A method for point spread function estimation for accurate quantitative imaging
Aim: A method to determine the point spread function (PSF) of an imaging system based on a set of 3-D Gaussian functions is presented for a robust estimation of the recovery corrections for accurate activity quantification in positron emission tomography (PET) and single-photon emission computed tom...
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| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
March 2018
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| In: |
IEEE transactions on nuclear science
Year: 2018, Jahrgang: 65, Heft: 3, Pages: 961-969 |
| ISSN: | 1558-1578 |
| Online-Zugang: |
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| Verfasserangaben: | A.A. Attarwala, D. Hardiansyah, C. Romanó, M. Roscher, F. Molina-Duran, B. Wängler, and G. Glatting |
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| 100 | 1 | |a Attarwala, Ali Asgar |d 1984- |e VerfasserIn |0 (DE-588)1070231711 |0 (DE-627)823391671 |0 (DE-576)429872852 |4 aut | |
| 245 | 1 | 2 | |a A method for point spread function estimation for accurate quantitative imaging |c A.A. Attarwala, D. Hardiansyah, C. Romanó, M. Roscher, F. Molina-Duran, B. Wängler, and G. Glatting |
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| 520 | |a Aim: A method to determine the point spread function (PSF) of an imaging system based on a set of 3-D Gaussian functions is presented for a robust estimation of the recovery corrections for accurate activity quantification in positron emission tomography (PET) and single-photon emission computed tomography systems. Materials and Methods: The spatial resolution of the ALBIRA II PET subsystem was determined using a 370-kBq 22Na point source. The measured data were reconstructed with a maximum-likelihood expectation-maximization algorithm. The PSF was calculated based on the National Electrical Manufacturing Association (NEMA) NU4 2008 protocol and on alternative methods based on three 3-D fitting functions for the xyz-directions: 1) a 3-D Gaussian function (3-D 1-Gauss) and convolutions of this function with a pixel size (3-D Gaussp) or source dimension of Ø 0.25 mm (3-D Gausss); 2) the sum of two Gaussian functions (3-D 2-Gauss); and 3) three Gaussian functions (3-D 3-Gauss). Goodness of fit and the method based on an Akaike information criterion were used for choosing the best function. A MATLAB-based mathematical source simulation study was performed to quantify the relevance of PSFs calculated from the different methods. Results: Based on the PSFs calculated from the NEMA protocol, the full-width at half-maximum (FWHM) in xyz-directions were 1.68, 1.51, and 1.50 mm. The corresponding results using 3-D Gauss and 3-D Gausss functions both were (1.87 ± 0.01), (1.70 ± 0.01), and (1.50 ± 0.01) mm and for 3-D Gauss,, were (1.84 ± 0.01), (1.67 ± 0.01), and (1.47 ± 0.01) mm. The FWHMs calculated with 3-D 2-Gauss and 3-D 3-Gauss were (1.78 ± 0.01), (1.74 ± 0.01), and (1.83 ± 0.01) mm and (1.76 ± 0.03), (1.72 ± 0.03), and (1.78 ± 0.03) mm, respectively. All coefficients of variations of the fit parameters were ≤29% and the adjusted R2 were ≥0.99. Based on Akaike weights wi, the 3-D 3-Gauss method was best supported by the data (wi = 100%). The simulation study showed a relative error in quantification of spherical lesions in the range of 15%-45% for lesions of diameters 1-5 mm compared to the PSFs based on the NEMA method. Conclusion: An alternative method to calculate the PSFs of imaging systems to accurately correct for recovery effects is presented. The proposed method includes choosing and fitting of 3-D functions, validation of fitting quality, and choosing the function best supported by the data along with an estimation of the uncertainty. | ||
| 650 | 4 | |a 1-Gauss | |
| 650 | 4 | |a 3D fitting functions | |
| 650 | 4 | |a 3D Gaussian function | |
| 650 | 4 | |a Akaike information criterion | |
| 650 | 4 | |a Akaike information criterion (AIC) | |
| 650 | 4 | |a Detectors | |
| 650 | 4 | |a Estimation | |
| 650 | 4 | |a expectation-maximisation algorithm | |
| 650 | 4 | |a Fitting | |
| 650 | 4 | |a full-width at half-maximum | |
| 650 | 4 | |a FWHMs | |
| 650 | 4 | |a Gaussian function | |
| 650 | 4 | |a image reconstruction | |
| 650 | 4 | |a Image reconstruction | |
| 650 | 4 | |a image resolution | |
| 650 | 4 | |a Imaging | |
| 650 | 4 | |a MATLAB-based mathematical source simulation | |
| 650 | 4 | |a maximum-likelihood expectation-maximization algorithm | |
| 650 | 4 | |a measured data reconstruction | |
| 650 | 4 | |a medical image processing | |
| 650 | 4 | |a National Electrical Manufacturing Association (NEMA) | |
| 650 | 4 | |a National Electrical Manufacturing Association NU4 2008 protocol | |
| 650 | 4 | |a NEMA method | |
| 650 | 4 | |a NU4 | |
| 650 | 4 | |a optical transfer function | |
| 650 | 4 | |a phantoms | |
| 650 | 4 | |a pixel size | |
| 650 | 4 | |a point spread function (PSF) | |
| 650 | 4 | |a point spread function estimation | |
| 650 | 4 | |a single photon emission computed tomography | |
| 650 | 4 | |a single-photon emission | |
| 650 | 4 | |a size 0.25 mm | |
| 650 | 4 | |a size 1.0 mm to 5.0 mm | |
| 650 | 4 | |a size 1.5 mm | |
| 650 | 4 | |a size 1.51 mm | |
| 650 | 4 | |a size 1.68 mm | |
| 650 | 4 | |a Spatial resolution | |
| 650 | 4 | |a spherical lesions | |
| 650 | 4 | |a Three-dimensional displays | |
| 650 | 4 | |a xyz-directions | |
| 700 | 1 | |a Wängler, Björn |d 1975- |e VerfasserIn |0 (DE-588)129702218 |0 (DE-627)477593909 |0 (DE-576)297793888 |4 aut | |
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