A Bayesian reconstruction method for micro‐rotation imaging in light microscopy

The authors present a three‐dimensional (3D) reconstruction algorithm and reconstruction‐based deblurring method for light microscopy using a micro‐rotation device. In contrast to conventional 3D optical imaging where the focal plane is shifted along the optical axis, micro‐rotation imaging employs dielectric fields to rotate the object inside a fixed optical set‐up. To address this entirely new 3D‐imaging modality, the authors present a reconstruction algorithm based on Bayesian inversion theory and use the total variation function as a structure prior. The spectral properties of the reconstruction by simulations that illustrate the strengths and the weaknesses of the micro‐rotation approach, compared with conventional 3D optical imaging, were studied. The reconstruction from real data sets shows that this method is promising for 3D reconstruction and offers itself as a deblurring method using a reconstruction‐based procedure for removing out‐of‐focus light from the micro‐rotation image series. Microsc. Res. Tech., 2008. © 2007 Wiley‐Liss, Inc.

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

[2]  F S Fay,et al.  Superresolution three-dimensional images of fluorescence in cells with minimal light exposure. , 1995, Science.

[3]  Bernhard Wagner,et al.  Radio-frequency microtools for particle and live cell manipulation , 1994, Naturwissenschaften.

[4]  Josiane Zerubia,et al.  Richardson–Lucy algorithm with total variation regularization for 3D confocal microscope deconvolution , 2006, Microscopy research and technique.

[5]  T. Holmes.  Expectation-maximization restoration of band-limited, truncated point-process intensities with application in microscopy , 1989 .

[6]  S S Brandt,et al.  Automatic TEM image alignment by trifocal geometry , 2006, Journal of microscopy.

[7]  S. Shorte,et al.  Use of micro-rotation imaging to study JNK-mediated cell survival in Theileria parva-infected B-lymphocytes , 2005, Parasitology.

[8]  G. Gradl,et al.  A 3-D microelectrode system for handling and caging single cells and particles , 1999 .

[9]  K. Mueller,et al.  Fast and accurate three-dimensional reconstruction from cone-beam projection data using algebraic methods , 1998 .

[10]  S G Shirley,et al.  Dielectrophoretic manipulation of suspended submicron particles , 2000, Electrophoresis.

[11]  R M Lewitt,et al.  Multidimensional digital image representations using generalized Kaiser-Bessel window functions. , 1990, Journal of the Optical Society of America. A, Optics and image science.

[12]  C Cremer,et al.  Axial tomographic confocal fluorescence microscopy , 2002, Journal of microscopy.

[13]  Peter Engelhardt,et al.  Electron Tomography of Chromosome Structure , 2006 .

[14]  P. Verveer,et al.  A comparison of image restoration approaches applied to three‐dimensional confocal and wide‐field fluorescence microscopy , 1999, Journal of microscopy.

[15]  E. Somersalo,et al.  Statistical and computational inverse problems , 2004 .

[16]  Carol J. Cogswell,et al.  Fluorescence microtomography: multiangle image acquisition and 3D digital reconstruction , 1996, Electronic Imaging.

[17]  G. Herman,et al.  Disentangling conformational states of macromolecules in 3D-EM through likelihood optimization , 2007, Nature Methods.

[18]  Marcel Carbillet,et al.  Deconvolution of multiple images with high dynamic range and an application to LBT LINC-NIRVANA , 2006 .

[19]  Ville Kolehmainen,et al.  Structure-From-Motion Without Correspondence From Tomographic Projections by Bayesian Inversion Theory , 2007, IEEE Transactions on Medical Imaging.

[20]  G Bricogne,et al.  Maximum-entropy three-dimensional reconstruction with deconvolution of the contrast transfer function: a test application with adenovirus. , 1996, Journal of structural biology.

[21]  D A Agard,et al.  Tilted view reconstruction in optical microscopy. Three-dimensional reconstruction of Drosophila melanogaster embryo nuclei. , 1989, Biophysical journal.

[22]  E Somersalo,et al.  Statistical inversion for medical x-ray tomography with few radiographs: II. Application to dental radiology. , 2003, Physics in medicine and biology.

[23]  I. Csiszár.  Why least squares and maximum entropy? An axiomatic approach to inference for linear inverse problems , 1991 .

[24]  I. Sherman,et al.  Selection of peptides recognized by human antibodies against the surface of Plasmodium falciparum-infected erythrocytes , 2004, Parasitology.

[25]  G. Fuhr,et al.  Three-dimensional electric field traps for manipulation of cells--calculation and experimental verification. , 1993, Biochimica et biophysica acta.

[26]  R. Lewitt.  Alternatives to voxels for image representation in iterative reconstruction algorithms , 1992, Physics in medicine and biology.

[27]  L. Rudin,et al.  Nonlinear total variation based noise removal algorithms , 1992 .

[28]  Sami Sebastian Brandt.  Markerless Alignment in Electron Tomography , 2007 .

[29]  G. M. P. VAN KEMPEN,et al.  A quantitative comparison of image restoration methods for confocal microscopy , 1997 .

[30]  T M Jovin,et al.  Improved restoration from multiple images of a single object: application to fluorescence microscopy. , 1998, Applied optics.

[31]  F S Fay,et al.  Three‐dimensional molecular distribution in single cells analysed using the digital imaging microscope , 1989, Journal of microscopy.

[32]  D. Agard,et al.  Fluorescence microscopy in three dimensions. , 1989, Methods in cell biology.

[33]  P. Green.  Bayesian reconstructions from emission tomography data using a modified EM algorithm. , 1990, IEEE transactions on medical imaging.

[34]  Badrinath Roysam,et al.  Light Microscopic Images Reconstructed by Maximum Likelihood Deconvolution , 1995 .

[35]  Rainer Heintzmann,et al.  A system and methodology for high-content visual screening of individual intact living cells in suspension , 2007, SPIE BiOS.

[36]  J. Korlach,et al.  Trapping, deformation, and rotation of giant unilamellar vesicles in octode dielectrophoretic field cages. , 2005, Biophysical journal.

[37]  L. Shepp,et al.  A Statistical Model for Positron Emission Tomography , 1985 .

[38]  J. Broers,et al.  Both emerin and lamin C depend on lamin A for localization at the nuclear envelope. , 2001, Journal of cell science.

[39]  Alberto Diaspro,et al.  Fuzzy logic and maximum a posteriori-based image restoration for confocal microscopy. , 2006, Optics letters.