Threshold selection, mitosis and dual mutation in cooperative coevolution: application to medical 3D tomography

Abstract

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.

Citation

F. P. Vidal, É. Lutton, J. Louchet, and J.-M. Rocchisani, “Threshold selection, mitosis and dual mutation in cooperative coevolution: application to medical 3D tomography,” in International Conference on Parallel Problem Solving From Nature (PPSN’10), Krakow, Poland, 2010, vol. 6238, pp. 414–423.

Bibtex

@inproceedings{Vidal2010PPSN,
  author = {Vidal, F. P. and Lutton, \'E. and Louchet, J. and Rocchisani, {J.-M.}},
  title = {Threshold selection, mitosis and dual mutation in cooperative
      coevolution: application to medical {3D} tomography},
  booktitle = {International Conference on Parallel Problem Solving From Nature
      (PPSN'10)},
  year = {2010},
  series = {Lecture Notes in Computer Science},
  volume = {6238},
  pages = {414-423},
  month = sep,
  address = {Krakow, Poland},
  annotation = {Sept~11--15, 2010},
  doi = {10.1007/978-3-642-15844-5_42},
  publisher = {Springer, Heidelberg}
}

Resources

   Doi: 10.1007/978-3-642-15844-5_42