Comparison of 3D structured illumination microscopy configurations in terms of spectral signal to noise ratio.

Structured illumination microscopy (SIM) is a powerful method for high-resolution 3D-imaging that is compatible with standard fluorescence labeling techniques, as it provides optical sectioning as well as an up to twofold improvement of lateral resolution over widefield microscopy by combining illumination pattern diversity with computational reconstruction. We present a quantitative analysis of the image quality of 3D-SIM using the spectral signal-to-noise ratio (SSNR). In particular, we compare conventional woodpile illumination pattern based 3D-SIM, where the pattern is rotated and translated to acquire the set of raw images that is fed into the reconstruction algorithm, to (square or hexagonal) lattice 3D-SIM, where the pattern is only translated to assemble the input set of raw images.

Noise amplification and ill-convergence of Richardson-Lucy deconvolution.

Richardson-Lucy (RL) deconvolution optimizes the likelihood of the object estimate for an incoherent imaging system. It can offer an increase in contrast, but converges poorly, and shows enhancement of noise as the iteration progresses. We have discovered the underlying reason for this problematic convergence behaviour using a Cramér Rao Lower Bound (CRLB) analysis.

Calibration-free estimation of field dependent aberrations for single molecule localization microscopy across large fields of view.

Image quality in single molecule localization microscopy (SMLM) depends largely on the accuracy and precision of the localizations. While under ideal imaging conditions the theoretically obtainable precision and accuracy are achieved, in practice this changes if (field dependent) aberrations are present. Currently there is no simple way to measure and incorporate these aberrations into the Point Spread Function (PSF) fitting, therefore the aberrations are often taken constant or neglected all together.

Single image Fourier ring correlation.

We address resolution assessment for (light super-resolution) microscopy imaging. In modalities where imaging is not diffraction limited, correlation between two noise independent images is the standard way to infer the resolution. Here we take away the need for two noise independent images by computationally splitting one image acquisition into two noise independent realizations.

Detecting continuous structural heterogeneity in single-molecule localization microscopy data.

Fusion of multiple chemically identical complexes, so-called particles, in localization microscopy, can improve the signal-to-noise ratio and overcome under-labeling. To this end, structural homogeneity of the data must be assumed. Biological heterogeneity, however, could be present in the data originating from distinct conformational variations or (continuous) variations in particle shapes.

Particle fusion of super-resolution data reveals the unit structure of Nup96 in Nuclear Pore Complex.

Single molecule localization microscopy offers resolution nearly down to the molecular level with specific molecular labelling, and is thereby a promising tool for structural biology. In practice, however, the actual value to this field is limited primarily by incomplete fluorescent labelling of the structure. This missing information can be completed by merging information from many structurally identical particles in a particle fusion approach similar to cryo-EM single-particle analysis.

Electron-beam patterned calibration structures for structured illumination microscopy.

Super-resolution fluorescence microscopy can be achieved by image reconstruction after spatially patterned illumination or sequential photo-switching and read-out. Reconstruction algorithms and microscope performance are typically tested using simulated image data, due to a lack of strategies to pattern complex fluorescent patterns with nanoscale dimension control. Here, we report direct electron-beam patterning of fluorescence nanopatterns as calibration standards for super-resolution fluorescence.

Axial accuracy in localization microscopy with 3D point spread function engineering.

Single-molecule localization microscopy has developed into a widely used technique to overcome the diffraction limit and enables 3D localization of single-emitters with nanometer precision. A widely used method to enable 3D encoding is to use a cylindrical lens or a phase mask to engineer the point spread function (PSF). The performance of these PSFs is often assessed by comparing the precision they achieve, ignoring accuracy.

Photon efficient orientation estimation using polarization modulation in single-molecule localization microscopy.

Combining orientation estimation with localization microscopy opens up the possibility to analyze the underlying orientation of biomolecules on the nanometer scale. Inspired by the recent improvement of the localization precision by shifting excitation patterns (MINFLUX, SIMFLUX), we have adapted the idea towards the modulation of excitation polarization to enhance the orientation precision. For this modality two modes are analyzed: i) normally incident excitation with three polarization steps to retrieve the in-plane angle of emitters and ii) obliquely incident excitation with p-polarization with five different azimuthal angles of incidence to retrieve the full orientation.

Precision in iterative modulation enhanced single-molecule localization microscopy.

Modulation enhanced single-molecule localization microscopy (meSMLM) methods improve the localization precision by using patterned illumination to encode additional position information. Iterative meSMLM (imeSMLM) methods iteratively generate prior information on emitter positions, used to locally improve the localization precision during subsequent iterations. The Cramér-Rao lower bound cannot incorporate prior information to bound the best achievable localization precision because it requires estimators to be unbiased.

Joint registration of multiple point clouds for fast particle fusion in localization microscopy.

Summary: We present a fast particle fusion method for particles imaged with single-molecule localization microscopy. The state-of-the-art approach based on all-to-all registration has proven to work well but its computational cost scales unfavorably with the number of particles N, namely as N2. Our method overcomes this problem and achieves a linear scaling of computational cost with N by making use of the Joint Registration of Multiple Point Clouds (JRMPC) method.

Waveguide-based total internal reflection fluorescence microscope enabling cellular imaging under cryogenic conditions.

Total internal reflection fluorescence (TIRF) microscopy is an important imaging tool for the investigation of biological structures, especially the study on cellular events near the plasma membrane. Imaging at cryogenic temperatures not only enables observing structures in a near-native and fixed state but also suppresses irreversible photo-bleaching rates, resulting in increased photo-stability of fluorophores. Traditional TIRF microscopes produce an evanescent field based on high numerical aperture immersion objective lenses with high magnification, which results in a limited field of view and is incompatible with cryogenic conditions.

Simultaneous orientation and 3D localization microscopy with a Vortex point spread function.

Estimating the orientation and 3D position of rotationally constrained emitters with localization microscopy typically requires polarization splitting or a large engineered Point Spread Function (PSF). Here we utilize a compact modified PSF for single molecule emitter imaging to estimate simultaneously the 3D position, dipole orientation, and degree of rotational constraint from a single 2D image. We use an affordable and commonly available phase plate, normally used for STED microscopy in the excitation light path, to alter the PSF in the emission light path.

Detecting structural heterogeneity in single-molecule localization microscopy data.

Particle fusion for single molecule localization microscopy improves signal-to-noise ratio and overcomes underlabeling, but ignores structural heterogeneity or conformational variability. We present a-priori knowledge-free unsupervised classification of structurally different particles employing the Bhattacharya cost function as dissimilarity metric. We achieve 96% classification accuracy on mixtures of up to four different DNA-origami structures, detect rare classes of origami occuring at 2% rate, and capture variation in ellipticity of nuclear pore complexes.

Structured illumination microscopy with noise-controlled image reconstructions.

Super-resolution structured illumination microscopy (SIM) has become a widely used method for biological imaging. Standard reconstruction algorithms, however, are prone to generate noise-specific artifacts that limit their applicability for lower signal-to-noise data. Here we present a physically realistic noise model that explains the structured noise artifact, which we then use to motivate new complementary reconstruction approaches.

3D particle averaging and detection of macromolecular symmetry in localization microscopy.

Single molecule localization microscopy offers in principle resolution down to the molecular level, but in practice this is limited primarily by incomplete fluorescent labeling of the structure. This missing information can be completed by merging information from many structurally identical particles. In this work, we present an approach for 3D single particle analysis in localization microscopy which hugely increases signal-to-noise ratio and resolution and enables determining the symmetry groups of macromolecular complexes.

High-speed multicolor structured illumination microscopy using a hexagonal single mode fiber array.

Structured illumination microscopy (SIM) is a widely used imaging technique that doubles the effective resolution of widefield microscopes. Most current implementations rely on diffractive elements, either gratings or programmable devices, to generate structured light patterns in the sample. These can be limited by spectral efficiency, speed, or both.

Automated detection of cribriform growth patterns in prostate histology images.

Cribriform growth patterns in prostate carcinoma are associated with poor prognosis. We aimed to introduce a deep learning method to detect such patterns automatically. To do so, convolutional neural network was trained to detect cribriform growth patterns on 128 prostate needle biopsies.

Image based aberration retrieval using helical point spread functions.

A practical method for determining wavefront aberrations in optical systems based on the acquisition of an extended, unknown object is presented. The approach utilizes a conventional phase diversity approach in combination with a pupil-engineered, helical point spread function (PSF) to discriminate the aberrated PSF from the object features. The analysis of the image's power cepstrum enables an efficient retrieval of the aberration coefficients by solving a simple linear system of equations.

Computational imaging modalities for multi-focal whole-slide imaging systems.

Whole-slide imaging systems can generate full-color image data of tissue slides efficiently, which are needed for digital pathology applications. This paper focuses on a scanner architecture that is based on a multi-line image sensor that is tilted with respect to the optical axis, such that every line of the sensor scans the tissue slide at a different focus level. This scanner platform is designed for imaging with continuous autofocus and inherent color registration at a throughput of the order of 400 MPx/s.

25 Anniversary of STED Microscopy and the 20 Anniversary of SIM: feature introduction.

This feature issue commemorating 25 years of STED microscopy and 20 years of SIM is intended to highlight the incredible progress and growth in the field of superresolution microscopy since Stefan Hell and Jan Wichmann published the article Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy in Optics Letters in 1994.

Multi-line fluorescence scanning microscope for multi-focal imaging with unlimited field of view.

Confocal scanning microscopy is the standard modality for fluorescence imaging. Point scanning, however, leads to a limited throughput and makes the technique unsuitable for fast multi-focal scanning over large areas. We propose an architecture for multi-focal fluorescence imaging that is scalable to large area imaging.

Localization microscopy at doubled precision with patterned illumination.

MINFLUX offers a breakthrough in single molecule localization precision, but is limited in field of view. Here we combine centroid estimation and illumination pattern induced photon count variations in a conventional widefield imaging setup to extract position information over a typical micrometer-sized field of view. We show a near two-fold improvement in precision over standard localization with the same photon count on DNA-origami nanostructures and tubulin in cells, using DNA-PAINT and STORM imaging.