Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-26T05:17:05.930Z Has data issue: false hasContentIssue false
  • English
  • Français

Improved Three-Dimensional (3D) Resolution of Electron Tomograms Using Robust Mathematical Data-Processing Techniques

Published online by Cambridge University Press:  16 November 2017

Toby Sanders  and
Ilke Arslan
Toby Sanders*
Affiliation:
School of Mathematical and Statistical Sciences, Arizona State University, PO Box 871804, Tempe, AZ 85287-1804, USA
Ilke Arslan
Affiliation:
Physical Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
*
*Corresponding author.[email protected]
Get access

Abstract

Electron tomography has become an essential tool for three-dimensional (3D) characterization of nanomaterials. In recent years, advances have been made in specimen preparation and mounting, acquisition geometries, and reconstruction algorithms. All of these components work together to optimize the resolution and clarity of an electron tomogram. However, one important component of the data-processing has received less attention: the 2D tilt series alignment. This is challenging for a number of reasons, namely because the nature of the data sets and the need to be coherently aligned over the full range of angles. An inaccurate alignment may be difficult to identify, yet can significantly limit the final 3D resolution. In this work, we present an improved center-of-mass alignment model that allows us to overcome discrepancies from unwanted objects that enter the imaging area throughout the tilt series. In particular, we develop an approach to overcome changes in the total mass upon rotation of the imaging area. We apply our approach to accurately recover small Pt nanoparticles embedded in a zeolite that may otherwise go undetected both in the 2D microscopy images and the 3D reconstruction. In addition to this, we highlight the particular effectiveness of the compressed sensing methods with this data set.

Keywords

electron tomographydata processingimage alignmentimage reconstructionL1 regularization
Type
Instrumentation and Software
Information
Microscopy and Microanalysis , Volume 23 , Issue 6 , December 2017 , pp. 1121 - 1129
Copyright
© Microscopy Society of America 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Batenburg, K.J., Bals, S., Sijbers, J., Kbel, C., Midgley, P.A., Hernandez, J.C., Kaiser, U., Encina, E.R., Coronado, E.A. & Van Tendeloo, G. (2009). 3d imaging of nanomaterials by discrete tomography. Ultramicroscopy 109(6), 730–740.Google Scholar
Binev, P., Dahmen, W., DeVore, R., Lamby, ., Savu, D. & Sharpley, R. (2012). Compressed sensing and electron microscopy. In Modeling Nanoscale Imaging in Electron Microscopy, pp. 73–126. New York, NY: Springer.CrossRefGoogle Scholar
Brandt, S., Heikkonen, J. & Engelhardt, P. (2001). Automatic alignment of transmission electron microscope tilt series without fiducial markers. J Struct Biol 136(3), 201–213.Google Scholar
Chen, Z., Jin, X., Li, L. & Wang, G. (2013). A limited-angle CT reconstruction method based on anisotropic TV minimization. Phys Med Biol 58(7), 2119.Google Scholar
Frank, J. (2006). Introduction: Principles of electron tomography. In Electron Tomography: Methods for Three-Dimensional Visualization of Structures in the Cell, pp. 1–15. New York, NY: Springer New York.Google Scholar
Goris, B., Roelandts, T., Batenburg, K.J., Heidari Mezerji, H. & Bals, S. (2013). Advanced reconstruction algorithms for electron tomography: From comparison to combination. Frontiers of Electron Microscopy in Materials Science. Ultramicroscopy 127, 40–47.Google Scholar
Hayashida, M. & Malac, M. (2016). Practical electron tomography guide: Recent progress and future opportunities. Micron 91, 49–74.Google Scholar
Houben, L. & Bar Sadan, M. (2011). Refinement procedure for the image alignment in high-resolution electron tomography. Ultramicroscopy 111(9), 1512–1520.CrossRefGoogle ScholarPubMed
Jones, S.D. & Härting, M. (2013). A new correlation based alignment technique for use in electron tomography. Ultramicroscopy 135, 56–63.Google Scholar
Kremer, J.R., Mastronarde, D.N. & McIntosh, J.R. (1996). Computer visualization of three-dimensional image data using IMOD. J Struct Biol 116(1), 71–76.Google Scholar
Leary, R., Saghi, Z., Midgley, P.A. & Holland, D.J. (2013). Compressed sensing electron tomography. Ultramicroscopy 131, 70–91.Google Scholar
Lučić, V., Förster, F. & Baumeister, W. (2005). Structural studies by electron tomography: from cells to molecules. Annu Rev Biochem 74, 833–865.Google Scholar
Masich, S., Östberg, T., Norlén, L., Shupliakov, O. & Daneholt, B. (2006). A procedure to deposit fiducial markers on vitreous cryo-sections for cellular tomography. J Struct Biol 156(3), 461–468.Google Scholar
Sanders, T. (2017). Matlab imaging algorithms: Image reconstruction, restoration, and alignment, with a focus in tomography. Available at http://www.toby-sanders.com/software, https://doi.org/10.13140/RG.2.2.33492.60801 (retrieved January 2017).Google Scholar
Sanders, T., Gelb, A., Platte, R.B., Arslan, I. & Landskron, K. (2017). Recovering fine details from under-resolved electron tomography data using higher order total variation $$\ell _{1} $$ regularization. Ultramicroscopy 174, 97–105.Google Scholar
Sanders, T., Prange, M., Akatay, C. & Binev, P. (2015). Physically motivated global alignment method for electron tomography. Adv Struct Chem Imaging 1(1), 1–11.Google Scholar
Saxton, W.O., Baumeister, W. & Hahn, M. (1984). Three-dimensional reconstruction of imperfect two-dimensional crystals. Ultramicroscopy 13(1–2), 57–70.Google Scholar
Scott, M.C., Chien-Chun, C., Mecklenburg, M., Zhu, C., Xu, R., Ercius, P., Dahmen, U., Regan, B.C. & Miao, J. (2012). Electron tomography at 2.4-angstrom resolution. Nature 483(7390), 444–447.Google Scholar
Sorzano, C.O.S., Messaoudi, C., Eibauer, M., Bilbao-Castro, J.R., Hegerl, R., Nickell, S., Marco, S. & Carazo, J.M. (2009). Marker-free image registration of electron tomography tilt-series. BMC Bioinformatics 10(1), 124.Google Scholar
Supplementary material: File

Sanders and Arslan supplementary material

Sanders and Arslan supplementary material 1

Download Sanders and Arslan supplementary material(File)
File 41.4 MB