Fully Three-Dimensional Tomographic Evolutionary Reconstruction in Nuclear Medicine

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Bousquet:2007:EA,

• author = "Aurelie Bousquet and Jean Louchet and Jean-Marie Rocchisani",
• title = "Fully Three-Dimensional Tomographic Evolutionary Reconstruction in Nuclear Medicine",
• booktitle = "Artificial Evolution, 2007",
• year = "2007",
• editor = "Nicolas Monmarche and El-Ghazali Talbi and Pierre Collet and Marc Schoenauer and Evelyne Lutton",
• volume = "4926",
• series = "Lecture Notes in Computer Science",
• pages = "231--242",
• address = "Tours, France",
• month = oct # " 29-31",
• publisher = "Springer",
• note = "Revised Selected Papers",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-540-79304-5",
• DOI = "doi:10.1007/978-3-540-79305-2_20",
• abstract = "3-D reconstruction in Nuclear Medicine imaging using complete Monte-Carlo simulation of trajectories usually requires high computing power. We are currently developing a Parisian Evolution Strategy in order to reduce the computing cost of reconstruction without degrading the quality of results. Our approach derives from the Fly algorithm which proved successful on real-time stereo image sequence processing. Flies are considered here as photon emitters. We developed the marginal fitness technique to calculate the fitness function, an approach usable in Parisian Evolution whenever each individual's fitness cannot be calculated independently of the rest of the population.",
• notes = "Published 2008?",

}

Genetic Programming entries for Aurelie Bousquet Jean Louchet Jean-Marie Rocchisani

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