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Titolo:
The ordered subsets mirror descent optimization method with applications to tomography
Autore:
Ben-Tal, A; Margalit, T; Nemirovski, A;
Indirizzi:
Technion Israel Inst Technol, Fac Ind Engn & Management, MINERVA OptimizatCtr, IL-32000 Haifa, Israel Technion Israel Inst Technol Haifa Israel IL-32000 L-32000 Haifa, Israel
Titolo Testata:
SIAM JOURNAL ON OPTIMIZATION
fascicolo: 1, volume: 12, anno: 2001,
pagine: 79 - 108
SICI:
1052-6234(20011023)12:1<79:TOSMDO>2.0.ZU;2-A
Fonte:
ISI
Lingua:
ENG
Soggetto:
RECONSTRUCTION; EMISSION; CT;
Keywords:
positron emission tomography; maximum likelihood; image reconstruction; convex optimization; mirror descent;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Physical, Chemical & Earth Sciences
Citazioni:
22
Recensione:
Indirizzi per estratti:
Indirizzo: Ben-Tal, A Technion Israel Inst Technol, Fac Ind Engn & Management, MINERVA OptimizatCtr, IL-32000 Haifa, Israel Technion Israel Inst Technol HaifaIsrael IL-32000 fa, Israel
Citazione:
A. Ben-Tal et al., "The ordered subsets mirror descent optimization method with applications to tomography", SIAM J OPTI, 12(1), 2001, pp. 79-108

Abstract

We describe an optimization problem arising in reconstructing three-dimensional medical images from positron emission tomography (PET). A mathematical model of the problem, based on the maximum likelihood principle, is posedas a problem of minimizing a convex function of several million variables over the standard simplex. To solve a problem of these characteristics, we develop and implement a new algorithm, ordered subsets mirror descent, and demonstrate, theoretically and computationally, that it is well suited for solving the PET reconstruction problem.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 25/01/20 alle ore 03:41:47