Abstract
The investigate of the cell image data are able to obtain the correlation between many diseases and abnormal cell behavior by tracking their trajectories. In this paper, a novel Ant Colony Algorithm for cell tracking based on Gaussian cloud model is proposed. In order to speed up the search and improve the accuracy, pheromone prediction strategy based on Gaussian cloud model is utilized. Experiment results show the effectiveness of our approach and it is competitive with some of the existing methods presented in recent literature.
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Acknowledgments
This work is supported by national natural science foundation of China (No. 61876024 and No. 61673075), and partly by the project of talent peak of six industries (2017-DZXX-001), Jiangsu Laboratory of Lake Environment Remote Sensing Technologies Open Project Fund (JSLERS-2017-006) and The Science and Technology Development Plan Project of Chang Shu (CR0201711).
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Lu, M., Xu, B., Dong, X., Zhu, P., Shi, J. (2019). Ant Colony Algorithm for Cell Tracking Based on Gaussian Cloud Model. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2019. Lecture Notes in Computer Science(), vol 11655. Springer, Cham. https://doi.org/10.1007/978-3-030-26369-0_19
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DOI: https://doi.org/10.1007/978-3-030-26369-0_19
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