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Deep learning enables cross-modality super-resolution in fluorescence microscopy
摘要： We present deep-learning-enabled super-resolution across different fluorescence microscopy modalities. This data-driven approach does not require numerical modeling of the imaging process or the estimation of a point-spread-function, and is based on training a generative adversarial network (GAN) to transform diffraction-limited input images into super-resolved ones. Using this framework, we improve the resolution of wide-field images acquired with low-numerical-aperture objectives, matching the resolution that is acquired using high-numerical-aperture objectives. We also demonstrate cross-modality super-resolution, transforming confocal microscopy images to match the resolution acquired with a stimulated emission depletion (STED) microscope. We further demonstrate that total internal reflection fluorescence (TIRF) microscopy images of subcellular structures within cells and tissues can be transformed to match the results obtained with a TIRF-based structured illumination microscope. The deep network rapidly outputs these super-resolved images, without any iterations or parameter search, and could serve to democratize super-resolution imaging.
关键词： GAN,cross-modality,super-resolution,fluorescence microscopy,deep learning
更新于2025-11-21 11:24:58
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Successful optimization of reconstruction parameters in structured illumination microscopy – A practical guide
摘要： The impact of the different reconstruction parameters in super-resolution structured illumination microscopy (SIM) on image artifacts is carefully analyzed. These parameters comprise the Wiener filter parameter, an apodization function, zero-frequency suppression and modifications of the optical transfer function. A detailed investigation of the reconstructed image spectrum is concluded to be suitable for identifying artifacts. For this purpose, two samples, an artificial test slide and a more realistic biological system, were used to characterize the artifact classes and their correlation with the image spectra as well as the reconstruction parameters. In addition, a guideline for efficient parameter optimization is suggested and the implementation of the parameters in selected up-to-date processing packages (proprietary and open-source) is depicted.
关键词： Super resolution,Fluorescence microscopy,Structured illumination microscopy,Parameter estimation,Image reconstruction
更新于2025-09-23 15:23:52
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Accelerated FRET-PAINT microscopy
摘要： Recent development of FRET-PAINT microscopy significantly improved the imaging speed of DNA-PAINT, the previously reported super-resolution fluorescence microscopy with no photobleaching problem. Here we try to achieve the ultimate speed limit of FRET-PAINT by optimizing the camera speed, dissociation rate of DNA probes, and bleed-through of the donor signal to the acceptor channel, and further increase the imaging speed of FRET-PAINT by 8-fold. Super-resolution imaging of COS-7 microtubules shows that high-quality 40-nm resolution images can be obtained in just tens of seconds.
关键词： FRET-PAINT,Super-resolution fluorescence microscopy,FRET,Single-molecule localization microscopy
更新于2025-09-23 15:22:29
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Quenched Stochastic Optical Reconstruction Microscopy (qSTORM) with Graphene Oxide
摘要： Quenched Stochastic Optical Reconstruction Microscopy (qSTORM) was demonstrated with graphene oxide sheets, peptides and bacteria; a method of contrast enhancement with super-resolution fluorescence microscopy. Individual sheets of graphene oxide (GO) were imaged with a resolution of 16 nm using the quenching of fluorescence emission by GO via its large Resonant Energy Transfer (RET) efficiency. The method was then extended to image self-assembled peptide aggregates (resolution 19 nm) and live bacterial cells (resolution 55 nm, the capsular structure of E. coli from urinary tract infections) with extremely low backgrounds and high contrasts (between one and two orders of magnitude contrast factor improvements that depended on the thickness of the graphene oxide layer used). Graphene oxide films combined with STORM imaging thus provide an extremely convenient method to image samples with large backgrounds due to non-specifically bound fluorophores (either due to excess labelling or autofluorescent molecules), which is a common occurrence in studies of both biological cells and soft-condensed matter. The GO quenches the fluorescence across a thin layer at distances of less than 15 nm. Graphene oxide films coated with thin layers (≤15 nm) of polystyrene, polymethylmethacrylate and polylysine are shown to be effective in producing high contrast qSTORM images, providing a convenient modulation of sample/substrate interactions. The GO coatings can also provide an increased image resolution and a factor of 2.3 improvement was observed with the peptide fibres using a feature of interest metric,when there was a large non-specifically bound background.
关键词： Quenched Stochastic Optical Reconstruction Microscopy,contrast enhancement,peptide aggregates,qSTORM,fluorescence quenching,RET,bacterial cells,Resonant Energy Transfer,graphene oxide,super-resolution fluorescence microscopy
更新于2025-09-10 09:29:36