Abstract
This paper discusses a study towards dynamic fitness based partitioning in IntraVascular UltraSound (IVUS) image analysis. MixedInteger Evolution Strategies (MI-ES) have recently been successfully used to optimize control parameters of a multi-agent image interpretation system for IVUS images lumen detection. However, because of complex interpretation contexts, it is impossible to find one single solution which works well on each possible image of each possible patient. Therefore it would be wise to let MI-ES find a set of solutions based on an optimal partition of IVUS images. Here a methodology is presented which does dynamic fitness based partitioning of the data during the MI-ES parameter optimization procedure. As a first step we applied this method to a challenging artificial test case which demonstrates the feasibility of our approach. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Li, R., Eggermont, J., Emmerich, M. T. M., Bovenkamp, E. G. P., Back, T., Dijkstra, J., & Reiber, J. H. C. (2007). Towards dynamic fitness based partitioning for intravascular ultrasound image analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4448 LNCS, pp. 391–398). Springer Verlag. https://doi.org/10.1007/978-3-540-71805-5_43
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