Abstract
Automated analysis of molecular images has increasingly become an important research in computational life science. In this paper some new and efficient algorithms for detecting and analyzing cell phases of high-content screening are presented. The conceptual frameworks are based on the morphological features of cell nuclei. Furthermore, the novel detecting and analyzing strategies of feed-forward and feed-back of cell phases are proposed based on grey feature, cell shape, geometrical features and difference information of corresponding neighbor frames. Experiment results tested the efficiency of the new method.
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Yu, D., Pham, T.D., Zhou, X. (2008). Detection and Analysis of Cell Nuclear Phases. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2008. Lecture Notes in Computer Science(), vol 5177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85563-7_52
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DOI: https://doi.org/10.1007/978-3-540-85563-7_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85562-0
Online ISBN: 978-3-540-85563-7
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