VAR a New Metric of Cryo-electron Tomography Resolution

Hmida Rojbani, Atef Hamouda

Abstract

Motivate by reaching a better understanding of the biological cells, scientists use the Transmission Electron Microscope (TEM) to investigate their inner structures. The cryo-electron tomography (cryo-ET) offers the possibility to reconstruct 3D structure reconstruction of a cell slice, that by tilting it according different angles. The resolution limits is the biggest challenge in the cryo-ET. The two phases involved in increasing the resolution are the acquisition phase and the reconstruction phase. In this work, we focus in the last one, as the biologists treat the acquisition phase within the phase of acquisition itself. The resolution of reconstruction depends on many factors such as: (1) the noisy and missing information from the collected projections data, (2) the capacity of processing large data sets, (3) the parametrization of the contrast function of the microscope, (4) errors of the tilt angles used in projections. In this paper, we presented a new method to evaluate the resolution of a reconstruction algorithm. Then the proposed method is used to show the relation between errors of the tilt angles used in projection and the degradation of the resolution. The resolution evaluation tests are made with different reconstruction methods (analytic and algebraic) applied on synthetic and real data.

References

  1. Chen, J.-L., Li, L., Wang, L.-Y., Cai, A.-L., Xi, X.-Q., Zhang, H.-M., Li, J.-X., and Yan, B. (2015). Fast parallel algorithm for three-dimensional distance-driven model in iterative computed tomography reconstruction. Chinese Physics B, 24(2).
  2. Colliex, C. (1998). The Electron Microscopy. Presses Universitaires de France.
  3. Egerton, R., Li, P., and Malac, M. (2004). Radiation damage in the TEM and SEM. Micron, 35(6):399-409.
  4. Frank, J. (2006). Electron tomography: methods for threedimensional visualization of structures in the cell. Springer.
  5. Gilbert, P. (1972). Iterative methods for the threedimensional reconstruction of an object from projections. Journal of Theoretical Biology, 36(1):105-117.
  6. Gordon, R., Bender, R., and Herman, G. (1970). Algebraic Reconstruction Techniques (ART) for threedimensional electron microscopy and X-ray photography. J Theor Biol, 29(3):471-481.
  7. Joseph, P. (1982). An improved algorithm for reprojecting rays through pixel images. Medical Imaging, IEEE Transactions on, 1(3):192-196.
  8. Man, B. D. and Basu, S. (2004). Distance-driven projection and backprojection in three dimensions. Physics in Medicine and Biology, 49(11):2463.
  9. Midgley, P. and Weyland, M. (2003). 3d electron microscopy in the physical sciences: the development of z-contrast and { EFTEM} tomography. Ultramicroscopy, 96(34):413 - 431. Proceedings of the International Workshop on Strategies and Advances in Atomic Level Spectroscopy and Analysis.
  10. Momey, F., Denis, L., Mennessier, C., Thiebaut, E., Becker, J.-M., and Desbat, L. (2011). A new representation and projection model for tomography, based on separable b-splines. In Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2011 IEEE, pages 2602-2609.
  11. Momey, F., Thiebaut, E., Mennessier, C., Denis, L., and Becker, J.-M. (2014). Spline driven: high accuracy projectors for 3D tomographic reconstruction from few projections. submitted.
  12. O'Keefe, M. and Allard, L. (2004). A standard for sub-ngstrom metrology of resolution in aberrationcorrected transmission electron microscopes. Microscopy and Microanalysis, 10:1002-1003.
  13. Penczek, P. (2010). Chapter one - fundamentals of three-dimensional reconstruction from projections. In Grant, J., editor, Cryo-EM, Part B: 3-D Reconstruction, volume 482 of Methods in Enzymology, pages 1-33. Academic Press.
  14. Sorzano, C., de la Fraga, L., Clackdoyle, R., and Carazo, J. (2004). Normalizing projection images: a study of image normalizing procedures for single particle threedimensional electron microscopy. Ultramicroscopy, 101(24):129-138.
  15. Stagg, S., Lander, G., Pulokas, J., Fellmann, D., Cheng, A., Quispe, J., Mallick, S., Avila, R., Carragher, B., and C.S.Potter (2006). Automated cryo-em data acquisition and analysis of 284742 particles of groel. J Struct Biol, 155:470-481.
  16. Thevenaz, P., Blu, T., and Unser, M. (2000). Interpolation revisited [medical images application]. Medical Imaging, IEEE Transactions on, 19(7):739-758.
  17. Unser, M. (2000). Sampling-50 years after shannon. Proceedings of the IEEE, 88(4):569-587.
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Paper Citation


in Harvard Style

Rojbani H. and Hamouda A. (2016). VAR a New Metric of Cryo-electron Tomography Resolution . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 154-159. DOI: 10.5220/0005725801540159


in Bibtex Style

@conference{visapp16,
author={Hmida Rojbani and Atef Hamouda},
title={VAR a New Metric of Cryo-electron Tomography Resolution},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={154-159},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005725801540159},
isbn={978-989-758-175-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)
TI - VAR a New Metric of Cryo-electron Tomography Resolution
SN - 978-989-758-175-5
AU - Rojbani H.
AU - Hamouda A.
PY - 2016
SP - 154
EP - 159
DO - 10.5220/0005725801540159