On the Effect of Relaxation in the Convergence and Quality of Statistical Image Reconstruction for Emission Tomography Using Block-Iterative Algorithms

Relaxation is widely recognized as a useful tool for providing convergence in block-iterative algorithms [1], [2], [6]. In the present article we give new results on the convergence of RAMLA (Row Action Maximum Likelihood Algorithm) [2], filling some important theoretical gaps. Furthermore, because...

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Vydané v:	XVIII Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI'05) s. 13 - 20
Hlavní autori:	Neto, E.S.H., De Pierro, A.R.
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 2005
Predmet:	Convergence Detectors Filling Image quality Image recognition Image reconstruction Inverse problems Maximum likelihood detection Positron emission tomography Single photon emission computed tomography
ISBN:	9780769523897, 0769523897
ISSN:	1530-1834
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