Abstract
Electron tomography is a method for determining 3D structure by electron microscopy, using multiple tilt views of the specimen (Lucic et al., 2005; McEwen and Marko 2001; McIntosh et al., 2005). Since electron tomography does not employ averaging or require the presence of symmetry, it can be used in biological applications to image single copies of subcellular components in situ. When specimen preparation is optimized by use of rapid freezing, and imaged either directly in the frozen-hydrated state, or after freeze substitution and plastic embedding, electron tomography provides a relatively high-resolution view of biological structure in a native, or near-native, cellular context.
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References
Aylward, S. and Bullitt, E. (2002). Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction. IEEE Trans. Med. Imag. 21:61–75.
Babu, S., Liao, P. C., Shin, M. C. and Tsap, L. V. (2004). Towards recovery of 3d chromosome structure, IEEE Workshop on Articulated and Nonrigid Motion ANM2004 (in conjunction with CVPR’04). Proceedings on a CD-ROM, Washington, DC, June 2004.
Bajaj, C., Yu, Z. and Auer, M. (2003). Volumetric feature extraction and visualization of tomographic molecular imaging. J. Struct. Biol. 144:132–143.
Ballard, D. (1981). Generalizing the Hough transform to detect arbitrary shapes. Pattern Recogn. 13:111–122.
Bartesaghi, A., Sapiro, G., Lee, S., Lefman, J., Wahl, S., Subramaniam, S. and Orenstein, J. (2004). A new approach for 3D segmentation of cellular tomograms obtained using three-dimensional electron microscopy. In Proceedings of the 2nd IEEE International Symposium on Biomedical Imaging, pp. 5–8.
Behiels, G., Vandermeulen, D., Maes, F., Suetens, P. and Dewaele, P. (1999). Active shape model-based segmentation of digital X-ray images. In Lecture Notes in Computer Science. Springer-Verlag, Berlin, 1679, MICCAI’ 99, pp. 128–137.
Böhm, J., Frangakis, A. S., Hegerl, R., Nickell, S., Typke, D. and Baumeister, W. (2000). Toward detecting and identifying macromolecules in a cellular context: template matching applied to electron tomograms. Proc. Natl Acad. Sci. USA 97:14245–14250.
Buck, T., Hammel, U. and Schwefel, H. (1997). Evolutionary computation: comments on the history and current state. IEEE Trans. Evol. Comput. 1:3–17.
Chan, T. and Vese, L. (2001). Active contours without edges. IEEE Trans. Image Processing 10:266–277.
Cootes, T. F., Taylor, C. J. and Cooper, D. H. (1995). Active shape models—their training and application. Comput. Vis. Image Understand. 61:38–59.
Doucet, A., de Freitas, N. and Gordon, N. (2000). Sequential Monte Carlo Methods in Practice. Springer, Berlin.
Duta, N. and Sonka, M. (1998). Segmentation and interpretation of MR brain images: an improved active shape model. IEEE Trans. Med. Imag. 17:1049–1067.
Elder, J. H., Krupnik, A. and Johnston, L.A. (2003). Contour grouping with prior models. IEEE Trans. Pattern Anal. Machine Intell. 25:661–674.
Elder, J. H. and Zucker, S.W. (1996). Computing contour closure. Proceeding of the 4th European Conference on Computer Vision 1. Cambridge, UK, pp. 399–412.
Frangakis, A. S., Böhm, J., Forster, F., Nickell, S., Nicastro, D., Typke, D., Hegerl, R. and Baumeister, W. (2002). Identification of macromolecular complexes in cryoelectron tomograms of phantom cells. Proc. Natl Acad. Sci. USA 99:14153–14148.
Frangakis, A. S. and Hegerl, R. (2002). Segmentation of two and three dimensional data from electron microscopy using eigenvector analysis. J. Struct. Biol. 138:105–113.
Frangi, A., Niessen, W., Hoogeveen, R., van Walsum, T and Viergever, M. (1999). Model-based quantitation of 3D magnetic resonance angiographic images. IEEE Trans. Med. Imag. 18:946–956.
Frank, J. and Wagenknecht, T. (1984). Automatic selection of molecular images from electron micrographs. Ultramicroscopy 12:169–176.
Frank, J., Radermacher, M., Penczek, P., Zhu, J., Li, Y., Ladjadj, M. and Leith, A. (1996). SPIDER and WEB: processing and visualization of images ion 3D electron microscopy and related fields. J. Struct. Biol. 116:190–199.
Harlow, M. L., Ress, D., Stoschek, A., Marshall, M. and McMahan, U. J. (2001). The architecture of active zone material at the frog’s neuromuscular junction. Nature 409: 479–484.
He, W., Cowin, P. and Stokes, D. (2003). Untangling desmosome knots with electron tomography. Science 302:109–113.
Hessler, D., Young, S. J., Carragher, B. O., Martone, M. E., Lamont, S., Whittaker, M., Milligan, R. A., Masliah, E., Henshaw, J. E. and Ellisman, M.H. (1992). Programs for visualization in three-dimensional microscopy. Neuroimage 1:55–68.
Hessler, D., Young, S. J. and Ellisman M. H. (1996). A flexible environment for the visualization of three-dimensional biological structures. J. Struct. Biol. 116:113–119.
Howard, J. and Hyman, A. A. (2003) Dynamics and mechanics of the microtubule plus end. Nature. 422:753–758.
Jacob, M., Blu, T. and Unse, M. (2002). 3-D reconstruction of DNA filaments from stereo cryoelectron micrographs. In Proceedings of 2002 IEEE International Symposium on Biomedical Imaging, pp. 597–600.
Jain, A. K., Zhong, Y. and Lakshmanan, S. (1996). Object matching using deformable templates. IEEE Trans. Pattern Anal. Machine Intell. 18:267–278.
Janosi, I. M., Chretien, D. and Flyvbjerg, H. (1998). Modeling elastic properties of microtubule tips and walls. Eur. Biophys. 27:501–513.
Jiang, M., Ji, Q. and McEwen, B. F. (2004a). Model-based automated segmentation of kinetochore microtubule from electron tomography. In 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 1656–1659.
Jiang, M., Ji, Q. and McEwen, B. F. (2004b). Enhancement of microtubules in EM tomography. Proceedings of the 2004 IEEE International Symposium on Biomedical Imaging, Arlington, VA, April 15–18, 2004, pp. 1123–1126.
Jiang, M., Ji, Q. and McEwen, B. F. (2005). Automated extraction of microtubules and their plus-ends. Seventh IEEE Workshop on Applications of Computer Vision Proceedings, Breckenridge, Colorado, January 5–7, 2005, pp. 336–341.
Jiang, M., Ji, Q. and McEwen, B. F. (2006a). Model-based automated extraction of microtubules from electron tomography volume. IEEE Transactions on Information Technology in Biomedicine, Vol. 10, No. 3, 2006, pp. 608–617.
Jiang, M., Ji, Q. and McEwen, B. F. (2006b). Automated extraction of fine-features of kinetochore microtubules and plus-ends from electron tomography volume. IEEE Transactions on Image Processing, Vol. 15, No. 7, 2006, pp. 2035–2048.
Kremer, J. R., Mastronarde, D.N. and McIntosh, J. R. (1996). Computer visualization of threedimensional image data using IMOD. J. Struct. Biol. 116:71–76.
Li, Y., Leith, A. and Frank, J. (1997). Tinkerbell—a tool for interactive segmentation of 3D data. J. Struct. Biol. 120:266–275.
Lucic, V., Forster, F. and Baumeister, W. (2005). Structural studies by electron tomography. Annu. Rev. Biochem. 74:833–865.
Mahamud, S., Williams, L.R., Thornber, K. K. and Xu, K. (2003). Segmentation of multiple salient closed contours from real images. IEEE Trans. Pattern Anal. Machine Intell. 25:433–444.
Maiato, H., DeLuca, J., Salmon, E. D. and Earnshaw, W. C. (2004). The dynamic kinetochore microtubule interface. J. Cell Sci. 117:5461–5477.
Marko, M. and Leith, A. (1996). Sterecon—three-dimensional reconstructions from stereoscopic contouring. J. Struct. Biol. 116:93–98.
Marsh, B. J., Mastronarde, D. N., Buttle, K. F., Howell, K. E. and McIntosh, J. R. (2001). Organellar relationships in the Golgi region of the pancreatic beta cell line, HIT-T15, visualized by high resolution electron tomography. Proc. Natl Acad. Sci. USA 98:2399–2406.
McEwen, B. F., Barnard, R. M., Portuese, T. and Hsieh, C. E. (2002). Using electron tomography to determine the interaction between mammalian kinetochores and microtubules. Proc. Int. Congr. Electron Microsc. 15:179.
McEwen, B. F. and Marko, M. (1999). Three-dimension transmission electron microscopy and its application to mitosis research. Methods Cell Biol 61:81–111.
McEwen, B. F. and Marko, M. (2001). The emergence of electron tomography as an important tool for investigating cellular ultrastructure. J. Histochem. Cytochem. 49:553–563.
McIntosh, R., Nicastro, D. and Mastronarde, D. (2005). New views of cells in 3D: an introduction to electron tomography. Trends Cell Biol. 15:43–51.
Monga, O., Benayoun, S. and Faugeras, O. (1992). Using partial derivatives of 3D images to extract typical surface features. In Proceedings of The Third Annual Conference of AI, Simulation, and Planning in Highway Autonomy Systems, pp. 225–236.
O’Toole, E., McDonald, K., Mantler, J., McIntosh, J.R., Hyman, A. and Muller-Reichert, T. (2003). Morphologically distinct microtubule ends in the mitotic centrosome of Caenorhabditis elegans. J. Cell Biol. 163:451–456.
Perez, P., Blake, A. and Gangnet, M. (2001). Jetstream: probabilistic contour extraction with particles. In Proceedings of the Eighth IEEE International Conference on Computer Vision Vol. 2, pp. 524–531.
Perkins, G., Renken, C., Martone, M. E., Young, S. J., Ellisman, M. and Frey, T. (1997). Electron tomography of neuronal mitochondria: three-dimensional structure and organization of cristae and membrane contacts. J. Struct. Biol. 119:260–272.
Rasband, W. and Bright, D. (1995). NIH Image. Microbeam Anal. 4:20–33.
Ray, N., Acton, S. T. and Ley, K. (2002). Tracking leukocytes in vivo with shape and size constrained active contours. IEEE Trans. Med. Imag. 21:1222–1235.
Renken, C., Siragusa, G., Perkins, G., Washington, L., Nulton, J., Salamon, P. and Frey, T. (2002). A thermodynamic model describing the nature of the crista junction: a structural motif in the the mitochondrion. J. Struct. Biol. 138: 137–144.
Rogers, M., Graham, J. and Malik, R. A. (2000). Exploiting weak shape constraints to segment capillary images in microangiopathy. In Proceedings of Medical Image Computing and Computer-Assisted Intervention, pp. 717–726.
Samson, C., Blanc-Feraud, L., Aubert, G. and Zerubia, J. (2000). A level set model for image classification. Int. J. Comput. Vis. 40:187–197.
Scorrano, L., Ashiya, M., Buttle, K., Oakes, S.A., Mannella, C. A. and Korsmeyer, S. J. (2002). A distinct pathway remodels mitochondrial cristae and mobilizes cytochrome c during apoptosis. Dev. Cell 2:55–67.
Segui-Simarro, J. M., Austin, J. R., White, E.A. and Staehelin, A. (2004). Electron tomographic analysis of somatic cell plate formation in meristematic cells of Arabidopsis preserved by high-pressure freezing. Plant Cell 16:836–856.
Sethian, J. A. (1996). A marching level set method for monotonically advancing fronts. Proc Natl Acad. Sci. USA 93:1591–1595.
Sethian, J. A. (1999). Level Set Methods and Fast Marching Methods, 2nd edn. Cambridge University Press, Cambridge.
Smyth, P. P., Taylor, J. and Adams, J. E. (1996). Automatic measurement of vertebral shape using active shape models. In Proceedings of the British Machine Vision Conference, pp. 705–714.
Sosinsky, G. E., Deerinck, T. J., Greco, R., Buitenhuys, C. H., Bartol, T. M. and Ellisman, M. H. (2005). Development of a model for microphysiological simulations: small nodes of Ranvier from peripheral nerves of mice reconstructed by electron tomography. Neuroinformatics 3:133–162.
Staib, L. H. (1990). Parametrically Deformable Contour Models for Image Analysis, PhD Thesis, Yale University, New Haven, Connecticut.
Staib, L.H. and Duncan, J. S. (1992). Boundary finding with parametrically deformable models. IEEE Trans. Pattern Anal. Machine Intell. 4:1061–1075.
Tregear, R.T., Reedy, M.C., Goldman, Y. E., Taylor, K.A., Winkler, H., Armstrong, C. F., Sasaki, H., Lucaveche, C. and Reedy, M. K. (2004). Cross-bridge number, position, and angle in target zones of cryofixed isometrically active insect flight muscle. Biophys. J. 86: 3009–3019.
Volkmann, N. (2002). A novel three dimensional variant of the watershed transform for segmentation of electron display maps. J. Struct. Biol. 138:123–129.
Wang, S., Kubota, T. and Siskind, J. M. (2003). Salient boundary detection using ratio contour. In Neural Information Processing Systems Conference (NIPS). Vancouver, Canada, pp. 1571–1578.
Wang, X., He, L. and Wee, W. G. (2004). Deformable contour method: a constrained optimization approach. Int. J. Comput. Vis. 59:87–108.
Worring, M., Smeulders, A. W. M., Staib, L.H. and Duncan, J. S. (1996). Parameterized feasible boundaries in gradient vector fields. Comput Vis. Image Understand. 63:135–144.
Yu, T. P.Y., Stoschek, A. and Donoho, D. L. (1996). Translation-and direction-invariant denoising of 2D and 3D images: experience and algorithms. In Proceedings of the SPIE, Wavelet Applications in Signal and Image Processing IV:2825, pp. 608–619.
Yu, Z. and Bajaj, C. (2004). Picking circular and rectangular particles based on geometric feature detection in electron micrographs. J. Struct. Biol. 145:168–180.
Zhu, Y., Carragher, B., Mouche, F. and Potter, C. S. (2003). Automatic particle detection through efficient Hough transforms. IEEE Trans. Med. Imaging, 22:1053–1062.
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Jiang, M., Ji, Q., Wang, X., McEwen, B.F. (2007). Segmentation of Cell Components Using Prior Knowledge. In: Frank, J. (eds) Electron Tomography. Springer, New York, NY. https://doi.org/10.1007/978-0-387-69008-7_14
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DOI: https://doi.org/10.1007/978-0-387-69008-7_14
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