Cited by 4,429Medical Imaging Techniques and ApplicationsNumerical methods in inverse problemsImage and Signal Denoising Methods

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Maximum Likelihood Reconstruction for Emission Tomography

Shepp, L. A., Vardi, Y.·1982·IEEE Transactions on Medical Imaging

DOI 10.1109/tmi.1982.4307558

Open this paper in CoChat — free account

Abstract

Previous models for emission tomography (ET) do not distinguish the physics of ET from that of transmission tomography. We give a more accurate general mathematical model for ET where an unknown emission density lambda = lambda(x, y, z) generates, and is to be reconstructed from, the number of counts n(*)(d) in each of D detector units d. Within the model, we give an algorithm for determining an estimate lambdainsertion mark of lambda which maximizes the probability p(n(*)|lambda) of observing the actual detector count data n(*) over all possible densities lambda. Let independent Poisson variables n(b) with unknown means lambda(b), b = 1, ..., B represent the number of unobserved emissions in each of B boxes (pixels) partitioning an object containing an emitter. Suppose each emission in box b is detected in detector unit d with probability p(b, d), d = 1, ..., D with p(b,d) a one-step transition matrix, assumed known. We observe the total number n(*) = n(*)(d) of emissions in each detector unit d and want to estimate the unknown lambda = lambda(b), b = 1, ..., B. For each lambda, the observed data n(*) has probability or likelihood p(n(*)|lambda). The EM algorithm of mathematical statistics starts with an initial estimate lambda(0) and gives the following simple iterative procedure for obtaining a new estimate lambdainsertion mark(new), from an old estimate lambdainsertion mark(old), to obtain lambdainsertion mark(k), k = 1, 2, ..., lambdainsertion mark(new)(b)= lambdainsertion mark(old)(b)Sum of (n(*)p(b,d) from d=1 to D/Sum of lambdainsertion mark()old(b('))p(b('),d) from b(')=1 to B), b=1,...B.

Integrity signals

Registry

Crossref · 10.1109/tmi.1982.4307558

Cites

9 of 9 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?

Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
The Fourier reconstruction of a head section
Shepp, L. A., & Logan, B. F. (1974) · IEEE Transactions on Nuclear Science · doi:10.1109/tns.1974.6499235 · Cited by 2,202
Self-citation
Nonlinear Programming.
Veinott, A. F., & Abadie, J. (1968) · Journal of the American Statistical Association · doi:10.2307/2283909 · Cited by 383
A Matheematical Model for Positron-Emission Tomography Systems Having Time-of-Flight Measurements
Snyder, D. L., Thomas, L. J., & Ter‐Pogossian, M. M. (1981) · IEEE Transactions on Nuclear Science · doi:10.1109/tns.1981.4332168 · Cited by 222
Emission Computer Assisted Tomography with Single-Photon and Positron Annihilation Photon Emitters
Budinger, T. F., Derenzo, S. E., Gullberg, G. T., Greenberg, W. L., & Huesman, R. H. (1977) · Journal of Computer Assisted Tomography · doi:10.1097/00004728-197701000-00015 · Cited by 200
Positron-Emission Tomography
Ter‐Pogossian, M. M., Raichle, M. E., & Sobel, B. E. (1980) · Scientific American · doi:10.1038/scientificamerican1080-170 · Cited by 173
Relaxation methods for image reconstruction
Herman, G. T., Lent, A. H., & Lutz, P. H. (1978) · Communications of the ACM · doi:10.1145/359340.359351 · Cited by 137
Circular Ring Transverse Axial Positron Camera for 3-Dimensional Reconstruction of Radionuclides Distribution
Cho, Z. H., Chan, J., & Eriksson, L. (1976) · IEEE Transactions on Nuclear Science · doi:10.1109/tns.1976.4328315 · Cited by 91
Nonparametric Estimation in Renewal Processes
Vardi, Y. (1982) · The Annals of Statistics · doi:10.1214/aos/1176345870 · Cited by 70
Self-citation

Show all 9 references

Research works printed but not linked: 1

lakshminarayanan, 1975, Reconstruction from divergent ray data

Sorted by citations

Learning the parts of objects by non-negative matrix factorization
Lee, D. D., & Seung, H. S. (1999) · Nature · doi:10.1038/44565 · Cited by 14,137
Unified segmentation
Ashburner, J., & Friston, K. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.02.018 · Cited by 7,507
ALGORITHMS FOR NON-NEGATIVE MATRIX FACTORIZATION
Lee, D. D., & Seung, H. S. (2000) · Cited by 7,972
On the Statistical Analysis of Dirty Pictures
Besag, J. E. (1986) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1986.tb01412.x · Cited by 4,204
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
The expectation-maximization algorithm
Moon, T. K. (1996) · IEEE Signal Processing Magazine · doi:10.1109/79.543975 · Cited by 3,197
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
A Catalog of 1.4 GHz Radio Sources from the FIRST Survey
White, R. L., Becker, R. H., Helfand, D. J., & Gregg, M. D. (1997) · The Astrophysical Journal · doi:10.1086/303564 · Cited by 1,135
Space-alternating generalized expectation-maximization algorithm
Fessler, J. A., & Hero, A. O. (1994) · IEEE Transactions on Signal Processing · doi:10.1109/78.324732 · Cited by 1,063
A three‐dimensional statistical approach to improved image quality for multislice helical CT
Thibault, J., Sauer, K. D., Bouman, C. A., & Hsieh, J. (2007) · Medical Physics · doi:10.1118/1.2789499 · Cited by 936
A Statistical Model for Positron Emission Tomography
Vardi, Y., Shepp, L. A., & Kaufman, L. (1985) · Journal of the American Statistical Association · doi:10.1080/01621459.1985.10477119 · Cited by 863
Self-citation
Network Tomography: Estimating Source-Destination Traffic Intensities from Link Data
Vardi, Y. (1996) · Journal of the American Statistical Association · doi:10.1080/01621459.1996.10476697 · Cited by 795
Self-citation
Iterative reconstruction methods in X-ray CT
Beister, M., Kolditz, D., & Kalender, W. A. (2012) · Physica Medica · doi:10.1016/j.ejmp.2012.01.003 · Cited by 754
Computational anatomy: an emerging discipline
Grenander, U., & Miller, M. I. (1998) · Quarterly of Applied Mathematics · doi:10.1090/qam/1668732 · Cited by 619
A generalized EM algorithm for 3-D Bayesian reconstruction from Poisson data using Gibbs priors
Hebert, T. J., & Leahy, R. M. (1989) · IEEE Transactions on Medical Imaging · doi:10.1109/42.24868 · Cited by 622
Penalized weighted least-squares image reconstruction for positron emission tomography
Fessler, J. A. (1994) · IEEE Transactions on Medical Imaging · doi:10.1109/42.293921 · Cited by 611
Single photon-emission computed tomography
Holly, T. A., Abbott, B., Al-Mallah, M. H., Calnon, D. A., Cohen, M. C., DiFilippo, F. P., Ficaro, E. P., Freeman, M. R., Hendel, R. C., Jain, D., et al. (2010) · Journal of Nuclear Cardiology · doi:10.1007/s12350-010-9246-y · Cited by 603
Synchrotron X-ray Analytical Techniques for Studying Materials Electrochemistry in Rechargeable Batteries
Lin, F., Liu, Y., Yu, X., Cheng, L., Singer, A., Shpyrko, O., Xin, H. L., Tamura, N., Tian, C., Weng, T., et al. (2017) · Chemical Reviews · doi:10.1021/acs.chemrev.7b00007 · Cited by 587
The EM Algorithm—an Old Folk-song Sung to a Fast New Tune
Meng, X.-L., & Van Dyk, D. (1997) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00082 · Cited by 802
Utility of Positron Emission Tomography for the Staging of Patients With Potentially Operable Esophageal Carcinoma
Flamen, P., Lerut, A., Cutsem, E. V., Wever, W. D., Peeters, M., Stroobants, S. G., Dupont, P. J., Bormans, G. M., Hiele, M. I., Leyn, P. D., et al. (2000) · Journal of Clinical Oncology · doi:10.1200/jco.2000.18.18.3202 · Cited by 568
Dietary Fats and the Risk of Incident Alzheimer Disease
Morris, M. C., Evans, D. A., Bienias, J. L., Tangney, C., Bennett, D. A., Aggarwal, N. T., Schneider, J. S., & Wilson, R. S. (2003) · Archives of Neurology · doi:10.1001/archneur.60.2.194 · Cited by 543
18FDG-Positron emission tomography for the early prediction of response in advanced soft tissue sarcoma treated with imatinib mesylate (Glivec®)
Stroobants, S. G., Goeminne, J.-C., Seegers, M., Dimitrijević, S., Dupont, P. J., Nuyts, J. L., Martens, M., van den Borne, B., Cole, P., Sciot, R., et al. (2003) · European Journal of Cancer · doi:10.1016/s0959-8049(03)00073-x · Cited by 520
Technical aspects of dental CBCT: state of the art
Pauwels, R., Araki, K., Siewerdsen, J. H., & Thongvigitmanee, S. S. (2014) · Dentomaxillofacial Radiology · doi:10.1259/dmfr.20140224 · Cited by 513
Blind deconvolution by means of the Richardson–Lucy algorithm
Fish, D. A., Walker, J. G., Brinicombe, A. M., & Pike, E. R. (1995) · Journal of the Optical Society of America A · doi:10.1364/josaa.12.000058 · Cited by 511
Joint estimation of object and aberrations by using phase diversity
Paxman, R. G., Schulz, T. J., & Fienup, J. R. (1992) · Journal of the Optical Society of America A · doi:10.1364/josaa.9.001072 · Cited by 506
Algebraic reconstruction techniques can be made computationally efficient (positron emission tomography application)
Herman, G. T., & Meyer, L. B. (1993) · IEEE Transactions on Medical Imaging · doi:10.1109/42.241889 · Cited by 485
A modified expectation maximization algorithm for penalized likelihood estimation in emission tomography
Pierro, A. R. D. (1995) · IEEE Transactions on Medical Imaging · doi:10.1109/42.370409 · Cited by 477
Image Processing and Data Analysis, The Multiscale Approach
Seymour, L., Starck, J., Murtagh, F. D., & Bijaoui, A. (1999) · Journal of the American Statistical Association · doi:10.2307/2669962 · Cited by 468
STIR: software for tomographic image reconstruction release 2
Thielemans, K., Tsoumpas, C., Mustafovic, S., Beisel, T., Aguiar, P., Δικαίος, Ν., & Jacobson, M. W. (2012) · Physics in Medicine and Biology · doi:10.1088/0031-9155/57/4/867 · Cited by 467
Tomographic bioluminescence imaging by use of a combined optical-PET (OPET) system: a computer simulation feasibility study
Alexandrakis, G., Rannou, F. R., & Chatziioannou, A. F. (2005) · Physics in Medicine and Biology · doi:10.1088/0031-9155/50/17/021 · Cited by 466
Prognostic Value of Positron Emission Tomography (PET) With Fluorine-18 Fluorodeoxyglucose ([18F]FDG) After First-Line Chemotherapy in Non-Hodgkin’s Lymphoma: Is [18F]FDG-PET a Valid Alternative to Conventional Diagnostic Methods?
Spaepen, K., Stroobants, S. G., Dupont, P. J., Steenweghen, S. V., Thomas, J., Vandenberghe, P., Vanuytsel, L., Bormans, G. M., Balzarini, J. M., Wolf‐Peeters, C. D., et al. (2001) · Journal of Clinical Oncology · doi:10.1200/jco.2001.19.2.414 · Cited by 465
Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation
Zhang, Y., Dong, Z., Wang‎, S., Yu, X., Yao, X., Zhou, Q., Hu, H., Li, M., Jiménez-Mesa, C., Ramı́rez, J., et al. (2020) · Information Fusion · doi:10.1016/j.inffus.2020.07.006 · Cited by 461
A Maximum a Posteriori Probability Expectation Maximization Algorithm for Image Reconstruction in Emission Tomography
Levitan, E., & Herman, G. T. (1987) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.1987.4307826 · Cited by 445
A unified approach to statistical tomography using coordinate descent optimization
Bouman, C. A., & Sauer, K. D. (1996) · IEEE Transactions on Image Processing · doi:10.1109/83.491321 · Cited by 442
Abdominal CT: Comparison of Adaptive Statistical Iterative and Filtered Back Projection Reconstruction Techniques
Singh, S., Kalra, M. K., Hsieh, J., Licato, P. E., Do, S., Pien, H. H., & Blake, M. A. (2010) · Radiology · doi:10.1148/radiol.10092212 · Cited by 435
Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile
Mena, G. E., Martinez, P. P., Mahmud, A. S., Marquet, P. A., Buckee, C. O., & Santillana, M. (2021) · Science · doi:10.1126/science.abg5298 · Cited by 431
Parameter expansion to accelerate EM: the PX-EM algorithm
Liu, C. (1998) · Biometrika · doi:10.1093/biomet/85.4.755 · Cited by 433
Deconvolution in Astronomy: A Review
Starck, J., Pantin, E., & Murtagh, F. D. (2002) · Publications of the Astronomical Society of the Pacific · doi:10.1086/342606 · Cited by 423
A row-action alternative to the EM algorithm for maximizing likelihood in emission tomography
Browne, J. A., & Pierrò, A. (1996) · IEEE Transactions on Medical Imaging · doi:10.1109/42.538946 · Cited by 424
Noise and Edge Artifacts in Maximum-Likelihood Reconstructions for Emission Tomography
Snyder, D. L., Miller, M. I., Thomas, L. J., & Politte, D. G. (1987) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.1987.4307831 · Cited by 421
MIRD Pamphlet No. 23: Quantitative SPECT for Patient-Specific 3-Dimensional Dosimetry in Internal Radionuclide Therapy
Dewaraja, Y. K., Frey, E. C., Sgouros, G., Brill, A. B., Roberson, P. L., ZANZONICO, P. B., & Ljungberg, M. H. (2012) · Journal of Nuclear Medicine · doi:10.2967/jnumed.111.100123 · Cited by 419
On Use of the Em Algorithm for Penalized Likelihood Estimation
Green, P. J. (1990) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1990.tb01798.x · Cited by 417
Iterative reconstruction techniques in emission computed tomography
Qi, J., & Leahy, R. M. (2006) · Physics in Medicine and Biology · doi:10.1088/0031-9155/51/15/r01 · Cited by 415
Early restaging positron emission tomography with 18F-fluorodeoxyglucose predicts outcome in patients with aggressive non-Hodgkin’s lymphoma
Spaepen, K., Stroobants, S., Dupont, P., Vandenberghe, P., Thomas, J., de Groot, T., Balzarini, J., De Wolf-Peeters, C., Mortelmans, L., & Verhoef, G. (2002) · Annals of Oncology · doi:10.1093/annonc/mdf256 · Cited by 410
Convergence of EM image reconstruction algorithms with Gibbs smoothing
Lange, K. L. (1990) · IEEE Transactions on Medical Imaging · doi:10.1109/42.61759 · Cited by 400
Mapping the three-dimensional density of the Galactic bulge with VVV red clump stars
Wegg, C., & Gerhard, O. (2013) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stt1376 · Cited by 399
Radiation dose reduction in computed tomography: techniques and future perspective
Yu, L., Liu, X., Leng, S., Kofler, J. M., Ramírez-Giraldo, J. C., Qu, M., Christner, J. A., Fletcher, J. G., & McCollough, C. H. (2009) · Imaging in Medicine · doi:10.2217/iim.09.5 · Cited by 396
Noise properties of the EM algorithm. I. Theory
Barrett, H. H., Wilson, D. W., & Tsui, B. M. W. (1994) · Physics in Medicine and Biology · doi:10.1088/0031-9155/39/5/004 · Cited by 391
Positron Emission Tomography: Current Challenges and Opportunities for Technological Advances in Clinical and Preclinical Imaging Systems
Vaquero, J. J., & Kinahan, P. E. (2015) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-071114-040723 · Cited by 384
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
MIRD Pamphlet No. 26: Joint EANM/MIRD Guidelines for Quantitative 177 Lu SPECT Applied for Dosimetry of Radiopharmaceutical Therapy
Ljungberg, M. H., Celler, A. M., Konijnenberg, M., Eckerman, K. F., Dewaraja, Y. K., & Gleisner, K. S. (2015) · Journal of Nuclear Medicine · doi:10.2967/jnumed.115.159012 · Cited by 375
Evaluation of sparse-view reconstruction from flat-panel-detector cone-beam CT
Bian, J., Siewerdsen, J. H., Han, X., Sidky, E. Y., Prince, J. L., Pelizzari, C. A., & Pan, X. (2010) · Physics in Medicine and Biology · doi:10.1088/0031-9155/55/22/001 · Cited by 375
Simultaneous maximum a posteriori reconstruction of attenuation and activity distributions from emission sinograms
Nuyts, J. L., Dupont, P. J., Stroobants, S. G., Benninck, R., Mortelmans, L., & Suetens, P. (1999) · IEEE Transactions on Medical Imaging · doi:10.1109/42.774167 · Cited by 361
Resolution modeling in PET imaging: Theory, practice, benefits, and pitfalls
Rahmim, A., Qi, J., & Sossi, V. (2013) · Medical Physics · doi:10.1118/1.4800806 · Cited by 371
Decreased mechanical stiffness in LMNA−/− cells is caused by defective nucleo-cytoskeletal integrity: implications for the development of laminopathies
Broers, J. L. V., Peeters, E. A. G., Kuijpers, H. J. H., Endert, J., Bouten, C. V. C., Oomens, C. W. J., Baaijens, F. F., & Ramaekers, F. C. S. (2004) · Human Molecular Genetics · doi:10.1093/hmg/ddh295 · Cited by 374
List-mode likelihood: EM algorithm and image quality estimation demonstrated on 2-D PET
Parra, L. C., & Barrett, H. H. (1998) · IEEE Transactions on Medical Imaging · doi:10.1109/42.700734 · Cited by 357
Determination of the attenuation map in emission tomography.
Zaidi, H., & Hasegawa, B. H. (2003) · PubMed · Cited by 350
Globally convergent image reconstruction for emission tomography using relaxed ordered subsets algorithms
Ahn, S., & Fessler, J. A. (2003) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2003.812251 · Cited by 345
Handbook of Mathematical Methods in Imaging
Lassas, M. J., Salo, M., & Uhlmann, G. A. (2010) · Springer eBooks · doi:10.1007/978-0-387-92920-0 · Cited by 360
Deblurring Poissonian images by split Bregman techniques
Setzer, S., Steidl, G., & Teuber, T. (2009) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2009.10.006 · Cited by 336
A Theoretical Study of Some Maximum Likelihood Algorithms for Emission and Transmission Tomography
Lange, K. L., Bahn, M. M., & Little, R. J. A. (1987) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.1987.4307810 · Cited by 330
Analytic and iterative reconstruction algorithms in SPECT.
Bruyant, P. P. (2002) · PubMed · Cited by 319
Image recovery from data acquired with a charge-coupled-device camera
Snyder, D. L., White, R. L., & Hammoud, A. M. (1993) · Journal of the Optical Society of America A · doi:10.1364/josaa.10.001014 · Cited by 318
Practical considerations for 3-D image reconstruction using spherically symmetric volume elements
Matej, S., & Lewitt, R. M. (1996) · IEEE Transactions on Medical Imaging · doi:10.1109/42.481442 · Cited by 315
Globally convergent algorithms for maximum a posteriori transmission tomography
Lange, K. L., & Fessler, J. A. (1995) · IEEE Transactions on Image Processing · doi:10.1109/83.465107 · Cited by 313
Image deblurring with Poisson data: from cells to galaxies
Bertero, M., Boccacci, P., Desiderà, G., & Vicidomini, G. (2009) · Inverse Problems · doi:10.1088/0266-5611/25/12/123006 · Cited by 308
History and future technical innovation in positron emission tomography
Jones, T., & Townsend, D. W. (2017) · Journal of medical imaging · doi:10.1117/1.jmi.4.1.011013 · Cited by 324
Tomographic mammography using a limited number of low‐dose cone‐beam projection images
Wu, T., Stewart, A. X., Stanton, M. J., McCauley, T. G., Phillips, W., Kopans, D. B., Moore, R. H., Eberhard, J. W., Opsahl‐Ong, B., Niklason, L. T., et al. (2003) · Medical Physics · doi:10.1118/1.1543934 · Cited by 301
EANM Dosimetry Committee guidelines for bone marrow and whole-body dosimetry
Hindorf, C., Glatting, G., Chiesa, C., Lindén, O., & Flux, G. (2010) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-010-1422-4 · Cited by 300
High-resolution SPECT using multipinhole collimation
Schramm, N. U., Ebel, G., Engeland, U., Schurrat, T., Béhé, M. P., & Behr, T. M. (2003) · IEEE Transactions on Nuclear Science · doi:10.1109/tns.2003.812437 · Cited by 298
Multiframe blind deconvolution of astronomical images
Schulz, T. J. (1993) · Journal of the Optical Society of America A · doi:10.1364/josaa.10.001064 · Cited by 293
Implementing and Accelerating the EM Algorithm for Positron Emission Tomography
Kaufman, L. (1987) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.1987.4307796 · Cited by 293
Iterative reconstruction for helical CT: a simulation study
Nuyts, J. L., Man, B. D., Dupont, P. J., Defrise, M., Suetens, P., & Mortelmans, L. (1998) · Physics in Medicine and Biology · doi:10.1088/0031-9155/43/4/003 · Cited by 291
Fast Model-Based X-Ray CT Reconstruction Using Spatially Nonhomogeneous ICD Optimization
Zhou, Y., Thibault, J., Bouman, C. A., Sauer, K. D., & Hsieh, J. (2010) · IEEE Transactions on Image Processing · doi:10.1109/tip.2010.2058811 · Cited by 291
Metabolic imaging of untreated prostate cancer by positron emission tomography with 18fluorine-labeled deoxyglucose.
Effert, P. J., Bares, R., Handt, S., Wolff, J. M., Büll, U., & Jakse, G. (1996) · PubMed · Cited by 289
Richardson-Lucy Deblurring for Scenes under a Projective Motion Path
Tai, Y., Tan, P., & Brown, M. S. (2010) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.222 · Cited by 288
Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms
Tang, J., Nett, B. E., & Chen, G. (2009) · Physics in Medicine and Biology · doi:10.1088/0031-9155/54/19/008 · Cited by 282
Fast gradient-based methods for Bayesian reconstruction of transmission and emission PET images
Mumcuoglu, E. U., Leahy, R. M., Cherry, S. R., & Zhou, Z. (1994) · IEEE Transactions on Medical Imaging · doi:10.1109/42.363099 · Cited by 282
Platelets: a multiscale approach for recovering edges and surfaces in photon-limited medical imaging
Willett, R. M., & Nowak, R. D. (2003) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2003.809622 · Cited by 279
TXM-Wizard : a program for advanced data collection and evaluation in full-field transmission X-ray microscopy
Liu, Y., Meirer, F., Williams, P. A., Wang, J., Andrews, J. C., & Pianetta, P. (2012) · Journal of Synchrotron Radiation · doi:10.1107/s0909049511049144 · Cited by 278
The Use of Sieves to Stabilize Images Produced with the EM Algorithm for Emission Tomography
Snyder, D. L., & Miller, M. I. (1985) · IEEE Transactions on Nuclear Science · doi:10.1109/tns.1985.4334521 · Cited by 278
Impact of Time-of-Flight on PET Tumor Detection
Kadrmas, D. J., Casey, M. E., Conti, M., Jakoby, B. W., Lois, C., & Townsend, D. W. (2009) · Journal of Nuclear Medicine · doi:10.2967/jnumed.109.063016 · Cited by 277
State of the art and challenges of time-of-flight PET
Conti, M. (2008) · Physica Medica · doi:10.1016/j.ejmp.2008.10.001 · Cited by 275
On Tensors, Sparsity, and Nonnegative Factorizations
Chi, E. C., & Kolda, T. G. (2012) · SIAM Journal on Matrix Analysis and Applications · doi:10.1137/110859063 · Cited by 274
Snapshot hyperspectral imaging in ophthalmology
Johnson, W. R., Wilson, D. W., Fink, W., Humayun, M. S., & Bearman, G. (2007) · Journal of Biomedical Optics · doi:10.1117/1.2434950 · Cited by 274
A Smoothed Em Approach to Indirect Estimation Problems, with Particular Reference to Stereology and Emission Tomography
Silverman, B. W., Jones, M. C., Wilson, J. D., & Nychka, D. W. (1990) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1990.tb01788.x · Cited by 274
Design of a motion-compensation OSEM list-mode algorithm for resolution-recovery reconstruction for the HRRT
Carson, R. E., Barker, W. C., Liow, J., & Johnson, C. A. (2004) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2003.1352597 · Cited by 269
Proximal minimization algorithm withD-functions
Censor, Y., & Zenios, S. A. (1992) · Journal of Optimization Theory and Applications · doi:10.1007/bf00940051 · Cited by 268
Histopathologic Validation of Lymph Node Staging With FDG-PET Scan in Cancer of the Esophagus and Gastroesophageal Junction
Lerut, A., Flamen, P., Ectors, N., Cutsem, E. V., Peeters, M., Hiele, M. I., Wever, W. D., Coosemans, W., Decker, G. A., Leyn, P. D., et al. (2000) · Annals of Surgery · doi:10.1097/00000658-200012000-00003 · Cited by 263
Simultaneous Reconstruction of Activity and Attenuation in Time-of-Flight PET
Rezaei, A., Defrise, M., Bal, G., Michel, C. J., Conti, M., Watson, C. C., & Nuyts, J. L. (2012) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2012.2212719 · Cited by 263
Computed-tomography imaging spectrometer: experimental calibration and reconstruction results
Descour, M. R., & Dereniak, E. L. (1995) · Applied Optics · doi:10.1364/ao.34.004817 · Cited by 262
Megavoltage CT on a tomotherapy system
Ruchala, K., Olivera, G., Schloesser, E. A., & Mackie, T. (1999) · Physics in Medicine and Biology · doi:10.1088/0031-9155/44/10/316 · Cited by 261
Direct reconstruction of kinetic parameter images from dynamic PET data
Kamaşak, M. E., Bouman, C. A., Morris, E. D., & Sauer, K. D. (2005) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2005.845317 · Cited by 255
Review of Terahertz Tomography Techniques
Guillet, J.-P., Recur, B., Frederique, L., Bousquet, B., Canioni, L., Manek-Hönninger, I. B., Desbarats, P., & Mounaix, P. (2014) · Journal of Infrared Millimeter and Terahertz Waves · doi:10.1007/s10762-014-0057-0 · Cited by 254
Stopping Rule for the MLE Algorithm Based on Statistical Hypothesis Testing
Veklerov, E., & Llacer, J. (1987) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.1987.4307849 · Cited by 254
A scaled gradient projection method for constrained image deblurring
Bonettini, S., Zanella, R., & Zanni, L. (2008) · Inverse Problems · doi:10.1088/0266-5611/25/1/015002 · Cited by 253
Quantitative Accuracy of Clinical 99mTc SPECT/CT Using Ordered-Subset Expectation Maximization with 3-Dimensional Resolution Recovery, Attenuation, and Scatter Correction
Zeintl, J., Vija, A. H., Yahil, A., Joachim Hornegger, A., & Kuwert, T. (2010) · Journal of Nuclear Medicine · doi:10.2967/jnumed.109.071571 · Cited by 252
Accelerating popular tomographic reconstruction algorithms on commodity PC graphics hardware
Xu, F., & Mueller, K. D. (2005) · IEEE Transactions on Nuclear Science · doi:10.1109/tns.2005.851398 · Cited by 252
Efficient Bayesian-based multiview deconvolution
Preibisch, S., Amat, F., Stamataki, E., Sarov, M., Singer, R. H., Myers, E. W., & Tomančák, P. (2014) · Nature Methods · doi:10.1038/nmeth.2929 · Cited by 250
From Image Deblurring to Optimal Investments: Maximum Likelihood Solutions for Positive Linear Inverse Problems
Vardi, Y., & Lee, D. (1993) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1993.tb01925.x · Cited by 249
Self-citation

Authors: Shepp, L. A., & Vardi, Y.
Affiliations: AT&T (United States) (US)
Venue: IEEE Transactions on Medical Imaging
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Published: 1982-10
Volume: 1
Issue: 2
Pages: 113-122
ISSN: 0278-0062 (ISSN-L)
1558-254X
DOI: 10.1109/tmi.1982.4307558
OpenAlex: W2069629287
Cited by: 4,429
References: 9
Citations by year: 2026: 74 · 2025: 101 · 2024: 122 · 2023: 101 · 2022: 117 · 2021: 140 · 2020: 154 · 2019: 153 · 2018: 137 · 2017: 142 · 2016: 152 · 2015: 164 · 2014: 167 · 2013: 182 · 2012: 176
FWCI: 10.00
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
Physical Sciences › Mathematics › Mathematical Physics › Numerical methods in inverse problems
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Signal Denoising Methods
Keywords: emission tomography, maximum likelihood reconstruction, expectation-maximization algorithm, Poisson likelihood, tomographic reconstruction

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

Maximum Likelihood Reconstruction for Emission Tomography

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