Abstract
In this paper, we investigate the improvement obtained by applying a distributed genetic algorithm to a problem of parameter optimization in medical images analysis. We setup a method for the detection of clustered microcalcifications in digital mammograms, based on statistical techniques and multiresolution analysis by means of wavelet transform. The optimization of this scheme requires multiple runs on a set of 40 images, in order to obtain relevant statistics.We aim to evaluate how fluctuations of some parameters values of the detection method influence the performance of our system. A distributed genetic algorithm supervising this process allowed to improve of some percents previous results obtained after having “hand tuned” these parameters for a long time. At last, we have been able to find out parameters not influencing performance at all.
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© 2001 Springer-Verlag Berlin Heidelberg
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Bevilacqua, A., Campanini, R., Lanconelli, N. (2001). A Distributed Genetic Algorithm for Parameters Optimization to Detect Microcalcifications in Digital Mammograms. In: Boers, E.J.W. (eds) Applications of Evolutionary Computing. EvoWorkshops 2001. Lecture Notes in Computer Science, vol 2037. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45365-2_29
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DOI: https://doi.org/10.1007/3-540-45365-2_29
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