Abstract
Microtubules are essential part of the cell structure. Cryo-Electron Microscopy (Cryo-EM) is employed to collect visual images of the microtubules in atomic resolution. However the electron microscopic images suffer from excessive white noise and incoherent cell structures. The Signal-to-Noise Ratio (SNR) of the images is rather low (less than 0.1). Automated segmentation of the microtubule region from high-noise electron micrographs is of significance, otherwise scientists have to manually locate and extract microtubules from a large amount of noisy data. Here, we proposed a new composite algorithm based on Chan-Vese (CV) model, which consists of three steps: (1) Remove the contaminant area in the micrograph, where the Otsu algorithm and the morphological closing operation are utilized. (2) Enhance the microtubules image by using improved diffusion filtering algorithm. (3) Use the adapted CV model to segment the microtubules. Our test results show that the new algorithm is quite effective for segmentation and extraction of microtubules from highly noisy images, with few errors and less time-cost.
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References
Li, H., DeRosier, D.J., Nicholson, W.V., Nogales, E., Downing, K.H.: Microtubule Structure at A Resolution. Structure 10, 1317–1328 (2002)
Shariff, A.: Learning Generative Models of Microtubule Distributions, CMUCB12101, March 2012
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: active contour models. International Journal of Computer Vision 1(4), 321–331 (1988)
Zovko, S., Abrahams, J.P., Koster, A.J., Galjart, N., Mommaas, A.M.: Microtubule plus-end conformations and dynamics in the periphery of interphase mouse fibroblasts. Molecular Biology of the Cell 19, 3138–3146 (2008)
Mumford, D., Shah, J.: Optimal approximation by piecewise smooth functions and associated variational problems. Commun. Pure Appl. Math. 42, 577–685 (1989)
Chan, T., Vese, L.: Active Contours without Edges. IEEE Trallsactions on Image Processing (2001)
Osher, S., Sethian, J.A.: Fronts propagating with curvature dependent speed: algorithms based on the Hamilton-Jacobi formulation. J. Comput. P., 12–49 (1998)
Gonzalez, R., Wood, R.: Digital Image Processing. Addison-Wesley (1992)
Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell., 679–698, October 1986
Perona, P., Malik, J.: Scale-space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 629–639, December 1990
Frangakis, A.S., Hegerl, R.: Noise Reduction in Electron Tomographic Reconstructions Using Nonlinear Anisotropic Diffusion. Journal of Structural Biology 135(3), 239–250 (2001). ISSN: 1047-8477
Jiang, M., Ji, Q., McEwen, B.F.: Automated extraction of fine features of kineto-chore microtubules and plus-ends from electron tomography volume. IEEE Transactions on Image Processing 15, 2035–2048 (2006)
Wen, Y., Cai, H., Deng, L.: Detecting microtubules in high noise Cryo-EM micrograph. In: 2012 5th International Conference on BioMedical Engineering and Informatics (BM- EI2012), May 2012
Plaisier, J.R., Jiang, L., Abrahams, J.P.: Cyclops: New modular software suite for cryo-EM. Journal of Structural Biology 157(1), 19–27 (2007). ISSN: 1047-8477
Liu, C., Shi, Z.: Anisotropic Diffusion-Median filter for Infrared Image. Journal of Projectiles, Rockets, Missiles and Guidance 26, 198–200 (2006). ISSN: 1673-9728
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Yue, G., Jiang, L., Liu, C., Yang, G., Ai, J., Chen, X. (2016). Automated Segmentation of Microtubules in Cryo-EM Images with Excessive White Noise. In: Kim, K., Joukov, N. (eds) Information Science and Applications (ICISA) 2016. Lecture Notes in Electrical Engineering, vol 376. Springer, Singapore. https://doi.org/10.1007/978-981-10-0557-2_34
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DOI: https://doi.org/10.1007/978-981-10-0557-2_34
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