EIT reconstruction of static images by a genetic algorithm approach (Contributo in volume (capitolo o saggio))

Type
Label
  • EIT reconstruction of static images by a genetic algorithm approach (Contributo in volume (capitolo o saggio)) (literal)
Anno
  • 1999-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1111/j.1749-6632.1999.tb09494.x (literal)
Alternative label
  • R.Olmi, M.Bini, S.Manetta and S.Priori (1999)
    EIT reconstruction of static images by a genetic algorithm approach
    in ELECTRICAL BIOIMPEDANCE METHODS: APPLICATIONS TO MEDICINE AND BIOTECHNOLOGY, 1999
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • R.Olmi, M.Bini, S.Manetta and S.Priori (literal)
Pagina inizio
  • 454 (literal)
Pagina fine
  • 465 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • ELECTRICAL BIOIMPEDANCE METHODS: APPLICATIONS TO MEDICINE AND BIOTECHNOLOGY (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
  • 873 (literal)
Note
  • ISI Web of Science (WOS) (literal)
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • IROE-CNR (literal)
Titolo
  • EIT reconstruction of static images by a genetic algorithm approach (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 1-57331-190-1 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume
  • Riu, PJ; Rosell, J; Bragos, R; (literal)
Abstract
  • A genetic algorithm (GA) approach is proposed for the reconstruction of static images in electrical impedance tomography (EIT). Genetic algorithms can be demonstrated to possess several advantages over more conventional 'gradient-based' techniques. In particular, they are implicitly parallel and realize a good compromise between 'exploration' and 'exploitation', thus being more robust against the problem of false minima. The results of GA-EIT in numerical experiments are presented, compared to those obtained by other, more established inversion methods, such as the modified Newton-Raphson method and the double-constraint method. The GA approach is relatively expensive in terms of computation time and resources, requiring (for example) from several minutes to tens of minutes on a Pentium Pro 200-based machine for normal-size EIT problems. This currently limits the applicability of GA-EIT to the field of static imaging. However, in light of the development trend in the field of computing, an extension to real-time dynamic imaging applications is not inconceivable in the near future. (literal)
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