Rapid alignment of nanotomography data using joint iterative reconstruction and reprojection

As x-ray and electron tomography is pushed further into the nanoscale, the limitations of rotation stages become more apparent, leading to challenges in the alignment of the acquired projection images. Here we present an approach for rapid post-acquisition alignment of these projections to obtain high quality three-dimensional images. Our approach is based on a joint estimation of alignment errors, and the object, using an iterative refinement procedure. With simulated data where we know the alignment error of each projection image, our approach shows a residual alignment error that is a factor of a thousand smaller, and it reaches the same error level in the reconstructed image in less than half the number of iterations. We then show its application to experimental data in x-ray and electron nanotomography.

[1]  D. DeRosier,et al.  The reconstruction of a three-dimensional structure from projections and its application to electron microscopy , 1970, Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences.

[2]  G. Herman,et al.  Algebraic reconstruction techniques (ART) for three-dimensional electron microscopy and x-ray photography. , 1970, Journal of theoretical biology.

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

[4]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[5]  R. Guckenberger Determination of a common origin in the micrographs of tilt series in three-dimensional electron microscopy , 1982 .

[6]  L. Shepp,et al.  Maximum Likelihood Reconstruction for Emission Tomography , 1983, IEEE Transactions on Medical Imaging.

[7]  E. P. Tinnel,et al.  Electron microscope tomography: transcription in three dimensions. , 1983, Science.

[8]  W. O. Saxton,et al.  Three-dimensional reconstruction of imperfect two-dimensional crystals. , 1984, Ultramicroscopy.

[9]  J. D. O'Sullivan,et al.  A Fast Sinc Function Gridding Algorithm for Fourier Inversion in Computer Tomography , 1985, IEEE Transactions on Medical Imaging.

[10]  Stephen J. Pennycook,et al.  Z-contrast stem for materials science , 1989 .

[11]  J. Dengler A multi-resolution approach to the 3D reconstruction from an electron microscope tilt series solving the alignment problem without gold particles , 1989 .

[12]  Z Q Jing,et al.  Alignment of tomographic projections using an incomplete set of fiducial markers. , 1991, Ultramicroscopy.

[13]  W. Baumeister,et al.  Towards automatic electron tomography. II. Implementation of autofocus and low-dose procedures , 1993 .

[14]  J Frank,et al.  A marker-free alignment method for electron tomography. , 1995, Ultramicroscopy.

[15]  W. Landis,et al.  Alignment of electron tomographic series by correlation without the use of gold particles. , 1996, Ultramicroscopy.

[16]  Lisa Axe,et al.  Developments in synchrotron x-ray computed microtomography at the National Synchrotron Light Source , 1999, Optics & Photonics.

[17]  D Ress,et al.  Automatic acquisition of fiducial markers and alignment of images in tilt series for electron tomography. , 1999, Journal of electron microscopy.

[18]  B. Niemann,et al.  Computed tomography of cryogenic biological specimens based on X-ray microscopic images. , 2000, Ultramicroscopy.

[19]  Wang,et al.  Soft X‐ray microscopy with a cryo scanning transmission X‐ray microscope: II. Tomography , 2000, Journal of microscopy.

[20]  J Heikkonen,et al.  Multiphase method for automatic alignment of transmission electron microscope images using markers. , 2001, Journal of structural biology.

[21]  J Heikkonen,et al.  Automatic alignment of transmission electron microscope tilt series without fiducial markers. , 2001, Journal of structural biology.

[22]  Stefan Vogt,et al.  MAPS : A set of software tools for analysis and visualization of 3D X-ray fluorescence data sets , 2003 .

[23]  M. L. Le Gros,et al.  X-ray tomography generates 3-D reconstructions of the yeast, saccharomyces cerevisiae, at 60-nm resolution. , 2003, Molecular biology of the cell.

[24]  W. Hoppe,et al.  Zur elektronenmikroskopisch dreidimensionalen Rekonstruktion eines Objektes , 2004, Naturwissenschaften.

[25]  Chao Yang,et al.  Unified 3-D structure and projection orientation refinement using quasi-Newton algorithm. , 2005, Journal of structural biology.

[26]  R. Ryan Vallance,et al.  Techniques for calibrating spindles with nanometer error motion , 2005 .

[27]  F. Beckmann,et al.  Automated determination of the center of rotation in tomography data. , 2006, Journal of the Optical Society of America. A, Optics, image science, and vision.

[28]  Mark H Ellisman,et al.  Transform-based backprojection for volume reconstruction of large format electron microscope tilt series. , 2006, Journal of structural biology.

[29]  K. Taylor,et al.  Accurate marker-free alignment with simultaneous geometry determination and reconstruction of tilt series in electron tomography. , 2006, Ultramicroscopy.

[30]  D. Muller,et al.  Three-dimensional imaging of nanovoids in copper interconnects using incoherent bright field tomography , 2006 .

[31]  Anja Seybert,et al.  Fiducial-less alignment of cryo-sections. , 2007, Journal of structural biology.

[32]  D. Gao,et al.  Software image alignment for X‐ray microtomography with submicrometre resolution using a SEM‐based X‐ray microscope , 2007, Journal of microscopy.

[33]  Hongtao Cui,et al.  X-ray computed tomography in Zernike phase contrast mode at 8 keV with 50-nm resolution using Cu rotating anode X-ray source , 2007 .

[34]  Alexander Sasov,et al.  Compensation of mechanical inaccuracies in micro-CT and nano-CT , 2008, Optical Engineering + Applications.

[35]  Falko Kuester,et al.  Automatic object and image alignment using Fourier Descriptors , 2008, Image Vis. Comput..

[36]  Manuel Guizar-Sicairos,et al.  Efficient subpixel image registration algorithms. , 2008, Optics letters.

[37]  José María Carazo,et al.  Marker-free image registration of electron tomography tilt-series , 2009, BMC Bioinformatics.

[38]  Mark Horowitz,et al.  Markov random field based automatic image alignment for electron tomography. , 2007, Journal of structural biology.

[39]  Albert F. Lawrence,et al.  Non-linear Bundle Adjustment for Electron Tomography , 2009, 2009 WRI World Congress on Computer Science and Information Engineering.

[40]  Mark Horowitz,et al.  Alignment of cryo-electron tomography datasets. , 2010, Methods in enzymology.

[41]  Achilleas S Frangakis,et al.  Alignator: a GPU powered software package for robust fiducial-less alignment of cryo tilt-series. , 2010, Journal of structural biology.

[42]  O. Bunk,et al.  Ptychographic X-ray computed tomography at the nanoscale , 2010, Nature.

[43]  Toshiyuki Fujimoto,et al.  Automatic coarse-alignment for TEM tilt series of rod-shaped specimens collected with a full angular range. , 2010, Micron.

[44]  Meng Cao,et al.  An automatic method of detecting and tracking fiducial markers for alignment in electron tomography. , 2011, Journal of electron microscopy.

[45]  L Houben,et al.  Refinement procedure for the image alignment in high-resolution electron tomography. , 2011, Ultramicroscopy.

[46]  O. Bunk,et al.  Phase tomography from x-ray coherent diffractive imaging projections. , 2011, Optics express.

[47]  Phillip A. Williams,et al.  TXM-Wizard: a program for advanced data collection and evaluation in full-field transmission X-ray microscopy , 2012, Journal of synchrotron radiation.

[48]  O. Bunk,et al.  An instrument for 3D x-ray nano-imaging. , 2012, The Review of scientific instruments.

[49]  C. Erdonmez,et al.  Automated markerless full field hard x-ray microscopic tomography at sub-50 nm 3-dimension spatial resolution , 2012 .

[50]  Chao Yang,et al.  Automatic alignment and reconstruction of images for soft X-ray tomography. , 2012, Journal of structural biology.

[51]  Kees Joost Batenburg,et al.  Automatic Optimization of Alignment Parameters for Tomography Datasets , 2013, SCIA.

[52]  Jungdae Kim,et al.  Compact prototype apparatus for reducing the circle of confusion down to 40 nm for x-ray nanotomography. , 2013, The Review of scientific instruments.

[53]  Norio Baba,et al.  Alternative automatic alignment method for specimen tilt-series images based on back-projected volume data cross-correlations. , 2014, Microscopy.

[54]  Francesco De Carlo,et al.  TomoPy: a framework for the analysis of synchrotron tomographic data , 2014, Journal of synchrotron radiation.

[55]  Jun Lim,et al.  Hard X-ray nanotomography beamline 7C XNI at PLS-II. , 2014, Journal of synchrotron radiation.

[56]  O. Bunk,et al.  X-ray ptychographic computed tomography at 16 nm isotropic 3D resolution , 2014, Scientific Reports.

[57]  B. Lai,et al.  The Bionanoprobe: hard X-ray fluorescence nanoprobe with cryogenic capabilities , 2013, Journal of synchrotron radiation.

[58]  Renmin Han,et al.  A marker-free automatic alignment method based on scale-invariant features. , 2014, Journal of structural biology.

[59]  Emmanuelle Gouillart,et al.  scikit-image: image processing in Python , 2014, PeerJ.

[60]  Alexander Sasov,et al.  Practical pseudo-3D registration for large tomographic images , 2014, Optics & Photonics - Optical Engineering + Applications.

[61]  Y. Ching,et al.  Image Alignment for Tomography Reconstruction from Synchrotron X-Ray Microscopic Images , 2014, PloS one.

[62]  Michael Drakopoulos,et al.  Reliable method for calculating the center of rotation in parallel-beam tomography. , 2014, Optics express.

[63]  Volker Schmidt,et al.  Missing wedge computed tomography by iterative algorithm DIRECTT , 2016, Journal of microscopy.

[64]  O. Bunk,et al.  Quantitative interior x-ray nanotomography by a hybrid imaging technique , 2015 .

[65]  S Kalbfleisch,et al.  Pushing the limits: an instrument for hard X-ray imaging below 20 nm. , 2015, Journal of synchrotron radiation.

[66]  Renmin Han,et al.  A novel fully automatic scheme for fiducial marker-based alignment in electron tomography. , 2015, Journal of structural biology.

[67]  Shumin Fang,et al.  Enhancing grain boundary ionic conductivity in mixed ionic–electronic conductors , 2015, Nature Communications.

[68]  Li Li,et al.  Multimodality hard-x-ray imaging of a chromosome with nanoscale spatial resolution , 2016, Scientific Reports.

[69]  Glenn R. Myers,et al.  Multi-resolution radiograph alignment for motion correction in x-ray micro-tomography , 2016, Optical Engineering + Applications.

[70]  Chung Ki Hong,et al.  Runout error correction in tomographic reconstruction by intensity summation method. , 2016, Journal of synchrotron radiation.

[71]  Hmida Rojbani,et al.  Joint 3D alignment-reconstruction multi-scale approach for cryo electron tomography , 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

[72]  K. Fezzaa,et al.  Nanoscale 3D imaging at the Advanced Photon Source , 2016 .

[73]  Charudatta Phatak,et al.  A convolutional neural network approach to calibrating the rotation axis for X-ray computed tomography. , 2017, Journal of synchrotron radiation.

[74]  Daniel J Ching,et al.  XDesign: an open-source software package for designing X-ray imaging phantoms and experiments. , 2017, Journal of synchrotron radiation.

[75]  Seokhwan Yoon,et al.  Alignment Solution for CT Image Reconstruction using Fixed Point and Virtual Rotation Axis , 2017, Scientific reports.