Principles of computerized tomographic imaging
Principles of computerized tomographic imaging
Stereo Analysis Using Individual Evolution Strategy
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
Multiple Network CGP for the Classification of Mammograms
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Fully three-dimensional tomographic evolutionary reconstruction in nuclear medicine
EA'07 Proceedings of the Evolution artificielle, 8th international conference on Artificial evolution
Artificial evolution for 3D PET reconstruction
EA'09 Proceedings of the 9th international conference on Artificial evolution
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
| Hi-index | 0.00 |
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.