Acquisition and reconstruction of data in three-dimensional positron emission tomography (3D PET) was introduced in 1990 almost 20 years after the first PET scanners were developed. 3D PET offers a significant sensitivity improvement over conventional, sliceoriented 2D PET, but at the cost of a three-fold increase in acceptance of scattered events. In addition, processing time is increased and new methods for applying corrections such as for photon attenuation, calibration, and detector/geometry normalisation are required. 3D PET raised concerns that the high quantitative accuracy that was possible with 2D PET (with its moderate sensitivity) would not be matched in 3D, primarily because of the greatly increased scattered photon component in the measured data. The aim of this thesis was to develop methods that enable quantitatively accurate measurements with 3D PET. A technique to correct for scattered photons prior to reconstruction has been developed, implemented and assessed. A device for normalising the data for detector efficiency and the geometry of the cylindrical detector system has been developed, and the factors affecting reconstruction investigated. A new approach to calibration of the reconstructed data to produce images of activity concentration which is independent of scatter has been implemented. Finally, the techniques have been applied to data from brain scans of human subjects. Evaluation of images reconstructed from 3D PET demonstrates that the methodology developed in this work produces data accurate to within 10% of the true activity concentration in an object with reasonably homogeneous density. 3D PET is shown to be as accurate as 2D PET, but with a sensitivity advantage that improves signal-to-noise by approximately a factor of three in the human brain and slightly less in other regions of the body.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:309199 |
| Date | January 1996 |
| Creators | Bailey, Dale L. |
| Publisher | University of Surrey |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://epubs.surrey.ac.uk/770395/ |
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