3D PET image reconstruction based on the maximum likelihood estimation method (MLEM) algorithm
-
Artur Słomski
,
Zbigniew Rudy
,
Tomasz Bednarski
Abstract
A positron emission tomography (PET) scan does not measure an image directly. Instead, a PET scan measures a sinogram at the boundary of the field-of-view that consists of measurements of the sums of all the counts along the lines connecting the two detectors. Because there is a multitude of detectors built in a typical PET structure, there are many possible detector pairs that pertain to the measurement. The problem is how to turn this measurement into an image (this is called imaging). Significant improvement in PET image quality was achieved with the introduction of iterative reconstruction techniques. This was realized approximately 20 years ago (with the advent of new powerful computing processors). However, three-dimensional imaging still remains a challenge. The purpose of the image reconstruction algorithm is to process this imperfect count data for a large number (many millions) of lines of response and millions of detected photons to produce an image showing the distribution of the labeled molecules in space.
Acknowledgments
We acknowledge technical and administrative support from M. Adamczyk, T. Gucwa-Rys, A. Heczko, M. Kajetanowicz, G. Konopka-Cupiał, J. Majewski, W. Migdał, A. Misiak, and financial support by the Polish National Center for Development and Research through grant INNOTECH-K1/IN1/64/159174/NCBR/12, the Foundation for Polish Science through the MPD program, and the EU and MSHE Grant No. POIG.02.03.00-161 00-013/09.
Conflict of interest statement
Authors’ conflict of interest disclosure: The authors stated that there are no conflicts of interest regarding the publication of this article. Research funding played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
Research funding: None declared.
Employment or leadership: None declared.
Honorarium: None declared.
References
1. Radon J. Ueber die Bestimmung von Funktionen durch ihre Integralwerte laengsbestimmter Mannigfaltigkeiten. Ber Verb Sächs Akad Wissensch Lepzig Math-Nat Kl 1917;69:262–77.Suche in Google Scholar
2. Herman GT. Image reconstruction from projections. New York: Academic Press, 1980.10.1007/3-540-09417-2Suche in Google Scholar
3. Smith KT, Keinert F. Mathematical foundations of computed tomography. Appl Optics 1985;24:3950–7.10.1364/AO.24.003950Suche in Google Scholar PubMed
4. Parra L, Barrett H. List mode likelihood: EM algorithm and image quality estimation demonstrated on 2D PET. IEEE Trans Med Imag 1998;17:228–35.10.1109/42.700734Suche in Google Scholar PubMed PubMed Central
5. Yokoi T, Shinohara H, Hashimoto T, Yamamoto T, Niio Y. Proceedings of the Second International Workshop on EGS, 8–12 August 2000, Tsukuba, Japan. KEK Proc 2000;20:224–34.Suche in Google Scholar
6. Wang ZA, Bovik C, Sheikh HR, Simoncelli EP. Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 2004;16:600–12.10.1109/TIP.2003.819861Suche in Google Scholar
©2014 by Walter de Gruyter Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Original Articles
- 3D PET image reconstruction based on the maximum likelihood estimation method (MLEM) algorithm
- List-mode reconstruction in 2D strip PET
- Calibration of photomultipliers gain used in the J-PET detector
- A novel method for calibration and monitoring of time synchronization of TOF-PET scanners by means of cosmic rays
- Plastic scintillators for positron emission tomography obtained by the bulk polymerization method
- J-PET analysis framework for the prototype TOF-PET detector
- Trigger-less and reconfigurable data acquisition system for positron emission tomography
- A novel method based solely on field programmable gate array (FPGA) units enabling measurement of time and charge of analog signals in positron emission tomography (PET)
- Review
- Positron emission tomography (PET) in oncology: current applications and future perspectives
Artikel in diesem Heft
- Frontmatter
- Original Articles
- 3D PET image reconstruction based on the maximum likelihood estimation method (MLEM) algorithm
- List-mode reconstruction in 2D strip PET
- Calibration of photomultipliers gain used in the J-PET detector
- A novel method for calibration and monitoring of time synchronization of TOF-PET scanners by means of cosmic rays
- Plastic scintillators for positron emission tomography obtained by the bulk polymerization method
- J-PET analysis framework for the prototype TOF-PET detector
- Trigger-less and reconfigurable data acquisition system for positron emission tomography
- A novel method based solely on field programmable gate array (FPGA) units enabling measurement of time and charge of analog signals in positron emission tomography (PET)
- Review
- Positron emission tomography (PET) in oncology: current applications and future perspectives
