Biology subjects

Koho, S. V.

Publications and source records attributed to Koho, S. V..

3 recordsLinked to original sources

bioRxiv2019

Synergic Combination of Stimulated Emission Depletion Microscopy with Image Scanning Microscopy to Reduce Light Dosage

Stimulated emission depletion (STED) microscopy is one of the most influential nanoscopy techniques; by increasing the STED beam intensity, it theoretically improves the spatial resolution to any desired value. However, the higher is the dose of stimulating photons, the stronger are the photo-bleaching and photo-toxicity effects, which potentially compromise live-cell and long-term imaging. For this reason the scientific community is looking for strategies to reduce the STED beam intensity needed to achieve a target resolution. Here, we show how the combination of STED microscopy with image scanning microscopy (ISM) meets this request. In particular, we introduce a new STED-ISM architecture - based on our recent single-photon-avalanche-diode (SPAD) detector array - which allows covering the near-diffraction limit resolution range with reduced STED beam intensity. We demonstrate this ability both with simulated data and in live-cell experiments. Because of (i) the minimal changes in the optical architecture of the typical point-scanning STED microscope; (ii) the parameter-free, robust and real-time pixel-reassignment method to obtain the STED-ISM image; (iii) the compatibility with all the recent progresses in STED microscopy, we envisage a natural and rapid upgrade of any STED microscope to the proposed STED-ISM architecture.

bioengineering↗

bioRxiv2019

Easy Two-Photon Image Scanning Microscopy with SPAD Array and Blind Image Reconstruction

Two-photon excitation (2PE) microscopy is the imaging modality of choice, when one desires to work with thick biological samples, possibly in-vivo. However, the resolution in two-photon microscopy is poor, below confocal microscopy, and the lack of an optical pinhole becomes apparent in complex samples as reduced quality of optical sectioning. Here, we propose a straightforward implementation of 2PE image scanning microscopy (2PE-ISM) that, by leveraging our recently introduced ISM platform - based on a new single-photon avalanche diode array detector - coupled with a novel blind image reconstruction method, is shown to improve the optical resolution, as well as the overall image quality in various test samples. Most importantly, our 2PE-ISM implementation requires no calibration or other input from the user - it works like any old and familiar two-photon system, but simply produces higher resolution images (in real-time). Making the complexity disappear, in our view, is the biggest novelty here, and the key for making 2PE-ISM mainstream.

bioengineering↗

bioRxiv2019

Fourier ring correlation simplifies image restoration in fluorescence microscopy

Fourier ring correlation (FRC) has recently gained some popularity among (super-resolution) fluorescence microscopists as a straightforward and objective method to measure the effective resolution of a microscopy image. While the knowledge of the numeric resolution value is helpful in e.g. interpreting imaging results, much more practical use can be made of FRC analysis - in this article we propose novel blind image restoration methods enabled by it. We apply FRC to perform image de-noising by frequency domain filtering. We propose novel blind linear and non-linear image deconvolution methods that use FRC to estimate the effective point-spread-function, directly from the images, with no need for prior knowledge of the instrument or sample characteristics. The deconvolution is shown to work exquisitely with both two- and three-dimensional images. We also show how FRC can be used as a powerful metric to observe the progress of iterative deconvolution. While developing the image restoration methods, we also addressed two important limitations in FRC that are of more general interest: how to make FRC work with single images and with three-dimensional images with anisotropic resolution.

bioinformatics↗