Filters

2016 - 20206

More filters

2019 - 201912020 - 20215
Reset filters

Settings

Author: Förster, Ronny × Start date: 2014 ×

Search Results

Now showing 1 - 6 of 6
  • Thumbnail Image
    Item
    Successful optimization of reconstruction parameters in structured illumination microscopy
    (Amsterdam [u.a.] : Elsevier, 2019) Karras, Christian; Smedh, Maria; Förster, Ronny; Deschout, Hendrik; Fernandez-Rodriguez, Julia; Heintzmann, Rainer
    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. © 2018 The Authors
  • Thumbnail Image
    Item
    Motion artefact detection in structured illumination microscopy for live cell imaging
    (Washington, DC : Optical Society of America, 2016) Förster, Ronny; Wicker, Kai; Müller, Walter; Jost, Aurélie; Heintzmann, Rainer
    The reconstruction process of structured illumination microscopy (SIM) creates substantial artefacts if the specimen has moved during the acquisition. This reduces the applicability of SIM for live cell imaging, because these artefacts cannot always be recognized as such in the final image. A movement is not necessarily visible in the raw data, due to the varying excitation patterns and the photon noise. We present a method to detect motion by extracting and comparing two independent 3D wide-field images out of the standard SIM raw data without needing additional images. Their difference reveals moving objects overlaid with noise, which are distinguished by a probability theory-based analysis. Our algorithm tags motion-artefacts in the final high-resolution image for the first time, preventing the end-user from misinterpreting the data. We show and explain different types of artefacts and demonstrate our algorithm on a living cell.
  • Thumbnail Image
    Item
    Automated distinction of shearing and distortion artefacts in structured illumination microscopy
    (Washington D.C. : Optical Society of America, 2018) Förster, Ronny; Müller, Walter; Richter, Renè; Heintzmann, Rainer
    Any motion during an image acquisition leads to an artefact in the final image. Structured illumination microscopy (SIM) combines several raw images into one high-resolution image and is thus particularly prone to these motion artefacts. Their unpredictable shape cannot easily be distinguished from real high-resolution content. We previously implemented a motion detection specifically for SIM, which had two shortcomings which are solved here. First, the brightness dependency of the motion signal is removed. Second, the empirical threshold of the calculated motion signal was not a threshold at a maximum allowed artefact. Here we investigate which artefacts are still acceptable and which linear movement creates them. Thus, the motion signal is linked with the maximal strength of the expected artefact. A signal-to-noise analysis including classification successfully distinguishes between artefact-free imaging, shearing and distortion artefacts in biological specimens. A shearing, as in wide-field microscopy, is the dominant reconstruction artefact, while distortions arise not until surprisingly fast movements.
  • Thumbnail Image
    Item
    Three-dimensional spatiotemporal tracking of nano-objects diffusing in water-filled optofluidic microstructured fiber
    (Berlin : de Gruyter, 2020) Jiang, Shiqi; Förster, Ronny; Plidschun, Malte; Kobelke, Jens; Ando, Ron Fatobene; Schmidt, Markus A.
    Three-dimensional (3D) tracking of nano-objects represents a novel pathway for understanding dynamic nanoscale processes within bioanalytics and life science. Here we demonstrate 3D tracking of diffusing 100 nm gold nanosphere within a water-filled optofluidic fiber via elastic light scattering-based position retrieval. Specifically, the correlation between intensity and position inside a region of a fiber-integrated microchannel has been used to decode the axial position from the scattered intensity, while image processing-based tracking was used in the image plane. The 3D trajectory of a diffusing gold nanosphere has been experimentally determined, while the determined diameter analysis matches expectations. Beside key advantages such as homogenous light-line illumination, low-background scattering, long observation time, large number of frames, high temporal and spatial resolution and compatibility with standard microscope, the particular properties of operating with water defines a new bioanalytical platform that is highly relevant for medical and life science applications. © 2020 Shiqi Jiang et al., published by De Gruyter. 2020.
  • Thumbnail Image
    Item
    Thermal illumination limits in 3D Raman microscopy: A comparison of different sample illumination strategies to obtain maximum imaging speed
    (San Francisco : Public Library of Science, 2019) Hauswald, Walter; Förster, Ronny; Popp, Jürgen; Heintzmann, Rainer
    Confocal Raman microscopy is a powerful tool for material science and biomedical research. However, the low Raman scattering cross-section limits the working speed, which reduces the applicability for large and sensitive samples. Here, we discuss the fundamental physical limits of Raman spectroscopy with respect to signal-to-noise, sample load and how to achieve maximal imaging speed. For this, we develop a simple model to describe arbitrary far field light microscopes and their thermal influence on the sample. This model is used to compare the practical applicability of point- and line-confocal microscopes as well as wide-field-, light sheet- and light line illumination, for the measurement of 3D biological samples. The parallelization degree of the illumination can positively affect the imaging speed as long as it is not limited by thermal sample heating. In case of heat build-up inside the sample, the advantages of parallelization can be lost due to the required attenuation of excitation and the working speed can drop below that of a sequential method. We show that for point like illumination, the exposure time is thermally not as critical for the sample as the irradiance, while for volume like illumination, the exposure time and irradiance result in the same thermal effect. The results of our theoretical study are experimentally confirmed and suggest new concepts of Raman microscopy, thus extending its applicability. The developed model can be applied to Raman imaging as well as to other modes (e.g. two- or three- photon imaging, STED, PALM/STORM, MINFLUX) where thermal effects impose a practical limit due to the high irradiance required.
  • Thumbnail Image
    Item
    cellSTORM - Cost-effective Super-Resolution on a Cellphone using dSTORM
    (San Francisco : Public Library of Science, 2019) Diederich, Benedict; Then, Patrick; Jügler, Alexander; Förster, Ronny; Heintzmann, Rainer
    High optical resolution in microscopy usually goes along with costly hardware components, such as lenses, mechanical setups and cameras. Several studies proved that Single Molecular Localization Microscopy can be made affordable, relying on off-the-shelf optical components and industry grade CMOS cameras. Recent technological advantages have yielded consumer-grade camera devices with surprisingly good performance. The camera sensors of smartphones have benefited of this development. Combined with computing power smartphones provide a fantastic opportunity for “imaging on a budget”. Here we show that a consumer cellphone is capable of optical super-resolution imaging by (direct) Stochastic Optical Reconstruction Microscopy (dSTORM), achieving optical resolution better than 80 nm. In addition to the use of standard reconstruction algorithms, we used a trained image-to-image generative adversarial network (GAN) to reconstruct video sequences under conditions where traditional algorithms provide sub-optimal localization performance directly on the smartphone. We believe that “cellSTORM” paves the way to make super-resolution microscopy not only affordable but available due to the ubiquity of cellphone cameras.High optical resolution in microscopy usually goes along with costly hardware components, such as lenses, mechanical setups and cameras. Several studies proved that Single Molecular Localization Microscopy can be made affordable, relying on off-the-shelf optical components and industry grade CMOS cameras. Recent technological advantages have yielded consumer-grade camera devices with surprisingly good performance. The camera sensors of smartphones have benefited of this development. Combined with computing power smartphones provide a fantastic opportunity for “imaging on a budget”. Here we show that a consumer cellphone is capable of optical super-resolution imaging by (direct) Stochastic Optical Reconstruction Microscopy (dSTORM), achieving optical resolution better than 80 nm. In addition to the use of standard reconstruction algorithms, we used a trained image-to-image generative adversarial network (GAN) to reconstruct video sequences under conditions where traditional algorithms provide sub-optimal localization performance directly on the smartphone. We believe that “cellSTORM” paves the way to make super-resolution microscopy not only affordable but available due to the ubiquity of cellphone cameras.