Iterative image reconstruction using geometrically ordered subsets with list-mode data
- Resource Type
- Conference
- Authors
- Popescu, L.M.; Matej, S.; Lewitt, R.M.
- Source
- IEEE Symposium Conference Record Nuclear Science 2004. Nuclear science symposium Nuclear Science Symposium Conference Record, 2004 IEEE. 6:3536-3540 Vol. 6 2004
- Subject
- Nuclear Engineering
Power, Energy and Industry Applications
Fields, Waves and Electromagnetics
Engineered Materials, Dielectrics and Plasmas
Image reconstruction
Change detection algorithms
Event detection
Maximum likelihood estimation
Positron emission tomography
Reconstruction algorithms
Histograms
Iterative algorithms
Memory management
Maximum likelihood detection
- Language
- ISSN
- 1082-3654
In positron emission tomography (PET), the format in which the data is stored has a major influence on the image reconstruction procedure. The use of the list-mode format preserves all of the measured attributes of the detected photon pairs but the events are stored in the order that they were measured, which allows only sequential access to the data. This fact limits the number of applicable algorithms and often computing speed or memory capacity constraints require the use of algorithms that do not make full use of the original precise information in the data. In this paper we show how through a change of the format in which the data is stored one can keep all the initial information about the individual events while providing random access to subsets of events belonging to given geometrical regions, thus making possible the use of maximum likelihood ordered subsets (OSEM) type algorithms with data provided as a collection of individual events (list-mode), and facilitating the adaptation of other types of algorithms. The structured data format also allows for more compact (compressed) storage of the information compared to the simple list-mode format.