties of three randoms variance reduction methods (based on algorithms previously used for normalization) in terms of their systematic accuracy and their variance reduction efficacy, both in phantom studies and in vivo. Those algorithms investigated that do not make assumptions about the spatial distribution of random coincidences give the best estimates of the randoms distribution. With the camera used, which has a limited axial extent (10.8 cm) and a large ring diameter (102 cm), the gains in image signal-to-noise ratio obtained with this technique ranged from ~5% to ~15%, depending on object size, activity distribution and the amount of activity in the field of view. Larger gains would be expected if this technique were to be employed on cameras of greater axial extent and smaller ring diameter.

Original languageEnglish (US)
Pages (from-to)941-954
Number of pages14
JournalPhysics in Medicine and Biology
Volume44
Issue number4
DOIs
StatePublished - Apr 1999
Externally publishedYes

Fingerprint

Positron emission tomography
Positron-Emission Tomography
Noise
positrons
tomography
Cameras
cameras
estimates
rings
Signal-To-Noise Ratio
Spatial distribution
field of view
Signal to noise ratio
spatial distribution
signal to noise ratios
estimating
Detectors
detectors

ASJC Scopus subject areas

  • Biomedical Engineering
  • Physics and Astronomy (miscellaneous)
  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology

Cite this

Randoms variance reduction in 3D PET. / Badawi, Ramsey D; Miller, M. P.; Bailey, D. L.; Marsden, P. K.

In: Physics in Medicine and Biology, Vol. 44, No. 4, 04.1999, p. 941-954.

Research output: Contribution to journalArticle

Badawi, RD, Miller, MP, Bailey, DL & Marsden, PK 1999, 'Randoms variance reduction in 3D PET', Physics in Medicine and Biology, vol. 44, no. 4, pp. 941-954. https://doi.org/10.1088/0031-9155/44/4/010
Badawi, Ramsey D ; Miller, M. P. ; Bailey, D. L. ; Marsden, P. K. / Randoms variance reduction in 3D PET. In: Physics in Medicine and Biology. 1999 ; Vol. 44, No. 4. pp. 941-954.
@article{cec1f7907e2e443dbad3884e6d093b06,
title = "Randoms variance reduction in 3D PET",
abstract = "In positron emission tomography (PET), random coincidence events must be removed from the measured signal in order to obtain quantitatively accurate data. The most widely implemented technique for estimating the number of random coincidences on a particular line of response is the delayed coincidence channel method. Estimates obtained in this way are subject to Poisson noise, which then propagates into the final image when the estimates are subtracted from the prompt signal. However, this noise may be reduced if variance reduction techniques similar to those used in normalization of PET detectors are applied to the randoms estimates prior to use. We have investigated the effects of randoms variance reduction on noise-equivalent count (NEC) rates on a whole-body PET camera operating in 3D mode. NEC rates were calculated using a range of phantoms representative of situations that might be encountered clinically. We have also investigated the properties of three randoms variance reduction methods (based on algorithms previously used for normalization) in terms of their systematic accuracy and their variance reduction efficacy, both in phantom studies and in vivo. Those algorithms investigated that do not make assumptions about the spatial distribution of random coincidences give the best estimates of the randoms distribution. With the camera used, which has a limited axial extent (10.8 cm) and a large ring diameter (102 cm), the gains in image signal-to-noise ratio obtained with this technique ranged from ~5{\%} to ~15{\%}, depending on object size, activity distribution and the amount of activity in the field of view. Larger gains would be expected if this technique were to be employed on cameras of greater axial extent and smaller ring diameter.",
author = "Badawi, {Ramsey D} and Miller, {M. P.} and Bailey, {D. L.} and Marsden, {P. K.}",
year = "1999",
month = "4",
doi = "10.1088/0031-9155/44/4/010",
language = "English (US)",
volume = "44",
pages = "941--954",
journal = "Physics in Medicine and Biology",
issn = "0031-9155",
publisher = "IOP Publishing Ltd.",
number = "4",

}

TY - JOUR

T1 - Randoms variance reduction in 3D PET

AU - Badawi, Ramsey D

AU - Miller, M. P.

AU - Bailey, D. L.

AU - Marsden, P. K.

PY - 1999/4

Y1 - 1999/4

N2 - In positron emission tomography (PET), random coincidence events must be removed from the measured signal in order to obtain quantitatively accurate data. The most widely implemented technique for estimating the number of random coincidences on a particular line of response is the delayed coincidence channel method. Estimates obtained in this way are subject to Poisson noise, which then propagates into the final image when the estimates are subtracted from the prompt signal. However, this noise may be reduced if variance reduction techniques similar to those used in normalization of PET detectors are applied to the randoms estimates prior to use. We have investigated the effects of randoms variance reduction on noise-equivalent count (NEC) rates on a whole-body PET camera operating in 3D mode. NEC rates were calculated using a range of phantoms representative of situations that might be encountered clinically. We have also investigated the properties of three randoms variance reduction methods (based on algorithms previously used for normalization) in terms of their systematic accuracy and their variance reduction efficacy, both in phantom studies and in vivo. Those algorithms investigated that do not make assumptions about the spatial distribution of random coincidences give the best estimates of the randoms distribution. With the camera used, which has a limited axial extent (10.8 cm) and a large ring diameter (102 cm), the gains in image signal-to-noise ratio obtained with this technique ranged from ~5% to ~15%, depending on object size, activity distribution and the amount of activity in the field of view. Larger gains would be expected if this technique were to be employed on cameras of greater axial extent and smaller ring diameter.

AB - In positron emission tomography (PET), random coincidence events must be removed from the measured signal in order to obtain quantitatively accurate data. The most widely implemented technique for estimating the number of random coincidences on a particular line of response is the delayed coincidence channel method. Estimates obtained in this way are subject to Poisson noise, which then propagates into the final image when the estimates are subtracted from the prompt signal. However, this noise may be reduced if variance reduction techniques similar to those used in normalization of PET detectors are applied to the randoms estimates prior to use. We have investigated the effects of randoms variance reduction on noise-equivalent count (NEC) rates on a whole-body PET camera operating in 3D mode. NEC rates were calculated using a range of phantoms representative of situations that might be encountered clinically. We have also investigated the properties of three randoms variance reduction methods (based on algorithms previously used for normalization) in terms of their systematic accuracy and their variance reduction efficacy, both in phantom studies and in vivo. Those algorithms investigated that do not make assumptions about the spatial distribution of random coincidences give the best estimates of the randoms distribution. With the camera used, which has a limited axial extent (10.8 cm) and a large ring diameter (102 cm), the gains in image signal-to-noise ratio obtained with this technique ranged from ~5% to ~15%, depending on object size, activity distribution and the amount of activity in the field of view. Larger gains would be expected if this technique were to be employed on cameras of greater axial extent and smaller ring diameter.

UR - http://www.scopus.com/inward/record.url?scp=0033046365&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033046365&partnerID=8YFLogxK

U2 - 10.1088/0031-9155/44/4/010

DO - 10.1088/0031-9155/44/4/010

M3 - Article

C2 - 10232807

AN - SCOPUS:0033046365

VL - 44

SP - 941

EP - 954

JO - Physics in Medicine and Biology

JF - Physics in Medicine and Biology

SN - 0031-9155

IS - 4

ER -