Abstract
Tracking the motion of Myxococcus xanthus is a crucial step for fundamental bacteria studies. Large number of bacterial cells involved, limited image resolution, and various cell behaviors (e.g., division) make tracking a highly challenging problem. A common strategy is to segment the cells first and associate detected cells into moving trajectories. However, known detection association algorithms that run in polynomial time are either ineffective to deal with particular cell behaviors or sensitive to segmentation errors. In this paper, we propose a polynomial time hierarchical approach for associating segmented cells, using a new Earth Mover’s Distance (EMD) based matching model. Our method is able to track cell motion when cells may divide, leave/enter the image window, and the segmentation results may incur false alarm, detection lost, and falsely merged/split detections. We demonstrate it on tracking M. xanthus. Applied to error-prone segmented cells, our algorithm exhibits higher track purity and produces more complete trajectories, comparing to several state-of-the-art detection association algorithms.
This work was supported in part by NSF under Grant CCF-1217906 and by NIH under Grants 1R01-GM095959 and 1R01-GM100470.
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References
Bise, R., Yin, Z., Kanade, T.: Reliable cell tracking by global data association. In: ISBI, pp. 1004–1010 (2011)
Hillier, F., Lieberman, G.: Introduction to Operations Research, 8th edn. McGraw-Hill (2010)
Kachouie, N., Fieguth, P.: Extended-Hungarian-JPDA: Exact single-frame stem cell tracking. IEEE Trans. on Biomedical Eng. 54(11), 2011–2019 (2007)
Kaiser, D.: Social gliding is correlated with the presence of pili in Myxococcus xanthus. Proc. of the Nat. Acad. of Sci. 76(11), 5952–5956 (1979)
Kremer, H., Gunnemann, S., Wollwage, S., Seidl, T.: Nesting the earth mover’s distance for effective cluster tracing. In: ICSSDM (2013)
Li, K., Chen, M., Kanade, T.: Cell population tracking and lineage construction with spatiotemporal context. In: Ayache, N., Ourselin, S., Maeder, A. (eds.) MICCAI 2007, Part II. LNCS, vol. 4792, pp. 295–302. Springer, Heidelberg (2007)
Liu, X., Harvey, C.W., Wang, H., Alber, M.S., Chen, D.Z.: Detecting and tracking motion of Myxococcus xanthus bacteria in swarms. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds.) MICCAI 2012, Part I. LNCS, vol. 7510, pp. 373–380. Springer, Heidelberg (2012)
Padfield, D., Rittscher, J., Roysam, B.: Coupled minimum-cost flow cell tracking for high-throughput quantitative analysis. Med. Image Anal. 15(4), 650–668 (2011)
Rubner, Y., Tomasi, C., Guibas, L.: A metric for distributions with applications to image databases. In: ICCV, pp. 59–66 (1998)
Schiegg, M., Hanslovsky, P., Kausler, B.X., Hufnagel, L., Hamprecht, F.: Conservation tracking. In: ICCV, pp. 2928–2935 (2013)
Wu, Y., Kaiser, D., Jiang, Y., Alber, M.: Periodic reversal of direction allows myxobacteria to swarm. Proc. of the Nat. Acad. of Sci. 106(4), 1222–1227 (2009)
Xie, J., Khan, S., Shah, M.: Automatic tracking of Escherichia coli bacteria. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part I. LNCS, vol. 5241, pp. 824–832. Springer, Heidelberg (2008)
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Chen, J., Harvey, C.W., Alber, M.S., Chen, D.Z. (2014). A Matching Model Based on Earth Mover’s Distance for Tracking Myxococcus Xanthus. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014. MICCAI 2014. Lecture Notes in Computer Science, vol 8674. Springer, Cham. https://doi.org/10.1007/978-3-319-10470-6_15
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DOI: https://doi.org/10.1007/978-3-319-10470-6_15
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