Convergent algorithms for statistical image reconstruction in emission tomography
Convergent algorithms for statistical image reconstruction in emission tomography
Accelerating the EMML algorithm and related iterative algorithms by rescaled block-iterative methods
IEEE Transactions on Image Processing
Penalized maximum-likelihood image reconstruction using space-alternating generalized EM algorithms
IEEE Transactions on Image Processing
Hi-index | 0.00 |
In this paper, the authors/researchers will introduce the incremental optimisation transfer framework to estimate emission means in positron emission tomography. The proposed algorithms accelerate convergence speeds and ensure global convergence (to a stationary point) under mild regularity conditions without inconvenient relaxation parameters. In experiments using synthetic data and real phantom data, it was found that, for a fixed level of background noise, the proposed idea in this paper provides high-quality reconstructed images.