Abstract
This paper discusses a study towards dynamic fitness based partitioning in IntraVascular UltraSound (IVUS) image analysis. Mixed-Integer 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.
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Li, R. et al. (2007). Towards Dynamic Fitness Based Partitioning for IntraVascular UltraSound Image Analysis. In: Giacobini, M. (eds) Applications of Evolutionary Computing. EvoWorkshops 2007. Lecture Notes in Computer Science, vol 4448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71805-5_43
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DOI: https://doi.org/10.1007/978-3-540-71805-5_43
Publisher Name: Springer, Berlin, Heidelberg
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