Threshold selection, mitosis and dual mutation in cooperative co-evolution: application to medical 3d tomography

Franck P. Vidal (1) , Evelyne Lutton (2) , Jean Louchet (3) , Jean-Marie Rocchisani (4, 5)

1 Bangor University
2 AVIZ - Analysis and Visualization
3 University College Ghent, Dept INWE
4 Service de médecine nucléaire [Bobigny]
5 UFR SMBH - UFR Santé, Médecine et Biologie Humaine

We present and analyse the behaviour of specialised operators designed for cooperative coevolution strategy in the framework of 3D tomographic PET reconstruction. The basis is a simple cooperative co-evolution scheme (the "fly algorithm"), which embeds the searched solution in the whole population, letting each individual be only a part of the solution. An individual, or fly, is a 3D point that emits positrons. Using a cooperative co-evolution scheme to optimize the position of positrons, the population of flies evolves so that the data estimated from flies matches measured data. The final population approximates the radioactivity concentration. In this paper, three operators are proposed, threshold selection, mitosis and dual mutation, and their impact on the algorithm efficiency is experimentally analysed on a controlled test-case. Their extension to other cooperative co-evolution schemes is discussed.

Domains: Signal and Image processing; Signal and Image Processing

Franck P. Vidal, Evelyne Lutton, Jean Louchet, Jean-Marie Rocchisani. Threshold selection, mitosis and dual mutation in cooperative co-evolution: application to medical 3d tomography. PPSN 2010, 11th International Conference on Parallel Problem Solving From Nature., Sep 2010, Krakow, Poland. ⟨hal-00783841⟩