A Distributed Genetic Algorithm for Parameters Optimization to Detect Microcalcifications in Digital Mammograms
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.
KeywordsGenetic Algorithm Gray Level Multiresolution Analysis True Signal Wall Clock Time
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- 1.Bazzani, A., Bevilacqua, A., Bollini, D., Brancaccio, R., Campanini, R., Lanconelli, N., Romani, D.: System for automatic detection of clustered microcalcifications in digital mammograms. Int. J. Mod. Phys. C 11 (2000) 901–912Google Scholar
- 3.Dokur, Z., Olmez, T., Yazgan, E.: Classification of MR and CT images using genetic algorithms. Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 20 (1998)Google Scholar
- 5.Yoshida, H., Anastasio, M., Nagel, R., Nishikawa, R.M., Doi, K.: Computer-Aided Diagnosis for Detection of Clustered Microcalcifications in Mammograms: Automated Optimization of Performance Based on Genetic Algorithm. Proceedings of IWCAD 1997, (Elsevier Science B.V., The Netherlands) (1997)Google Scholar
- 7.Cantú-Paz, E.: A survey of Parallel Genetic Algorithms. Report No. 97003, (Univ. of Illinois, Urbana, 1997) (1997)Google Scholar
- 8.Bevilacqua, A.: A dynamic load balancing method on a heterogeneous cluster of workstations. Informat. 23 (1999) 49–56Google Scholar