Advanced reconstruction algorithms for electron tomography: from comparison to combination.

In this work, the simultaneous iterative reconstruction technique (SIRT), the total variation minimization (TVM) reconstruction technique and the discrete algebraic reconstruction technique (DART) for electron tomography are compared and the advantages and disadvantages are discussed. Furthermore, we describe how the result of a three dimensional (3D) reconstruction based on TVM can provide objective information that is needed as the input for a DART reconstruction. This approach results in a tomographic reconstruction of which the segmentation is carried out in an objective manner.

[1]  Daniel Wolf,et al.  Towards automated electron holographic tomography for 3D mapping of electrostatic potentials. , 2010, Ultramicroscopy.

[2]  P. Midgley,et al.  Three-dimensional morphology of iron oxide nanoparticles with reactive concave surfaces. A compressed sensing-electron tomography (CS-ET) approach. , 2011, Nano letters.

[3]  B. Inkson,et al.  Spectroscopic electron tomography. , 2003, Ultramicroscopy.

[4]  S. Bals,et al.  A practical method to determine the effective resolution in incoherent experimental electron tomography. , 2011, Ultramicroscopy.

[5]  Kees Joost Batenburg,et al.  A semi-automatic algorithm for grey level estimation in tomography , 2011, Pattern Recognit. Lett..

[6]  Kees Joost Batenburg,et al.  Assisted spray pyrolysis production and characterisation of ZnO nanoparticles with narrow size distribution , 2010 .

[7]  David L Donoho,et al.  Compressed sensing , 2006, IEEE Transactions on Information Theory.

[8]  D. Donoho For most large underdetermined systems of equations, the minimal 𝓁1‐norm near‐solution approximates the sparsest near‐solution , 2006 .

[9]  J R Kremer,et al.  Computer visualization of three-dimensional image data using IMOD. , 1996, Journal of structural biology.

[10]  P. Midgley,et al.  Electron tomography and holography in materials science. , 2009, Nature materials.

[11]  K Joost Batenburg,et al.  Quantitative three-dimensional modeling of zeotile through discrete electron tomography. , 2009, Journal of the American Chemical Society.

[12]  E. Candès,et al.  Stable signal recovery from incomplete and inaccurate measurements , 2005, math/0503066.

[13]  A. Verkleij,et al.  Three-Dimensional Transmission Electron Microscopy: A Novel Imaging and Characterization Technique with Nanometer Scale Resolution for Materials Science , 2000 .

[14]  E.J. Candes,et al.  An Introduction To Compressive Sampling , 2008, IEEE Signal Processing Magazine.

[15]  P. Midgley,et al.  High-Resolution Three-Dimensional Imaging of Dislocations , 2006, Science.

[16]  S Bals,et al.  Exploring different inelastic projection mechanisms for electron tomography. , 2011, Ultramicroscopy.

[17]  Kees Joost Batenburg,et al.  A 3-dimensional discrete tomography approach for superresolution micro-CT images:application to foams , 2010 .

[18]  P. Gilbert Iterative methods for the three-dimensional reconstruction of an object from projections. , 1972, Journal of theoretical biology.

[19]  S Bals,et al.  3D Imaging of Nanomaterials by Discrete Tomography , 2006, Microscopy and Microanalysis.

[20]  Kees Joost Batenburg,et al.  Electron tomography based on a total variation minimization reconstruction technique , 2012 .

[21]  S. Bals,et al.  A New Approach for Electron Tomography: Annular Dark‐Field Transmission Electron Microscopy , 2006 .

[22]  D. Van Dyck,et al.  Correction of non-linear thickness effects in HAADF STEM electron tomography , 2012 .

[23]  Jan Sijbers,et al.  Quantitative Three-Dimensional Reconstruction of Catalyst Particles for Bamboo-like Carbon Nanotubes , 2007 .

[24]  P. Midgley,et al.  3D electron microscopy in the physical sciences: the development of Z-contrast and EFTEM tomography. , 2003, Ultramicroscopy.

[25]  Kees Joost Batenburg,et al.  DART: A Practical Reconstruction Algorithm for Discrete Tomography , 2011, IEEE Transactions on Image Processing.