Artificial Evolution for 3D PET Reconstruction

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Vidal:2009:EA,

• author = "Franck P. Vidal and Delphine Lazaro-Ponthus and Samuel Legoupil and Jean Louchet and Evelyne Lutton and Jean-Marie Rocchisani",
• title = "Artificial Evolution for {3D PET} Reconstruction",
• booktitle = "Artificial Evolution, EA 2009",
• year = "2009",
• editor = "Pierre Collet and Nicolas Monmarche and Pierrick Legrand and Marc Schoenauer and Evelyne Lutton",
• volume = "5975",
• series = "Lecture Notes in Computer Science,",
• pages = "37--48",
• address = "Strasbourg, France",
• month = "26-28 " # oct,
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, Positron Emission Tomography, Positron Emission Tomography Imaging, Compton Scattering, Bright Area, Tomographic Reconstruction",
• isbn13 = "978-3-642-14155-3",
• DOI = "doi:10.1007/978-3-642-14156-0_4",
• abstract = "This paper presents a method to take advantage of artificial evolution in positron emission tomography reconstruction. This imaging technique produces datasets that correspond to the concentration of positron emitters through the patient. Fully 3D tomographic reconstruction requires high computing power and leads to many challenges. Our aim is to reduce the computing cost and produce datasets while retaining the required quality. Our method is based on a coevolution strategy (also called Parisian evolution) named fly algorithm. Each fly represents a point of the space and acts as a positron emitter. The final population of flies corresponds to the reconstructed data. Using marginal evaluation, the fly's fitness is the positive or negative contribution of this fly to the performance of the population. This is also used to skip the relatively costly step of selection and simplify the evolutionary algorithm.",

}

Genetic Programming entries for Franck P Vidal Delphine Lazaro-Ponthus Samuel Legoupil Jean Louchet Evelyne Lutton Jean-Marie Rocchisani

Citations