Threshold selection, mitosis and dual mutation in cooperative co-evolution: application to medical 3d tomography
| Autor: | Franck Vidal, Jean-Marie Rocchisani, Jean Louchet, Evelyne Lutton |
|---|---|
| Přispěvatelé: | Bangor University, Analysis and Visualization (AVIZ), Laboratoire de Recherche en Informatique (LRI), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), University College Ghent, Dept INWE, University College Ghent, Service de médecine nucléaire [Bobigny], Université Paris 13 (UP13)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Avicenne [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), UFR Santé, Médecine et Biologie Humaine (UFR SMBH), Université Paris 13 (UP13) |
| Jazyk: | angličtina |
| Rok vydání: | 2010 |
| Předmět: |
0303 health sciences
Mathematical optimization education.field_of_study Cooperative coevolution Basis (linear algebra) Computer science Population 02 engineering and technology 03 medical and health sciences Adaptive mutation [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Position (vector) Algorithmic efficiency Mutation (genetic algorithm) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing education [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing Selection (genetic algorithm) 030304 developmental biology |
| Zdroj: | PPSN 2010, 11th International Conference on Parallel Problem Solving From Nature. PPSN 2010, 11th International Conference on Parallel Problem Solving From Nature., Sep 2010, Krakow, Poland Parallel Problem Solving from Nature, PPSN XI ISBN: 9783642158438 PPSN (1) |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|