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.
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©2014 by Walter de Gruyter Berlin/Boston
Articles in the same Issue
- 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
Articles in the same Issue
- 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
