A software tool for tomographic axial superresolution in STED microscopy |
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| Authors: | S. KOHO T. DEGUCHI P. E. HÄNNINEN |
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| Affiliation: | Department of Cell Biology and Anatomy, Laboratory of Biophysics, Institute of Biomedicine and Medicity Research Laboratories, University of Turku, Turku, Finland |
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| Abstract: | A method for generating three‐dimensional tomograms from multiple three‐dimensional axial projections in STimulated Emission Depletion (STED) superresolution microscopy is introduced. Our STED< method, based on the use of a micromirror placed on top of a standard microscopic sample, is used to record a three‐dimensional projection at an oblique angle in relation to the main optical axis. Combining the STED< projection with the regular STED image into a single view by tomographic reconstruction, is shown to result in a tomogram with three‐to‐four‐fold improved apparent axial resolution. Registration of the different projections is based on the use of a mutual‐information histogram similarity metric. Fusion of the projections into a single view is based on Richardson‐Lucy iterative deconvolution algorithm, modified to work with multiple projections. Our tomographic reconstruction method is demonstrated to work with real biological STED superresolution images, including a data set with a limited signal‐to‐noise ratio (SNR); the reconstruction software (SuperTomo) and its source code will be released under BSD open‐source license. |
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| Keywords: | Axial tomography image fusion image processing image registration open source software reconstruction algorithms superresolution microscopy STED |
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