Comparative evaluation of scatter correction in 3D PET using different scatter-level approximations

Polycarpou, Irene; Thielemans, Kris; Manjeshwar, Ravindra; Aguiar, Pablo; Marsden, Paul; Tsoumpas, Charalampos

doi:10.1007/s12149-011-0514-y

Cited by 40 publications

(24 citation statements)

References 32 publications

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“…It is interesting to note that the attenuation estimate derived from the TOF-PET data may be used to obtain the scatter estimate 26 with an algorithm like the single scatter simulation (SSS). 37,38 As expected, the accuracy of the method depends on the number of counts of the acquisition. A comparison of the results showed in Figs.…”

Section: Discussionsupporting

confidence: 59%

Sensitivity estimation in time‐of‐flight list‐mode positron emission tomography

Herraiz

Sitek

2015

Medical Physics

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Purpose: An accurate quantification of the images in positron emission tomography (PET) requires knowing the actual sensitivity at each voxel, which represents the probability that a positron emitted in that voxel is finally detected as a coincidence of two gamma rays in a pair of detectors in the PET scanner. This sensitivity depends on the characteristics of the acquisition, as it is affected by the attenuation of the annihilation gamma rays in the body, and possible variations of the sensitivity of the scanner detectors. In this work, the authors propose a new approach to handle time-of-flight (TOF) list-mode PET data, which allows performing either or both, a self-attenuation correction, and self-normalization correction based on emission data only. Methods: The authors derive the theory using a fully Bayesian statistical model of complete data. The authors perform an initial evaluation of algorithms derived from that theory and proposed in this work using numerical 2D list-mode simulations with different TOF resolutions and total number of detected coincidences. Effects of randoms and scatter are not simulated. Results: The authors found that proposed algorithms successfully correct for unknown attenuation and scanner normalization for simulated 2D list-mode TOF-PET data. Conclusions: A new method is presented that can be used for corrections for attenuation and normalization (sensitivity) using TOF list-mode data. C 2015 American Association of Physicists in Medicine. [http://dx

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Section: Discussionsupporting

confidence: 59%

Sensitivity estimation in time‐of‐flight list‐mode positron emission tomography

Herraiz

Sitek

2015

Medical Physics

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“…Random and scatter events are corrected separately for each motion state . The random events are estimated from single events.…”

Section: Methodsmentioning

confidence: 99%

“…A detailed description of the reconstruction algorithm can be found in (35). Random and scatter events are corrected separately for each motion state (36,37). The random events are estimated from single events.…”

Section: Positron Emission Tomography Data Acquisition and Image Recomentioning

confidence: 99%

Fully integrated 3D high‐resolution multicontrast abdominal PET‐MR with high scan efficiency

Kolbitsch

Neji

Fenchel

et al. 2017

Magnetic Resonance in Med

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“…For every ROI the bias and CoV were calculated and used to study how the various reconstruction methods differ from MLEM, and to assess the variability in the ROIs. Scatter correction was performed by STIR as describe by Tsoumpas et al [24] and discussed in more detail by Polycarpou et al [17]. For every ROI the bias and CoV were calculated and used to study how the various reconstruction methods differ from our gold standard, and to assess the variability in the ROIs.…”

Section: Image Analysismentioning

confidence: 99%

Comparative evaluation of image reconstruction methods for the siemens PET-MR scanner using the stir library

Deidda

Efthimiou

Manber

et al. 2016

2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop (NSS/MIC/R

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Abstract-With the introduction of Positron Emission Tomography -Magnetic Resonance (PET-MR) scanners the development of new algorithms and the comparison of the performance of different iterative reconstruction algorithms and the characteristics of the reconstructed images data is relevant . In this work, we perform a quantitative assessment of the currently used ordered subset (OS) algorithms for low-counts PET-MR data taken from a Siemens Biograph mMR scanner using the Software for Tomographic Image Reconstruction (STIR, stir.sf.net). A comparison has been performed in terms of bias and coefficient of variation (CoV). Within the STIR library different algorithms are available, such as Order Subsets Expectation Maximization (OSEM), OS Maximum A Posteriori One Step Late (OSMA-POSL) with Quadratic Prior (QP) and with Median Root Prior (MRP), OS Separable Paraboloidal Surrogate (OSSPS) with QP and Filtered Back-Projection (FBP). In addition, List Mode (LM) reconstruction is available. Corrections for attenuation, scatter and random events are performed using STIR instead of using the scanner. Data from the Hoffman brain phantom are acquired, processed and reconstructed. Clinical data from the thorax of a patient have also been reconstructed with the same algorithms. The number of subsets does not appreciably affect the bias nor the coefficient of variation (CoV=11%) at a fixed sub-iteration number. The percentage relative bias and CoV maximum values for OSMAPOSL-MRP are 10% and 15% at 360 s acquisition and 12% and 15% for the 36 s, whilst for OSMAPOSL-QP they are 6% and 16% for 360 s acquisition and 11% and 23% at 36 s and for OSEM 6% and 11% for the 360 s acquisition and 10% and 15% for the 36 s. Our findings demonstrate that when it comes to low-counts, noise and bias become significant. The methodology for reconstructing Siemens mMR data with STIR is included in the CCP-PET-MR website (www.ccppetmr.ac.uk).

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Comparative evaluation of scatter correction in 3D PET using different scatter-level approximations

Cited by 40 publications

References 32 publications

Sensitivity estimation in time‐of‐flight list‐mode positron emission tomography

Sensitivity estimation in time‐of‐flight list‐mode positron emission tomography

Fully integrated 3D high‐resolution multicontrast abdominal PET‐MR with high scan efficiency

Comparative evaluation of image reconstruction methods for the siemens PET-MR scanner using the stir library

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