New genetic operators in the fly algorithm: application to medical PET image reconstruction

Abstract : Our reconstruction method is based on a cooperative coevolution strategy (also called Parisian evolution): the "fly algorithm". Each fly is a 3D point that mimics a positron emitter. The flies' position is progressively optimised using evolutionary computing to closely match the data measured by the imaging system. The performance of each fly is assessed using a "marginal evaluation" based on the positive or negative contribution of this fly to the performance of the population. Using this property, we propose a "thresholded-selection" method to replace the classical tournament method. A mitosis operator is also proposed. It is triggered to automatically increase the population size when the number of flies with negative fitness becomes too low.
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EVOIASP, Evolutionary Computation in Image Analysis and Signal Processing, EvoApplications 2010, Apr 2010, Istambul, Turkey. Springer, 6024, 2010, LNCS
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Franck Vidal, Jean Louchet, Jean-Marie Rocchisani, Evelyne Lutton. New genetic operators in the fly algorithm: application to medical PET image reconstruction. EVOIASP, Evolutionary Computation in Image Analysis and Signal Processing, EvoApplications 2010, Apr 2010, Istambul, Turkey. Springer, 6024, 2010, LNCS. 〈hal-00783832〉

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