Abstract
We introduce a novel algorithm for actin filament segmentation in 2D TIRFM image sequences. This problem is difficult because actin filaments dynamically change shapes during their growth, and the TIRFM images are usually noisy. We ask a user to specify the two tips of a filament of interest in the first frame. We then model the segmentation problem in an image sequence as a temporal chain, where its states are tip locations; given candidate tip locations, actin filaments’ body points are inferred by a dynamic programming method, which adaptively generates candidate solutions. Combining candidate tip locations and their inferred body points, the temporal chain model is efficiently optimized using another dynamic programming method. Evaluation on noisy TIRFM image sequences demonstrates the accuracy and robustness of this approach.
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References
Amini, A.A., Weymouth, T.E., Jain, R.C.: Using dynamic programming for solving variational problems in vision. IEEE TPAMI 12, 855–867 (1990)
Cohen, L.D., Kimmel, R.: Global minimum for active contour models: A minimal path approach. IJCV 24, 57–78 (1997)
Felzenszwalb, F., Huttenlocher, P., Efficient, D.P.: matching of pictorial structures. In: Proc. CVPR, vol. 2, pp. 66–73 (2000)
Frangi, A.F., Niessen, W.J., Vincken, K.L., Viergever, M.A.: Multiscale vessel enhancement filtering. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 130–137. Springer, Heidelberg (1998)
Fujiwara, I., Takahashi, S., Tadakuma, H., Funatsu, T., Ishiwata, S.: Microscopic analysis of polymerization dynamics with individual actin filaments. Nat. Cell Biol. 4, 666–673 (2002)
Fujiwara, I., Vavylonis, D., Pollard, T.D.: Polymerization kinetics of ADP- and ADP-Pi-actin determined by fluorescence microscopy. Proc. Natl. Acad. Sci. USA 104, 8827–8832 (2007)
Hadjidemetriou, S., Toomre, D., Duncan, J.: Motion tracking of the outer tips of microtubules. Medical Image Analysis 12, 689–702 (2008)
Kong, K., Marcus, A., Giannakakou, P., Wang, M.: Using particle filter to track and model microtubule dynamics. In: Proc. ICIP, vol. 5, pp. 517–520 (2007)
Li, H., Shen, T., Smith, M., Fujiwara, I., Vavylonis, D., Huang, X.: Automated actin filament segmentation, tracking and tip elongation measurements based on open active contour models. In: Proc. ISBI (2009)
Li, H., Shen, T., Vavylonis, D., Huang, X.: Actin filament tracking based on particle filters and stretching open active contour models. In: Yang, G.-Z., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds.) MICCAI 2009. LNCS, vol. 5762, pp. 673–681. Springer, Heidelberg (2009)
Li, H., Shen, T., Vavylonis, D., Huang, X.: Actin filament segmentation using spatiotemporal active-surface and active-contour models. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010. LNCS, vol. 6361, pp. 86–94. Springer, Heidelberg (2010)
Saban, M., Altinok, A., Peck, A., Kenney, C., Feinstein, S., Wilson, L., Rose, K., Manjunath, B.: Automated tracking and modeling of microtubule dynamics. In: Proc. ISBI, vol. 1, pp. 1032–1035 (2006)
Sargin, M.E., Altinok, A., Kiris, E., Feinstein, S.C., Wilson, L., Rose, K., Manjunath, B.S.: Tracing microtubules in live cell images. In: Proc. ISBI (2007)
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 TMI 27, 789–804 (2008)
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Li, H., Shen, T., Huang, X. (2011). Actin Filament Segmentation Using Dynamic Programming. In: Székely, G., Hahn, H.K. (eds) Information Processing in Medical Imaging. IPMI 2011. Lecture Notes in Computer Science, vol 6801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22092-0_34
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DOI: https://doi.org/10.1007/978-3-642-22092-0_34
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