Cited by 536Medical Imaging Techniques and ApplicationsCardiac Imaging and DiagnosticsAdvanced X-ray and CT Imaging

The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.

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

Open this paper in CoChat — free account

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.

Integrity signals

Registry

Crossref · 10.1109/tmi.2006.876171

Cites

30 of 30 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

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
New, faster, image-based scatter correction for 3D PET
Watson, C. C. (2000) · IEEE Transactions on Nuclear Science · doi:10.1109/23.873020 · Cited by 520
An Improved Algorithm for Reprojecting Rays through Pixel Images
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
Self-citation

Flagged first, then by citations

Show all 30 references

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

Sorted by citations

Items 401–500 of 531

Optimization of reconstruction in quantitative brain PET images: Benefits from PSF modeling and correction of edge artifacts
Verrecchia‐Ramos, E., Ginet, M., Morel, O., Engels‐Deutsch, M., Mahmoud, S. B., & Retif, P. (2024) · Medical Physics · doi:10.1002/mp.17419 · Cited by 2
Von PET und PET/CT zur PET/MRT: Ein technologisches Update
Büther, F. (2018) · Der Nuklearmediziner · doi:10.1055/a-0621-3171 · Cited by 2
Advances in PET/CT Imaging
Iskra, I., Visvikis, D., Koole, M. J. B., Armstrong, I. S., Vanhove, C., Žagar, I., Middlebrooks, T., Bormans, G. M., Cleeren, F., Weehaeghe, D. V., et al. (2021) · doi:10.52717/pwze5872 · Cited by 3
[PET] 7. History of PET Image Reconstruction Methods
Tashima, H. (2024) · Japanese Journal of Radiological Technology · doi:10.6009/jjrt.2024-2353 · Cited by 2
An animal PET scanner using flat-panel position-sensitive PMTs
Okamoto, T., Ote, K., Sakai, K., Noda, A., Shimizu, K., Masuda, K., Ohmura, T., & Watanabe, M. (2013) · Annals of Nuclear Medicine · doi:10.1007/s12149-013-0772-y · Cited by 2
PET image reconstruction using ANN
Thiyagarajan, A., Rajasekaran, M. P., & Kannan, S. (2014) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22100 · Cited by 2
Fast iterative image reconstruction using sparse matrix factorization with GPU acceleration
Zhou, J., & Qi, J. (2011) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.878799 · Cited by 2
Detector response correction for 3D PET using Bayesian modeling of the location Of interaction
Sitek, A., & Andreyev, A. (2012) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2012.6551533 · Cited by 2
System response matrix denoising in measurement space in positron emission tomography
Cabello, J., & Rafecas, M. (2011) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2011.6153808 · Cited by 2
Recent Advances in Hybrid Imaging for Radiation Therapy Planning: The Cutting Edge
Zaidi, H., & Pan, T. (2011) · PET Clinics · doi:10.1016/j.cpet.2011.02.009 · Cited by 2
Pre-computed system matrix calculation based on a piece-wise method for PET
Ahmed, A. M., Kikuchi, Y., Matsuyama, S., Terakawa, A., Takyu, S., Sugai, H., & Ishii, K. (2014) · Radiological Physics and Technology · doi:10.1007/s12194-014-0293-y · Cited by 2
Effects of point spread function-based image reconstruction on neuroreceptor binding in positron emission tomography study with [11C]FLB 457
Thongpraparn, T., Ikoma, Y., Shiraishi, T., Yamaya, T., & Ito, H. (2015) · Radiological Physics and Technology · doi:10.1007/s12194-015-0343-0 · Cited by 2
Scan time reduction with advanced PET reconstruction: Preserving lesion detection performance
Kadrmas, D. J., Bradshaw, T., Casey, M. E., & Hamill, J. J. (2010) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2010.5874213 · Cited by 2
Self-citation
Estimation of detector response function for PET from point source measurements: Effect of point source configuration
Tohme, M. S., & Qi, J. (2007) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2007.4437093 · Cited by 2
Isotope dependent system matrices for high resolution PET imaging
Kotasidis, F. A., Angelis, G. I., Anton‐Rodriguez, J., Matthews, J. C., Reader, A. J., Green, M., & Zaidi, H. (2012) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2012.6551667 · Cited by 2
Spatially variant resolution modelling for iterative list-mode PET reconstruction
Bickell, M. G., Zhou, L., & Nuyts, J. (2013) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2013.6829233 · Cited by 2
Promising results on PSF correction applied in the reconstruction process of a small animal PET image
Orero, A., Correcher, C., González, A. J., Soriano, A., Carles, M., Moliner, L., Seimetz, M., Sánchez, F., & Benlloch, J. (2011) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2011.6152507 · Cited by 2
MRI guided PET image filtering and partial volume correction
Yan, J., Lim, J., & Townsend, D. W. (2013) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2013.6829058 · Cited by 2
Towards Radiotherapy Enhancement and Real Time Tumor Radiation Dosimetry Through 3D Imaging of Gold Nanoparticles Using XFCT
Vienne, C., Stolidi, A., Lemaire, H., Maier, D., Renaud, D., Grall, R., Chevillard, S., Brun, É., Sicard‐Roselli, C., & Limousin, O. O. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00928-1_46 · Cited by 2
A Monte Carlo detector response model for the IRIS PET preclinical scanner
Pilleri, A., Camarlinghi, N., Guerra, A. D., Sportelli, G., & Belcari, N. (2019) · Physica Medica · doi:10.1016/j.ejmp.2018.12.035 · Cited by 2
Application of the pseudoinverse for real-time 3D PET image reconstruction
López-Montes, A., Galve, P., Udías, J. M., & Herraiz, J. L. (2019) · International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D) · doi:10.1117/12.2534841 · Cited by 2
Super-resolution PET Brain Imaging using Deep Learning
Ren, S., Liu, J., Xie, H., Toyonaga, T., Mirian, N., Chen, M.-K., Aboian, M., Carson, R. E., & Liu, C. (2021) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nss/mic44867.2021.9875548 · Cited by 2
Effects of point spread function correction and time-of-flight on visual contrast level and pixel values in brain PET images
Kamikawa, Y., Yoshida, Y., & Kawahara, Y. (2023) · Nuclear Medicine Communications · doi:10.1097/mnm.0000000000001681 · Cited by 2
PET/CT for Interventional Use
Kijewski, M. F., Tempany, C. M., Golby, A. J., & Jolesz, F. A. (2013) · Springer eBooks · doi:10.1007/978-1-4614-7657-3_15 · Cited by 2
Theoretical analysis of resolution and noise properties of PET image reconstruction with and without sinogram blurring modeling
Ahn, S. (2014) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2014.7430760 · Cited by 2
Algorithms for Image Reconstruction
Hoeschen, C., Rafecas, M., & Aspelmeier, T. (2010) · Springer eBooks · doi:10.1007/978-3-642-11327-7_12 · Cited by 2
Performance and Methodological Aspects in Positron Emission Tomography
Teräs, M. (2008) · UTUPub (University of Turku) · Cited by 2
Time-of-flight in cardiac PET/TC: What do we know and what we should know?
Matheoud, R., & Lecchi, M. (2018) · Journal of Nuclear Cardiology · doi:10.1007/s12350-018-1336-2 · Cited by 2
Primary Central Nervous System Lymphoma: Lessons and Opportunities from 2 Decades of CT and PET/CT
Jara, H. J. (2019) · Radiology · doi:10.1148/radiol.2019191147 · Cited by 2
Evaluation of a motion correction algorithm in lung cancer PET/CT: Phantom validation and patient studies
Wang, Z., Liu, J., Lu, D., Sui, G., Wang, Y., Tong, L., Liu, X., Zhang, Y., Fu, J., Xu, W., et al. (2025) · Medical Physics · doi:10.1002/mp.17846 · Cited by 1
Dynamic PET Image Reconstruction Using Kalman Inspired Network
Chen, M., Ran, H., Wan, Y., Ran, A., Guo, M. Y., & Liu, H. (2025) · IEEE Transactions on Radiation and Plasma Medical Sciences · doi:10.1109/trpms.2025.3602938 · Cited by 1
Parallel Beam Approximation for Calculation of Detection Efficiency of Crystals in PET Detector Arrays
Komarov, S., Song, T. Y., Wu, H., & Tai, Y. (2011) · IEEE Transactions on Nuclear Science · doi:10.1109/tns.2011.2162962 · Cited by 1
Challenges of image generation for tight ring, long bore PET scanners
Wangerin, K. A., Qian, H., & Manjeshwar, R. M. (2011) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2011.6153872 · Cited by 1
Characterization of Maximum Likelihood Solutions to Image Reconstruction in Photon Emission Tomography
Chapeau‐Blondeau, F., & Jeanguillaume, C. (2013) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-013-0477-9 · Cited by 1
Iterative Reconstruction with Monte Carlo Based System Matrix for Dedicated Breast PET
Saha, K., Straus, K. J., & Glick, S. J. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-31271-7_21 · Cited by 1
La synchronisation respiratoire en TEP/TDM : vœu pieux ou réalité clinique ?
Daouk, J., Bailly, P., Pépin, A. P. A., & Meyer, M.-É. (2013) · Médecine Nucléaire · doi:10.1016/j.mednuc.2013.03.002 · Cited by 1
Experimental comparison of lesion detectability for four fully-3D PET reconstruction schemes
Kadrmas, D. J., Casey, M., Black, N. F., Hamill, J. J., Panin, V., & Conti, M. (2007) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2007.4436724 · Cited by 1
Self-citation
Investigation of image resolution effects in maximum-likelihood TOF PET reconstruction
Ispiryan, M. K., & Matej, S. (2012) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2012.6551607 · Cited by 1
Clinical NECR in 18F-FDG PET scans: Optimization of patient specific activity and variable acquisition time. Relationship with SNR
Carlier, T., Ferrer, L., Nécib, H., Bodet‐Milin, C., Rousseau, C., & Kraeber‐Bodéré, F. (2013) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2013.6829382 · Cited by 1
Chapter 4 Intraoperative 3D Nuclear Imaging and Its Hybrid Extensions
Wendler, T. (2016) · CRC Press eBooks · doi:10.1201/9781315370224-5 · Cited by 1
Image reconstruction for PET and SPECT
Leahy, R. M., Bai, B., & Asma, E. (2017) · doi:10.4324/9781315374383-22 · Cited by 1
Image accuracy and quality test in rate constant depending on reconstruction algorithms with and without incorporating PSF and TOF in PET imaging
Maeda, Y., Kudomi, N., Yamamoto, H., Yamamoto, Y., & Nishiyama, Y. (2015) · Annals of Nuclear Medicine · doi:10.1007/s12149-015-0979-1 · Cited by 1
Radioactive Source Localization Method for the Partially Coded Field-of-View of Coded-Aperture Imaging in Nuclear Security Applications
Liu, Q., Cheng, Y., Tuo, X., & Yang, Y. (2022) · Springer eBooks · doi:10.1007/978-3-030-92989-3_12 · Cited by 1
Feasibility of dose reduction for [18F]FDG-PET/MR imaging of patients with non-lesional epilepsy
Kertész, H., Traub‐Weidinger, T., Cal-González, J., Rausch, I., Muzik, O., Sundar, L. K. S., & Beyer, T. (2023) · Nuklearmedizin - NuclearMedicine · doi:10.1055/a-2015-7785 · Cited by 1
Stochastic model for enhanced PET image reconstruction
Matulić, T., & Seršić, D. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.106294 · Cited by 1
Free Software for PET Imaging
de la Prieta, R. (2012) · InTech eBooks · doi:10.5772/31882 · Cited by 1
State of the Art Hybrid Technology: PET/CT
Slomka, P. J., Berman, D. S., & Germano, G. (2013) · Current Cardiovascular Imaging Reports · doi:10.1007/s12410-013-9208-2 · Cited by 1
Quantification of Small-Animal Imaging Data
Zaidi, H. (2014) · Springer eBooks · doi:10.1007/978-1-4939-0894-3_17 · Cited by 1
SPATIAL AND ENERGY RESOLUTIONS OF A HEXAGONAL ANIMAL PET SCANNER BASED ON LGSO CRYSTAL AND FLAT-PANEL PMT
Lee, C.-M., Hong, S.-J., Yoon, H.-S., Ito, M., Kwon, S.-I., Park, S.-K., Lee, D.-S., Sim, K.-S., & Lee, J. (2012) · Nuclear Engineering and Technology · doi:10.5516/net.08.2010.059 · Cited by 1
Point-spread Function and Time-of-flight in PET Image Reconstruction
Akamatsu, G., 木寺, 大., 前畠, 彬., 光元, 勝., 筒井, 悠., 三輪, 建., & 佐々木, 雅. (2015) · Japanese Journal of Radiological Technology · doi:10.6009/jjrt.2015_jsrt_71.11.1115 · Cited by 1
Detector response modeling with asymmetric 2D Gaussian functions for GPU-based image reconstruction of the whole-body dual-ring OpenPET
Tashima, H., Yoshida, E., Shinaji, T., & Yamaya, T. (2014) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2014.7430806 · Cited by 1
Accuracy of Resolution Recovery in PSF-based Fully-3D PET Image Reconstruction: Simulation and Phantom Study in Multicenter Trial
Kangai, Y., Odajima, S., Matsutomo, N., Kamiya, T., Mizuta, T., & Onishi, H. (2016) · Japanese Journal of Radiological Technology · doi:10.6009/jjrt.2016_jsrt_72.3.209 · Cited by 1
Physikalisch-technische Grundlagen
Rausch, I., & Beyer, T. (2016) · Springer eBooks · doi:10.1007/978-3-662-48842-3_2 · Cited by 1
Model asymmetrical detector response function with a skew normal distribution function in PET
Jin, X., Miao, J., Ross, S. G., & Stearns, C. W. (2015) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2015.7582168 · Cited by 1
High-Resolution PET/CT Development
Wong, W., & Zhang, Y. (2017) · Springer eBooks · doi:10.1007/978-981-10-3349-0_5 · Cited by 1
Effect of drugs containing glucose on FDG-PET image quality
Okamoto, S., Toyonaga, T., Matsuzawa, K., Aizawa, M., Mouri, T., Suzuki, Y., Miyamoto, N., & Inubushi, M. (2019) · Annals of Nuclear Medicine · doi:10.1007/s12149-019-01394-1 · Cited by 1
High-fidelity calibration and characterization of a spectral computed tomography system
Gallegos, I. O., Dalton, G., Stohn, A., Koundinyan, S. P., Thompson, K., & Jimenez, E. S. (2019) · Hard X-Ray, Gamma-Ray, and Neutron Detector Physics · doi:10.1117/12.2533923 · Cited by 1
Improved PET quantification and harmonization by adaptive denoising
Namías, M., & Jeraj, R. (2020) · Biomedical Physics & Engineering Express · doi:10.1088/2057-1976/ab6996 · Cited by 1
Influence of Reconstruction FOV and Matrix Size on the Quantitative Accuracy of FDG-PET: Comparison between OSEM and Bayesian Penalized Likelihood
Mikami, S., Nakamura, F., Nakamura, A., & Torizuka, T. (2021) · Japanese Journal of Radiological Technology · doi:10.6009/jjrt.2021_jsrt_77.5.454 · Cited by 1
Post-Reconstruction PET Resolution Modelling by Synthesised Image Reconstruction
Vass, L., & Reader, A. J. (2021) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nss/mic44867.2021.9875478 · Cited by 1
High definition PET for cardiac imaging: Preliminary results
Meunier, L. L., Slomka, P. J., Fermin, J. S., Dey, D., Hayes, S. W., Friedman, J. D., Germano, G., & Berman, D. S. (2008) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2008.4774498 · Cited by 1
Understanding the impact of advanced PET reconstruction in cardiac PET: The devil is in the details
Armstrong, I. S. (2018) · Journal of Nuclear Cardiology · doi:10.1007/s12350-018-1329-1 · Cited by 1
Constant Infusion Radiotracer Administration for High Temporal Resolution Positron Emission Tomography (PET) of the Human Brain: Application to [18F]-Fluorodexoyglucose PET (FDG-PET)Preprint
Jamadar, S. D., Ward, P. G. D., Carey, A., McIntyre, R., Parkes, L., Sasan, D., Fallon, J., Li, S., Chen, Z., & Egan, G. F. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/667352 · Cited by 1
Partial volume correction of cardiac mouse positron emission tomography images
Dumouchel, T. (2012) · doi:10.22215/etd/2012-09506 · Cited by 1
Investigation of the benefit of PVC in high resolution PET as a post and within reconstruction method for FDG brain dataPreprint
Raptis, E., Parkes, L. M., Anton‐Rodriguez, J., Carter, S., Herholz, K., & Matthews, J. C. (2020) · Research Square · doi:10.21203/rs.3.rs-44351/v1 · Cited by 1
Quantitative Techniques for PET/CT: A Clinical Assessment of the Impact of PSF and TOF
Schaefferkoetter, J. D. (2013)
GPU-based particle transport for PET reconstruction
Magdics, M. (2014)
Fourierdomänen modengekoppelte Laser: Aufklärung der Funktionsweise und Erschließung neuer Anwendungsbereiche
Biedermann, B. R. (2010) · doi:10.5282/edoc.12226
Investigation of the Effects of Image Signal-to-Noise Ratio on TSPO PET Quantification of Neuroinflammation
Constable, C. (2013) · The Sydney eScholarship Repository (The University of Sydney)
From PET to PET/CT
Mawlawi, O. R., Wendt, R. E., & Wong, W. H. (2012) · Springer eBooks · doi:10.1007/978-1-4419-0802-5_3
Implementation and evaluation of a fully 3D OS–MLEM reconstruction algorithm accounting for the PSF of the PET imaging system
Rapisarda, E., Bettinardi, V., Thielemans, K., & Gilardi, M. C. (2009) · Nuclear Physics B - Proceedings Supplements · doi:10.1016/j.nuclphysbps.2009.10.064
Preliminary clinical applications of a device-dedicated whole-body positron emission tomography reconstruction method: impact on standardized uptake values
Daouk, J., Bailly, P., Fin, L., & Meyer, M.-É. (2010) · Nuclear Medicine Communications · doi:10.1097/mnm.0b013e32833d691a
A hardware projector/backprojector pair for 3D PET reconstruction
Nicolas Gac, A., Mancini, S., Desvignes, M., de Boissieu, F., & Reilhac, A. (2008) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.770588
A fully 3D OS-MLEM reconstruction algorithm accounting for the point spread function of a PET system
Rapisarda, E., Bettinardi, V., Thielemans, K., & Gilardi, M. C. (2011) · Nuclear Physics B - Proceedings Supplements · doi:10.1016/j.nuclphysbps.2011.03.128
Dopamine D2-receptor Mapping in Restless Legs Syndrome and Human Behaviour
Červenka, S. (2008) · Figshare
A feasible method to correct system matrix for microPET image reconstruction using artificial neural network
Su, K., Wu, L.-C., Lee, J.-S., Liu, R.-S., Wang, S.-J., & Chen, J.-C. (2007) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2007.4436721
Imaging Studies for Evaluating Impact of Position Sampling Techniques in PET Scanners
Surti, S., Werner, M. E., & Karp, J. S. (2010) · IEEE Transactions on Nuclear Science · doi:10.1109/tns.2010.2049121
Improving resolution for the Siemens 3T MR-BrainPET
Botelho, M. R. D. S. (2015) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)
Clinical PET Technology
Asseler, Y. D., & de Wiele, C. V. (2012) · WORLD SCIENTIFIC eBooks · doi:10.1142/9789814317740_0011
Symposium 1: The Future of the Molecular Imaging in Japan
Kawamitsu, H., Senda, M., 西村, 伸., 西田, 広., & 堀次, 元. (2014) · Japanese Journal of Radiological Technology · doi:10.6009/jjrt.2014_jsrt_70.1.73
Property and Problems of Image Reconstruction Methods in PET and PET/CT
Onishi, H., Kitamura, K., Yamaya, T., Sakaguchi, K., & Hishinuma, M. (2011) · Japanese Journal of Radiological Technology · doi:10.6009/jjrt.67.805
Fast single scan derivation of the PSF resolution model on the TruePoint PET/CT using a printed point source array
Kotasidis, F. A., Matthews, J. C., Angelis, G. I., Noonan, P. J., Markiewicz, P. J., Lionheart, W. R. B., & Reader, A. J. (2010) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2010.5874471
Modified ordered subsets scheme for attenuation weighted reconstruction
Rothfuß, H., Panin, V., & Gregor, J. (2009) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2009.5401959
Self-citation
Technique to distinguish signal from statistical noise in PET imaging
Hamill, J. J., & Conti, M. (2009) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2009.5401859
A sinogram resolution modelling adapted to the geometry of the HRRT
Mendes, L. G. A., Comtat, C., & Ferreira, N. C. (2012) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2012.6551762
Effect of various image reconstruction parameters on pet lesion detection performance
Morey, A.-J. (2018) · J. Willard Marriott Library · doi:10.26053/0h-tte5-hfg0
Investigation of Reconstruction Algorithms by Means of Quantitative PET/CT Phantom Studies with a Focus on Evaluation Strategies A PET/CT Phantom Study
Neuwirth, J., Layer, T., Blaickner, M., Birkfellner, W., & Staudenherz, A. (2015) · International Journal of Life Science and Medical Research · doi:10.5963/lsmr0502001
PET/MR imaging of hypoxic atherosclerotic plaque using 64Cu-ATSM
Nie, X. (2017) · Open Scholarship Institutional Repository (Washington University in St. Louis) · doi:10.7936/k7m9072q
Composite system modelling for high accuracy brain PET image reconstruction using GATE
Belzunce, M. A., & Reader, A. J. (2016) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2016.8069558
A Subband-Specific Deconvolution Model for MTF Improvement in CT
Han, S., Choi, K., & Yoo, S. W. (2017) · Journal of Healthcare Engineering · doi:10.1155/2017/2193635
Time-Domain Signal Processing
Prinzie, J., Steyaert, M. S. J., & Leroux, P. (2018) · Analog circuits and signal processing/Analog circuits and signal processing series · doi:10.1007/978-3-319-78616-2_2
Emission Tomography and Image Reconstruction
Khalil, M. M. (2010) · Springer eBooks · doi:10.1007/978-3-540-85962-8_13
Differences in edge artifacts between 68Ga- and 18F-PET images reconstructed using point spread function correction
Amakusa, S., Matsuoka, K., Baba, S., Yoshida, T., & Sasaki, M. (2019) · Nuclear Medicine Communications · doi:10.1097/mnm.0000000000001079
8. Clinical Application 6: Analytical Reconstruction Algorithm of SPECT and PET
Matsumoto, K. (2014) · Japanese Journal of Radiological Technology · doi:10.6009/jjrt.2014_jsrt_70.12.1496
Positron Emission Tomography (PET): Characteristics and Performance
Khalil, M. M. (2021) · Springer eBooks · doi:10.1007/978-3-030-65245-6_13
Quantitative evaluation of single-photon emission computed tomography findings in lower extremity possible without computed tomography-based attenuation correction
Tsuchitani, T., Kitajima, K., Takahashi, Y., & Kotoura, N. (2021) · Nuclear Medicine Communications · doi:10.1097/mnm.0000000000001440
EMISTA-Based Quantitative PET Reconstruction
Zhao, L., & Liu, H. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-87358-5_56
Comparison of PSF and Non PSF BLOB based reconstructed image in Time-of-Flight PET/CT
Vishwakarma, M. K. (2021) · International Journal of Pharmaceutical and Bio-Medical Science · doi:10.47191/ijpbms/v1-i8-03
Image Reconstruction
Comtat, C. (2021) · Springer eBooks · doi:10.1007/978-3-319-93785-4_39
Emission Tomography and Image Reconstruction
Khalil, M. M. (2021) · Springer eBooks · doi:10.1007/978-3-030-65245-6_16

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

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

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

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks