Abstract
Heuristic algorithms are used for solving numerous modern research questions in biomedical informatics. We here summarize ongoing research done in this context and focus on approaches used in the analysis of microscopic images of biological samples. On the one hand we discuss the use of evolutionary algorithms for detecting and classifying structures in microscopy images, especially micro-patterns, cornea cells, and strands of myocardial muscles. On the other hand we show the use of data mining for characterizing the motions of molecules (for recognizing cells affected by paroxysmal nocturnal hemoglobinuria) and the progress of bone development.
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The correct cell shape classifications were in these tests defined by a tissue bank technician.
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Acknowledgments
The authors cordially thank their research partners at Red Cross Blood Transfusion Service of Upper Austria, Olympus Austria, Trauma Care Consult, and at the Research Centers Hagenberg, Wels, and Linz of the University of Applied Sciences Upper Austria for their ongoing support. The work described in this paper was done within the research projects MicroProt (sponsored by the University of Applied Sciences Upper Austria within its basic research programme) and NanoDetect (sponsored by the Austrian Research Promotion Agency within the FIT-IT programme).
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Winkler, S.M. et al. (2015). Identification and Classification of Objects and Motions in Microscopy Images of Biological Samples Using Heuristic Algorithms. In: Borowik, G., Chaczko, Z., Jacak, W., Łuba, T. (eds) Computational Intelligence and Efficiency in Engineering Systems. Studies in Computational Intelligence, vol 595. Springer, Cham. https://doi.org/10.1007/978-3-319-15720-7_8
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