Title :
BLOCK-ITERATIVE FISHER SCORING FOR EMISSION TOMOGRAPHY
Author :
Ma, Jun ; Hudson, Malcolm
Author_Institution :
Dept. of Stat., Macquarie Univ., North Ryde, NSW
Abstract :
We introduce and evaluate a block-iterative Fisher scoring (BFS) algorithm for emission tomography. Regularization is achieved by penalized likelihood with a general quadratic penalty. When the algorithm converges, it converges to the unconstrained maximum penalized likelihood (MPL) solution. In a simulated data set, constrained BFS achieves a higher penalized likelihood in fewer iterations than other block-iterative algorithms which are designed for non-negatively constrained penalized reconstruction
Keywords :
emission tomography; iterative methods; maximum likelihood estimation; Block-iterative fisher scoring; emission tomography; maximum penalized likelihood; Algorithm design and analysis; Cameras; Equations; Linear systems; Maximum likelihood detection; Maximum likelihood estimation; Parameter estimation; Reconstruction algorithms; Statistics; Tomography;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2007. ISBI 2007. 4th IEEE International Symposium on
Conference_Location :
Arlington, VA
Print_ISBN :
1-4244-0672-2
Electronic_ISBN :
1-4244-0672-2
DOI :
10.1109/ISBI.2007.356811
