Maximum likelihood reconstruction for SPECT with Monte Carlo Modeling: Asymptotic behavior
Inverse Monte Carlo (IMOC) reconstruction for SPECT uses a Maximum Likelihood (EM) estimator with detection probabilities generated as Monte Carlo solutions to the photon transport equation (PTE). To evaluate the behavior of the iterative EM algorithm, reconstructions from experimental projection data for up to 1000 iterations were examined. Compensation for scatter and attenuation was achieved by including those effects in the PTE. For uniform activity distribution, noise increased monotonically with iteration. With line sources included, both noise and resolution improved between 1 and 30 iterations after which resolution was slightly improved at the expense of noise. Contrast (for a nonactive region surrounded by activity) improved from 0.32 at 5 iterations to 0.90 at 200 iterations, and 0.97 at 1000. Uncertainty in the measurement increased due to increased noise in the active region.
- Research Organization:
- Duke Univ. Medical Center, Durham, NC 27710
- OSTI ID:
- 6651240
- Report Number(s):
- CONF-861007-
- Journal Information:
- IEEE Trans. Nucl. Sci.; (United States), Journal Name: IEEE Trans. Nucl. Sci.; (United States) Vol. NS-34:1; ISSN IETNA
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
62 RADIOLOGY AND NUCLEAR MEDICINE
ALGORITHMS
ATTENUATION
BOUNDARY CONDITIONS
COMPUTERIZED TOMOGRAPHY
DATA COVARIANCES
DIAGNOSTIC TECHNIQUES
EMISSION COMPUTED TOMOGRAPHY
EQUATIONS
GAMMA TRANSPORT THEORY
ITERATIVE METHODS
MATHEMATICAL LOGIC
MATHEMATICAL MODELS
MAXIMUM-LIKELIHOOD FIT
MONTE CARLO METHOD
NEUTRAL-PARTICLE TRANSPORT
NOISE
NUMERICAL SOLUTION
PHOTON TRANSPORT
PROBABILITY
RADIATION TRANSPORT
RESOLUTION
SCATTERING
SINGLE PHOTON EMISSION COMPUTED TOMOGRAPHY
TOMOGRAPHY
TRANSPORT THEORY