Improved image reconstruction in small animal PET using a priori estimates of single-pixel events

Espaa, S.; Herraiz, Joaquín L.; Vicente, E.; Herranz, Elena; Vaquero, J.J.; Desco, Manuel; Udías, J. M.

doi:10.1109/nssmic.2007.4436965

Cited by 8 publications

(7 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Changes induced by therapy in SUV(tumor)/SUV(testicle) values appear 10% larger, in the average of the three rats, for improved OSEM with respect to standard OSEM. This is in accordance with previous studies on phantoms that also showed increased contrast and larger recovery coefficients for the improved 3DOSEM reconstruction [13].…”

Section: B Suvs Computationsupporting

confidence: 93%

“…In one of them, there is no attempt to correct for random counts, scatter or pile-up in the acquisition data. In the other one (improved 3D-OSEM), corrections for randoms, scatter and pile-up are incorporated in the reconstruction algorithm [13].…”

Section: B Calibration Acquisitions and Analysismentioning

confidence: 99%

“…The parameters of all of fits are quoted in table I. The larger values of the coefficients for the improved 3D-OSEM method are due to the fact that a smaller number of counts survive in the image compared to the standard reconstruction, after the (iterative) removal of, mostly, detector scatter counts [13]. In Fig.…”

Section: A Calibration Fitsmentioning

confidence: 99%

See 2 more Smart Citations

Influence of random, pile-up and scatter corrections in the quantification properties of small-animal PET scanners

Vicente

Soto-Montenegro

Espaa

et al. 2007

2007 IEEE Nuclear Science Symposium Conference Record

Self Cite

View full text Add to dashboard Cite

Abstract-The potential of PET imaging for pre-clinical studies will be fully realized only if repeatable, reliable and accurate quantitative analysis can be performed. The characteristic blurring of PET images due to positron range and non co-linearity, as well as random, pile-up and scatter contributions, that may be significant for fully 3D PET acquisitions of small animal, make it difficult their quantitative analysis. In this work specific activity versus specific counts in the image calibration curves for 3D-OSEM reconstructions from a commercially available small animal PET scanner are determined. Both linear and non-linear calibration curves are compared and the effect of corrections for random and scatter contributions are studied. To assess the improvement in the calibration procedure when scatter and random corrections are considered, actual data from a rat tumor pre-and postcancer therapy are analyzed. The results show that correcting for random and scatter corrections can increase the sensitivity of PET images to changes in the biological response of tumors by more than 15%, compared to uncorrected reconstructions.

show abstract

Section: B Suvs Computationsupporting

confidence: 93%

Section: B Calibration Acquisitions and Analysismentioning

confidence: 99%

See 1 more Smart Citation

Influence of random, pile-up and scatter corrections in the quantification properties of small-animal PET scanners

Vicente

Soto-Montenegro

Espaa

et al. 2007

2007 IEEE Nuclear Science Symposium Conference Record

Self Cite

View full text Add to dashboard Cite

show abstract

“…We selected this study for quantification because the expected ideal profile is well known and the heart has also been used for similar comparisons elsewhere. 18,17,19 All the results presented are expressed as a percentage with respect to a baseline reconstruction consisting of FBP with a ramp filter only. Table I shows the filters used in the comparison.…”

Section: Iid Assessment Of Resultsmentioning

confidence: 99%

Sinogram bow‐tie filtering in FBP PET reconstruction

Abella¹,

Vaquero²,

Soto-Montenegro³

et al. 2009

Medical Physics

Self Cite

View full text Add to dashboard Cite

Low-pass filtering of sinograms in the radial direction is the most common practice to limit noise amplification in filtered back projection ͑FBP͒ reconstruction of positron emission tomography studies. Other filtering strategies have been proposed to prevent the loss in resolution due to low-pass radial filters, although results have been diverse. Using the well-known properties of the Fourier transform of a sinogram, the authors defined a binary mask that matches the expected shape of the support region in the Fourier domain of the sinogram ͑"bow tie"͒. This mask was smoothed by a convolution with a ten-point Gaussian kernel which not only avoids ringing but also introduces a pre-emphasis at low frequencies. A new filtering scheme for FBP is proposed, comprising this smoothed bow-tie filter combined with a standard radial filter and an axial filter. The authors compared the performance of the bow-tie filtering scheme with that of other previously reported methods: Standard radial filtering, angular filtering, and stackgram-domain filtering. All the quantitative data in the comparisons refer to a baseline reconstruction using a ramp filter only. When using the smallest size of the Gaussian kernel in the stackgram domain, the authors achieved a noise reduction of 33% at the cost of degrading radial and tangential resolutions ͑14.5% and 16%, respectively, for cubic interpolation͒. To reduce the noise by 30%, the angular filter produced a larger degradation of contrast ͑3%͒ and tangential resolution ͑46% at 10 mm from the center of the field of view͒ and showed noticeable artifacts in the form of circular blurring dependent on the distance to the center of the field of view. For a similar noise reduction ͑33%͒, the proposed bow-tie filtering scheme yielded optimum results in resolution ͑gain in radial resolution of 10%͒ and contrast ͑1% increase͒ when compared with any of the other filters alone. Experiments with rodent images showed noticeable image quality enhancement when using the proposed bow-tie filtering scheme.

show abstract

“…Indeed, with the help of detailed simulations, it is possible to establish a correlation between the parameters recorded by the scanner for each count, such as rate of coincidences and, if available, of singles too, XY-positioning of the interaction as provided by standard Anger algorithms, energy deposited in the detectors and the likelihood of the count acquired of being assigned to the correct crystal of first interaction. Details of this procedure have been given in España et al (2007b). Due to detector pile-up, coincidences acquired at high rates will suffer, more often than the ones at low rates, of wrong crystal positioning.…”

Section: Advanced Use Of Simulationsmentioning

confidence: 99%

PeneloPET, a Monte Carlo PET simulation tool based on PENELOPE: features and validation

et al. 2009

View full text Add to dashboard Cite

Monte Carlo simulations play an important role in positron emission tomography (PET) imaging, as an essential tool for the research and development of new scanners and for advanced image reconstruction. PeneloPET, a PET-dedicated Monte Carlo tool, is presented and validated in this work. PeneloPET is based on PENELOPE, a Monte Carlo code for the simulation of the transport in matter of electrons, positrons and photons, with energies from a few hundred eV to 1 GeV. PENELOPE is robust, fast and very accurate, but it may be unfriendly to people not acquainted with the FORTRAN programming language. PeneloPET is an easy-to-use application which allows comprehensive simulations of PET systems within PENELOPE. Complex and realistic simulations can be set by modifying a few simple input text files. Different levels of output data are available for analysis, from sinogram and lines-of-response (LORs) histogramming to fully detailed list mode. These data can be further exploited with the preferred programming language, including ROOT. PeneloPET simulates PET systems based on crystal array blocks coupled to photodetectors and allows the user to define radioactive sources, detectors, shielding and other parts of the scanner. The acquisition chain is simulated in high level detail; for instance, the electronic processing can include pile-up rejection mechanisms and time stamping of events, if desired. This paper describes PeneloPET and shows the results of extensive validations and comparisons of simulations against real measurements from commercial acquisition systems. PeneloPET is being extensively employed to improve the image quality of commercial PET systems and for the development of new ones.1

show abstract

Improved image reconstruction in small animal PET using a priori estimates of single-pixel events

Cited by 8 publications

References 5 publications

Influence of random, pile-up and scatter corrections in the quantification properties of small-animal PET scanners

Influence of random, pile-up and scatter corrections in the quantification properties of small-animal PET scanners

Sinogram bow‐tie filtering in FBP PET reconstruction

PeneloPET, a Monte Carlo PET simulation tool based on PENELOPE: features and validation

Contact Info

Product

Resources

About