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...

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Bibliographic Details
Published in:Microscopy research and technique 2008-02, Vol.71 (2), p.158-167
Main Authors: Laksameethanasan, Danai, Brandt, Sami S., Engelhardt, Peter, Renaud, Olivier, Shorte, Spencer L.
Format: Article
Language:English
Subjects:
Animals
Bayes Theorem
cell biology
expectation-maximization
fluorescence imaging
Image Processing, Computer-Assisted - methods
Imaging, Three-Dimensional - methods
micro-rotation imaging
Microscopy - methods
Nuclear Envelope - ultrastructure
Rotation
total variation
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Summary: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.
ISSN:1059-910X
1097-0029
DOI:10.1002/jemt.20550