Literature DB >> 21339831

Image reconstruction for PET/CT scanners: past achievements and future challenges.

Shan Tong1, Adam M Alessio, Paul E Kinahan.   

Abstract

PET is a medical imaging modality with proven clinical value for disease diagnosis and treatment monitoring. The integration of PET and CT on modern scanners provides a synergy of the two imaging modalities. Through different mathematical algorithms, PET data can be reconstructed into the spatial distribution of the injected radiotracer. With dynamic imaging, kinetic parameters of specific biological processes can also be determined. Numerous efforts have been devoted to the development of PET image reconstruction methods over the last four decades, encompassing analytic and iterative reconstruction methods. This article provides an overview of the commonly used methods. Current challenges in PET image reconstruction include more accurate quantitation, TOF imaging, system modeling, motion correction and dynamic reconstruction. Advances in these aspects could enhance the use of PET/CT imaging in patient care and in clinical research studies of pathophysiology and therapeutic interventions.

Entities:  

Year:  2010        PMID: 21339831      PMCID: PMC3039307          DOI: 10.2217/iim.10.49

Source DB:  PubMed          Journal:  Imaging Med        ISSN: 1755-5191


  79 in total

1.  Comparison of 3-D maximum a posteriori and filtered backprojection algorithms for high-resolution animal imaging with microPET.

Authors:  A Chatziioannou; J Qi; A Moore; A Annala; K Nguyen; R Leahy; S R Cherry
Journal:  IEEE Trans Med Imaging       Date:  2000-05       Impact factor: 10.048

2.  Clinically significant inaccurate localization of lesions with PET/CT: frequency in 300 patients.

Authors:  Medhat M Osman; Christian Cohade; Yuji Nakamoto; Laura T Marshall; Jeff P Leal; Richard L Wahl
Journal:  J Nucl Med       Date:  2003-02       Impact factor: 10.057

3.  Correction methods for random coincidences in fully 3D whole-body PET: impact on data and image quality.

Authors:  David Brasse; Paul E Kinahan; Carole Lartizien; Claude Comtat; Mike Casey; Christian Michel
Journal:  J Nucl Med       Date:  2005-05       Impact factor: 10.057

Review 4.  Multimodality in vivo imaging systems: twice the power or double the trouble?

Authors:  Simon R Cherry
Journal:  Annu Rev Biomed Eng       Date:  2006       Impact factor: 9.590

Review 5.  Monitoring cancer treatment with PET/CT: does it make a difference?

Authors:  Wolfgang A Weber; Robert Figlin
Journal:  J Nucl Med       Date:  2007-01       Impact factor: 10.057

6.  Accelerated iterative reconstruction for positron emission tomography based on the em algorithm for maximum likelihood estimation.

Authors:  R M Lewitt; G Muehllehner
Journal:  IEEE Trans Med Imaging       Date:  1986       Impact factor: 10.048

7.  A note on stopping rules in EM-ML reconstructions of ECT images.

Authors:  V E Johnson
Journal:  IEEE Trans Med Imaging       Date:  1994       Impact factor: 10.048

8.  Fast point spread function computation from aperture functions in high-resolution positron emission tomography.

Authors:  D Schmitt; B Karuta; C Carrier; R Lecomte
Journal:  IEEE Trans Med Imaging       Date:  1988       Impact factor: 10.048

Review 9.  Instrumentation aspects of animal PET.

Authors:  Yuan-Chuan Tai; Richard Laforest
Journal:  Annu Rev Biomed Eng       Date:  2005       Impact factor: 9.590

10.  Modeling and incorporation of system response functions in 3-D whole body PET.

Authors:  Adam M Alessio; Paul E Kinahan; Thomas K Lewellen
Journal:  IEEE Trans Med Imaging       Date:  2006-07       Impact factor: 10.048

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  24 in total

Review 1.  Innovations in Instrumentation for Positron Emission Tomography.

Authors:  Eric Berg; Simon R Cherry
Journal:  Semin Nucl Med       Date:  2018-03-12       Impact factor: 4.446

Review 2.  Quantitative Rodent Brain Receptor Imaging.

Authors:  Kristina Herfert; Julia G Mannheim; Laura Kuebler; Sabina Marciano; Mario Amend; Christoph Parl; Hanna Napieczynska; Florian M Maier; Salvador Castaneda Vega; Bernd J Pichler
Journal:  Mol Imaging Biol       Date:  2020-04       Impact factor: 3.488

3.  Ordered subset expectation maximization algorithm for positron emission tomographic image reconstruction using belief kernels.

Authors:  Yang-Ming Zhu
Journal:  J Med Imaging (Bellingham)       Date:  2018-11-21

4.  Impact of different image reconstructions on PET quantification in non-small cell lung cancer: a comparison of adenocarcinoma and squamous cell carcinoma.

Authors:  Michael Messerli; Fotis Kotasidis; Irene A Burger; Daniela A Ferraro; Urs J Muehlematter; Corina Weyermann; David Kenkel; Gustav K von Schulthess; Philipp A Kaufmann; Martin W Huellner
Journal:  Br J Radiol       Date:  2019-02-26       Impact factor: 3.039

5.  Standard OSEM vs. regularized PET image reconstruction: qualitative and quantitative comparison using phantom data and various clinical radiopharmaceuticals.

Authors:  Judit Lantos; Erik S Mittra; Craig S Levin; Andrei Iagaru
Journal:  Am J Nucl Med Mol Imaging       Date:  2018-04-25

6.  Artificial Neural Network Enhanced Bayesian PET Image Reconstruction.

Authors:  Bao Yang; Leslie Ying; Jing Tang
Journal:  IEEE Trans Med Imaging       Date:  2018-06       Impact factor: 10.048

Review 7.  Positron emission tomography-computed tomography standardized uptake values in clinical practice and assessing response to therapy.

Authors:  Paul E Kinahan; James W Fletcher
Journal:  Semin Ultrasound CT MR       Date:  2010-12       Impact factor: 1.875

Review 8.  Artificial Intelligence for Response Evaluation With PET/CT.

Authors:  Lise Wei; Issam El Naqa
Journal:  Semin Nucl Med       Date:  2020-11-11       Impact factor: 4.446

9.  Phantom and clinical assessment of small pulmonary nodules using Q.Clear reconstruction on a silicon-photomultiplier-based time-of-flight PET/CT system.

Authors:  Zhifang Wu; Binwei Guo; Bin Huang; Xinzhong Hao; Ping Wu; Bin Zhao; Zhixing Qin; Jun Xie; Sijin Li
Journal:  Sci Rep       Date:  2021-05-14       Impact factor: 4.379

Review 10.  Artificial intelligence in molecular imaging.

Authors:  Edward H Herskovits
Journal:  Ann Transl Med       Date:  2021-05
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