Aspects of Three-Dimensional Imaging by Classical Tomography for Dual Detector Positron Emission Mammography (PEM)
Images from dual detector positron emission mammography (PEM) systems are commonly reconstructed by backprojection methods of classical tomography. Characteristics of three-dimensional (3-D) PEM images were investigated using analytic models, computer simulations, and experimental acquisitions with compact pixellated detectors, in particular depth resolution normal to the detectors. An analytic formula was developed using circular image pixels that models blurring normal to the detectors. The amount of blurring is dependent on the acceptance angle for coincidence events and may vary across the field of view due to geometric limitations on the maximum angle of lines of response normal to the detectors. For experimental acquisitions with line sources and a pixellated lutetium gadolinium oxyorthosilicate (LGSO) detector, depth resolution is broader than predicted by numerical simulations, possibly due to uncorrected randoms or scatter within the scintillator arrays. Iterative image reconstruction with the maximum likelihood expectation maximization (MLEM) algorithm of a compressed breast phantom acquisition with a pixellated gadolinium oxyorthosilicate (GSO) detector shows improved contract compared with backprojection reconstruction. Image reconstruction for dual detector PEM with static detectors represents a case of limited angle tomography with truncated projection data, and there is the opportunity to improve three-dimensional PEM imaging by the use of more sophisticated image reconstruction techniques.
- Research Organization:
- Thomas Jefferson National Accelerator Facility, Newport News, VA (US)
- Sponsoring Organization:
- USDOE Office of Energy Research (ER) (US)
- DOE Contract Number:
- AC05-84ER40150
- OSTI ID:
- 790066
- Report Number(s):
- JLAB-PHY-02-03; DOE/ER/40150-1979; 1 R21 CA82752-01; 1 R21 CA82752-01 National Cancer Institute of the National Institutes of Health
- Country of Publication:
- United States
- Language:
- English
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