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Fully 3-D PET reconstruction with system matrix derived from point source measurements

Panin, V.Y., Kehren, F., Michel, C., Casey, M.·2006·IEEE Transactions on Medical Imaging

DOI 10.1109/tmi.2006.876171

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Abstract

The quality of images reconstructed by statistical iterative methods depends on an accurate model of the relationship between image space and projection space through the system matrix The elements of the system matrix for the clinical Hi-Rez scanner were derived by processing the data measured for a point source at different positions in a portion of the field of view. These measured data included axial compression and azimuthal interleaving of adjacent projections. Measured data were corrected for crystal and geometrical efficiency. Then, a whole system matrix was derived by processing the responses in projection space. Such responses included both geometrical and detection physics components of the system matrix. The response was parameterized to correct for point source location and to smooth for projection noise. The model also accounts for axial compression (span) used on the scanner. The forward projector for iterative reconstruction was constructed using the estimated response parameters. This paper extends our previous work to fully three-dimensional. Experimental data were used to compare images reconstructed by the standard iterative reconstruction software and the one modeling the response function. The results showed that the modeling of the response function improves both spatial resolution and noise properties.

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Numerical recipes in C: the art of scientific computing
(1993) · Choice Reviews Online · doi:10.5860/choice.30-5638 · Cited by 17,933
Numerical recipes in Pascal: the art of scientific computing
(1990) · Choice Reviews Online · doi:10.5860/choice.27-5158 · Cited by 12,040
Numerical Recipes in C: The Art of Scientific Computing.
Birchenhall, C. R., Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (1994) · The Economic Journal · doi:10.2307/2234664 · Cited by 4,355
Accelerated image reconstruction using ordered subsets of projection data
Hudson, H. M., & Larkin, R. S. (1994) · IEEE Transactions on Medical Imaging · doi:10.1109/42.363108 · Cited by 3,713
Bayesian reconstructions from emission tomography data using a modified EM algorithm
Green, P. J. (1990) · IEEE Transactions on Medical Imaging · doi:10.1109/42.52985 · Cited by 1,242
Exact and approximate rebinning algorithms for 3-D PET data
Defrise, M., Kinahan, P. E., Townsend, D. W., Michel, C. J., Sibomana, M., & Newport, D. F. (1997) · IEEE Transactions on Medical Imaging · doi:10.1109/42.563660 · Cited by 757
Self-citation
High-resolution 3D Bayesian image reconstruction using the microPET small-animal scanner
Qi, J., Leahy, R. M., Cherry, S. R., Chatziioannou, A. F., & Farquhar, T. H. (1998) · Physics in Medicine and Biology · doi:10.1088/0031-9155/43/4/027 · Cited by 634
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Watson, C. C. (2000) · IEEE Transactions on Nuclear Science · doi:10.1109/23.873020 · Cited by 520
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Joseph, P. M. (1982) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.1982.4307572 · Cited by 378
OSEM-3D Reconstruction Strategies for the ECAT HRRT
Comtat, Bataille, F., Michel, C. J., Jones, J. P., Sibomana, M., Janeiro, L., & Trébossen, R. (2005) · IEEE Symposium Conference Record Nuclear Science 2004. · doi:10.1109/nssmic.2004.1466639 · Cited by 133
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Research works printed but not linked: 2

casey, 0, a component based method for normalization in volume pet, Proc 1995 Int Meeting Fully Three-Dimensional Image Reconstruction Radiol Nucl Med, 67
panin, 0, a 3-d ordinary poisson em iterative reconstruction algorithm for ring pet scanner, 2005 Soc Nucl Med Meeting

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Authors: Panin, V. Y., Kehren, F., Michel, C., & Casey, M.
Affiliations: Siemens Healthcare (United States) (US)
ORCID: Panin, V.Y.
Michel, C.
Venue: IEEE Transactions on Medical Imaging
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Published: 2006-07
Volume: 25
Issue: 7
Pages: 907-921
ISSN: 0278-0062 (ISSN-L)
DOI: 10.1109/tmi.2006.876171
OpenAlex: W2169683146
Cited by: 536
References: 30
Citations by year: 2026: 6 · 2025: 8 · 2024: 16 · 2023: 16 · 2022: 17 · 2021: 23 · 2020: 35 · 2019: 23 · 2018: 26 · 2017: 31 · 2016: 33 · 2015: 33 · 2014: 48 · 2013: 39 · 2012: 45
FWCI: 16.79
Type: journal article
Language: en
Open access: closed
Licence: ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
Locations: IEEE Transactions on Medical Imaging (publishedVersion)
PubMed (publishedVersion)
Topics: Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
Physical Sciences › Engineering › Biomedical Engineering › Advanced X-ray and CT Imaging
Keywords: point source measurements, iterative reconstruction, axial compression, spatial resolution, noise characteristics
MeSH terms: Algorithms, Image Enhancement, Image Interpretation, Computer-Assisted, Sensitivity and Specificity, Signal Processing, Computer-Assisted, Reproducibility of Results, Phantoms, Imaging, Imaging, Three-Dimensional, Positron-Emission Tomography

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Fully 3-D PET reconstruction with system matrix derived from point source measurements

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