Abstract
This paper discusses Mixed-Integer Evolution Strategies and their application to an automatic image analysis system for IntraVascular UltraSound (IVUS) images. Mixed-Integer Evolution Strategies can optimize different types of decision variables, including continuous, nominal discrete, and ordinal discrete values. The algorithm is first applied to a set of test problems with scalable ruggedness and dimensionality. The algorithm is then applied to the optimization of an IVUS image analysis system. The performance of this system depends on a large number of parameters that – so far – need to be chosen manually by a human expert. It will be shown that a mixed-integer evolution strategy algorithm can significantly improve these parameters compared to the manual settings by the human expert.
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Li, R. et al. (2006). Mixed-Integer Evolution Strategies and Their Application to Intravascular Ultrasound Image Analysis. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2006. Lecture Notes in Computer Science, vol 3907. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11732242_37
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DOI: https://doi.org/10.1007/11732242_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33237-4
Online ISBN: 978-3-540-33238-1
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