Abstract
The computer vision domain has seen increasing attention in the design of automated tools for cellular biology researchers. In addition to quantitative analysis on whole populations of cells, identification of the cell division events is another important topic. In this research, a novel fully automated image-based cell-division-detection approach is proposed. Differing from most of the existing approaches that exploit training-based or image-based segmentation methods, the main idea of the proposed approach is detecting cell divisions using a motion based occlusion analysis process. Testing has been performed on different types of cellular datasets, including fluorescence images and phase-contrast data, and it has confirmed the effectiveness of the proposed method.
Thanks the National Biophotonics and Imaging Platform Ireland (NBIPI).
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Notes
- 1.
The rate of the correct automatically detected division number out of the total automatically detected number.
- 2.
The rate of the correct automatically detected division number out of the total manually annotated number.
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Acknowledgments
This research was supported by the National Biophotonics Imaging Platform (NBIP) Ireland funded under the Higher Education Authority PRTLI Cycle 4, co-funded by the Irish Government and the European Union—Investing in your future.
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Yu, S., Molloy, D. (2014). Optic Flow Based Occlusion Analysis for Cell Division Detection. In: Mat Sakim, H., Mustaffa, M. (eds) The 8th International Conference on Robotic, Vision, Signal Processing & Power Applications. Lecture Notes in Electrical Engineering, vol 291. Springer, Singapore. https://doi.org/10.1007/978-981-4585-42-2_55
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DOI: https://doi.org/10.1007/978-981-4585-42-2_55
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