Skip to main content

Segmentation of Cell Components Using Prior Knowledge

  • Chapter
  • 3262 Accesses

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.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   189.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   249.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

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.

    Article  Google Scholar 

  • 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.

    Google Scholar 

  • Bajaj, C., Yu, Z. and Auer, M. (2003). Volumetric feature extraction and visualization of tomographic molecular imaging. J. Struct. Biol. 144:132–143.

    Article  PubMed  Google Scholar 

  • Ballard, D. (1981). Generalizing the Hough transform to detect arbitrary shapes. Pattern Recogn. 13:111–122.

    Article  Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Article  PubMed  Google Scholar 

  • Buck, T., Hammel, U. and Schwefel, H. (1997). Evolutionary computation: comments on the history and current state. IEEE Trans. Evol. Comput. 1:3–17.

    Article  Google Scholar 

  • Chan, T. and Vese, L. (2001). Active contours without edges. IEEE Trans. Image Processing 10:266–277.

    Article  CAS  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Doucet, A., de Freitas, N. and Gordon, N. (2000). Sequential Monte Carlo Methods in Practice. Springer, Berlin.

    Google Scholar 

  • 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.

    Article  CAS  Google Scholar 

  • Elder, J. H., Krupnik, A. and Johnston, L.A. (2003). Contour grouping with prior models. IEEE Trans. Pattern Anal. Machine Intell. 25:661–674.

    Article  Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Article  PubMed  Google Scholar 

  • 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.

    Article  CAS  Google Scholar 

  • Frank, J. and Wagenknecht, T. (1984). Automatic selection of molecular images from electron micrographs. Ultramicroscopy 12:169–176.

    Article  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • He, W., Cowin, P. and Stokes, D. (2003). Untangling desmosome knots with electron tomography. Science 302:109–113.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • Howard, J. and Hyman, A. A. (2003) Dynamics and mechanics of the microtubule plus end. Nature. 422:753–758.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Google Scholar 

  • Jain, A. K., Zhong, Y. and Lakshmanan, S. (1996). Object matching using deformable templates. IEEE Trans. Pattern Anal. Machine Intell. 18:267–278.

    Article  Google Scholar 

  • Janosi, I. M., Chretien, D. and Flyvbjerg, H. (1998). Modeling elastic properties of microtubule tips and walls. Eur. Biophys. 27:501–513.

    Article  CAS  Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Article  PubMed  Google Scholar 

  • 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.

    Article  PubMed  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • Li, Y., Leith, A. and Frank, J. (1997). Tinkerbell—a tool for interactive segmentation of 3D data. J. Struct. Biol. 120:266–275.

    Article  PubMed  CAS  Google Scholar 

  • Lucic, V., Forster, F. and Baumeister, W. (2005). Structural studies by electron tomography. Annu. Rev. Biochem. 74:833–865.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Maiato, H., DeLuca, J., Salmon, E. D. and Earnshaw, W. C. (2004). The dynamic kinetochore microtubule interface. J. Cell Sci. 117:5461–5477.

    Article  PubMed  CAS  Google Scholar 

  • Marko, M. and Leith, A. (1996). Sterecon—three-dimensional reconstructions from stereoscopic contouring. J. Struct. Biol. 116:93–98.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Google Scholar 

  • McEwen, B. F. and Marko, M. (1999). Three-dimension transmission electron microscopy and its application to mitosis research. Methods Cell Biol 61:81–111.

    PubMed  CAS  Google Scholar 

  • 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.

    PubMed  CAS  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • Rasband, W. and Bright, D. (1995). NIH Image. Microbeam Anal. 4:20–33.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • Sethian, J. A. (1996). A marching level set method for monotonically advancing fronts. Proc Natl Acad. Sci. USA 93:1591–1595.

    Article  PubMed  CAS  Google Scholar 

  • Sethian, J. A. (1999). Level Set Methods and Fast Marching Methods, 2nd edn. Cambridge University Press, Cambridge.

    Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Article  PubMed  Google Scholar 

  • Staib, L. H. (1990). Parametrically Deformable Contour Models for Image Analysis, PhD Thesis, Yale University, New Haven, Connecticut.

    Google Scholar 

  • Staib, L.H. and Duncan, J. S. (1992). Boundary finding with parametrically deformable models. IEEE Trans. Pattern Anal. Machine Intell. 4:1061–1075.

    Article  Google Scholar 

  • 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.

    PubMed  CAS  Google Scholar 

  • Volkmann, N. (2002). A novel three dimensional variant of the watershed transform for segmentation of electron display maps. J. Struct. Biol. 138:123–129.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Google Scholar 

  • Wang, X., He, L. and Wee, W. G. (2004). Deformable contour method: a constrained optimization approach. Int. J. Comput. Vis. 59:87–108.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

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

Download citation

Publish with us

Policies and ethics