Maximum-likelihood reconstruction of transmission images in emission computed tomography via the EM algorithm
- Washington Univ., St. Louis, MO (United States)
The expectation-maximization (EM) algorithm for computing maximum-likelihood estimates of transmission images in positron-emission tomography (PET) is extended to include measurement error, accidental coincidences and Compton scatter. A method for accomplishing the maximization step using one step of Newton's method is proposed. The algorithm is regularized with the method of sieves. Evaluations using both Monte Carlo simulations and phantom studies on the Siemens 953B scanner suggest that the algorithm yields unbiased images with significantly lower variances than filtered-backprojection when the images are reconstructed to the intrinsic resolution. Large features in the images converge in under 200 iterations while the smallest features required up to 2,000 iterations. All but the smallest features in typical transmission scans converge in approximately 250 iterations. The initial implementation of the algorithm requires 50 sec per iteration o a DECStation 5000.
- OSTI ID:
- 7242775
- Journal Information:
- IEEE Transactions on Medical Imaging (Institute of Electrical and Electronics Engineers); (United States), Vol. 13:1; ISSN 0278-0062
- Country of Publication:
- United States
- Language:
- English
Similar Records
Fast gradient-based methods for Bayesian reconstruction of transmission and emission PET images
Penalized weighted least-squares image reconstruction for positron emission tomography
Related Subjects
EMISSION COMPUTED TOMOGRAPHY
ALGORITHMS
IMAGE PROCESSING
OPTIMIZATION
X RADIATION
COMPUTERIZED TOMOGRAPHY
DIAGNOSTIC TECHNIQUES
ELECTROMAGNETIC RADIATION
IONIZING RADIATIONS
MATHEMATICAL LOGIC
PROCESSING
RADIATIONS
TOMOGRAPHY
550602* - Medicine- External Radiation in Diagnostics- (1980-)