基于蚁群算法的乳腺癌细胞分类

2013 International Conference on Electrical Engineering and Software Applications Pub Date : 2013-03-21 DOI:10.1109/ICEESA.2013.6578445

Ahmed Nejmedine Machraoui, M. A. Cherni, M. Sayadi

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引用次数: 10

摘要

蚁群优化(蚁群优化)是一种生物启发技术，形式化为组合优化问题的元启发式。本文将ACO-Otsu分割方法应用于乳腺癌细胞的分类和检测，该方法以ACO算法为基础，以Otsu方法为适应度函数。随后，将该方法与Otsu的标准方法进行了比较。实验证明了这种概率搜索方法在这类问题中的性能。

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Ant Colony optimization algorithm for breast cancer cells classification

Ant colony optimization (ACO) is a bio-inspired technique formalized into a meta-heuristic for combinatorial optimization problems. In this work, the ACO-Otsu segmentation method, based on ACO algorithm and Otsu's method as a fitness function, is applied in classification and detection of breast cancer cells. Subsequently, this method is compared with the Otsu's standard method. The experiments show the performance of this probabilistic search approach in such type of problems.

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2013 International Conference on Electrical Engineering and Software Applications

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