Abstract
Multi-cell tracking is an important problem in studies of dynamic cell cycle behaviors. This paper models a novel multi-tasking ant system that jointly estimates the number of cells and their individual states in cell image sequences. Our ant system adopts an interactive mode with cooperation and competition. In simulations of real cell image sequences, the multi-tasking ant system integrated with interactive mode yielded better tracking results . Furthermore, the results suggest that our algorithm can automatically and accurately track numerous cells in various scenarios, and is competitive with state-of-the-art multi-cell tracking methods.
Keywords
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Dufour, A., Shinin, V., Tajbakhsh, S., Guillen-Aghion, N., Olivo-Marin, J.C., Zimmer, C.: Segmenting and tracking fluorescent cells in dynamic 3-D microscopy with coupled active surfaces. IEEE Transactions on Image Processing 14, 1396–1410 (2005)
Nguyen, N.H., Keller, S., Norris, E., Huynh, T.T., Clemens, M.G., Shin, M.C.: Tracking Colliding Cells In Vivo Microscopy. IEEE Transactions on Biomedical Engineering 58, 2391–2400 (2011)
Bandi, S.R., Varadharajan, A., Masthan, M.: Performance evaluation of various foreground extraction algorithms for object detection in visual surveillance. Comput. Eng. Res. 2, 1339–1443 (2012)
Hartigan, J.A., Wong, M.A.: Algorithm AS 136: A K-Means Clustering Algorithm. Journal of the Royal Statistical Society. Series C (Applied Statistics) 28, 100–108 (1979)
Smal, I., Draegestein, K., Galjart, N., Niessen, W., Meijering, E.: Particle Filtering for Multiple Object Tracking in Dynamic Fluorescence Microscopy Images: Application to Microtubule Growth Analysis. IEEE Transactions on Medical Imaging 27, 789–804 (2008)
Hoseinnezhad, R., Vo, B.-N., Vo, B.-T., Suter, D.: Visual tracking of numerous targets via multi-Bernoulli filtering of image data. Pattern Recognition 45, 3625–3635 (2012)
Juang, R.R., Levchenko, A., Burlina, P.: Tracking cell motion using GM-PHD. In: IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009, pp. 1154–1157 (2009)
Lu, M., Xu, B., Sheng, A.: Cell automatic tracking technique with particle filter. In: Tan, Y., Shi, Y., Ji, Z. (eds.) ICSI 2012, Part II. LNCS, vol. 7332, pp. 589–595. Springer, Heidelberg (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Lu, M., Xu, B., Zhu, P., Shi, J. (2014). A Novel Ant System with Multiple Tasks for Spatially Adjacent Cell State Estimate. In: Tan, Y., Shi, Y., Coello, C.A.C. (eds) Advances in Swarm Intelligence. ICSI 2014. Lecture Notes in Computer Science, vol 8795. Springer, Cham. https://doi.org/10.1007/978-3-319-11897-0_29
Download citation
DOI: https://doi.org/10.1007/978-3-319-11897-0_29
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11896-3
Online ISBN: 978-3-319-11897-0
eBook Packages: Computer ScienceComputer Science (R0)