New Genetic Operators in the Fly Algorithm: Application to Medical PET Image Reconstruction

Abstract. This paper presents an evolutionary approach for image reconstruction in positron emission tomography (PET). 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.

• Type: Journal
• Year: 2010
• Where: EVOW
• Authors: Franck Patrick Vidal, Jean Louchet, Jean-Marie Rocchisani, Evelyne Lutton
• Keywords: Artificial Intelligence, Classical Tournament Method, Cooperative Coevolution Strategy, EVOW 2010, Positron Emission Tomography