Detektion und Klassifizierung von Bewegungsartefakten in der Mikroskopie mit strukturierter Beleuchtung

Mikroskopie mit strukturierter Beleuchtung (SIM) ist eine Technik zur hochaufgelösten Mikroskopie an lebenden Zellen. Die Aufnahme von lebenden biologischen Zellen durch Mikroskopie mit strukturierter Beleuchtung leidet an Bewegungsartefakten. Diese nehmen mit steigender Geschwindigkeit der abgebildeten Struktur zu und sind nur im Extremfall als Artefakte zu identifizieren. Um das Auftreten von Bewegungsartefakten im Vorfeld zu unterbinden, lohnt sich eine Abschätzung der Geschwindigkeit der zu beobachtenden Struktur und ein Vergleich mit der Aufnahmegeschwindigkeit des verwendeten Mikroskops. Zellkomponenten können jedoch auch ruckartige Bewegung vollführen, sodass diese Abschätzung nicht ausreicht, um Bewegungsartefakte sicher auszuschließen. Kner et al. sehen beispielsweise deutliche Bewegungsartefakte in ihren SIM-Daten beim Aufbrechen von Mikrotubuli. Die Regeln guter wissenschaftlicher Praxis fordern alle Ergebnisse konsequent selbst anzuzweifeln. Zweifel, an der Richtigkeit der Abbildung und den daraus abgeleiteten Schlussfolgerungen, können bisher nicht widerlegt werden, da es kein Verfahren gibt, welche Bewegungsartefakte in SIM-Bilder sicher identifiziert. Dies führt zu Kritik an Mikroskopie mit strukturierter Beleuchtung. Ziel dieser Arbeit ist die vollautomatische Detektion und Lokalisation von Bewegungsartefakten. Dies ist ein elementarer Schritt um die Glaubwürdigkeit einer SIM-Aufnahme zu verifizieren, sodass die eigentliche Aufgabe - die Erforschung der Zelle - im Fokus stehen kann

Better than a lens -- Increasing the signal-to-noise ratio through pupil splitting

Lenses are designed to fulfill Fermats principle such that all light interferes constructively in its focus, guaranteeing its maximum concentration. It can be shown that imaging via an unmodified full pupil yields the maximum transfer strength for all spatial frequencies transferable by the system. Seemingly also the signal-to-noise ratio (SNR) is optimal. The achievable SNR at a given photon budget is critical especially if that budget is strictly limited as in the case of fluorescence microscopy. In this work we propose a general method which achieves a better SNR for high spatial frequency information of an optical imaging system, without the need to capture more photons. This is achieved by splitting the pupil of an incoherent imaging system such that two (or more) sub-images are simultaneously acquired and computationally recombined. We compare the theoretical performance of split pupil imaging to the non-split scenario and implement the splitting using a tilted elliptical mirror placed at the back-focal-plane (BFP) of a fluorescence widefield microscope

Thermal illumination limits in 3D Raman microscopy: A comparison of different sample illumination strategies to obtain maximum imaging speed

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

cellSTORM - Cost-effective Super-Resolution on a Cellphone using dSTORM

Expensive scientific camera hardware is amongst the main cost factors in modern, high-performance microscopes. Recent technological advantages have, however, yielded consumer-grade camera devices that can provide surprisingly good performance. The camera sensors of smartphones in particular have benefited of this development. Combined with computing power and due to their ubiquity, smartphones provide a fantastic opportunity for "imaging on a budget". Here we show that a consumer cellphone is capable even 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 investigated an approach by a trained image-to-image generative adversarial network (GAN). This not only serves as a versatile technique to reconstruct video sequences under conditions where traditional algorithms provide sub-optimal localization performance, but also allows processing directly on the smartphone. We believe that "cellSTORM" paves the way for affordable super-resolution microscopy suitable for research and education, expanding access to cutting edge research to a large community

Motion artefact detection in structured illumination microscopy for live cell imaging

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

Successful optimization of reconstruction parameters in structured illumination microscopy

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 Author

Three-dimensional spatiotemporal tracking of nano-objects diffusing in water-filled optofluidic microstructured fiber

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

Ultralong Tracking of Fast‐Diffusing Nano‐Objects inside Nanofluidic Channel−Enhanced Microstructured Optical Fiber

Nanoparticle tracking analysis (NTA) represents one essential technology to characterize diffusing nanoscale objects. Herein, uncovering dynamic processes and high-precision measurements requires tracks with thousands of frames to reach high statistical significance, ideally at high frame rates. Optical fibers with nanochannels are used for NTA, successfully demonstrating acquisition of trajectories of fast diffusion nano-objects with 100 000 frames. Due to the spatial limitation of the central nanofluidic channel, diffusion of objects illuminated by the core mode is confined, enabling the recording of Brownian motion over extraordinarily long time scales at high frame rates. The resulting benefits are discussed on a representative track of a gold nanosphere diffusing in water in over nearly 100 000 frames at 2 kHz frame rate. In addition to the verification of the fiber-based NTA using two data processing methods, a segmented analysis reveals a correlation between precision of determined diameter and continuous time interval (i.e., number of frames per subtrajectory). The presented results demonstrate the capabilities of fiber-based NTA in terms of 1) determining diameters with extraordinary high precision of single species and 2) monitoring dynamic processes of the object or the fluidic environment, both of which are relevant within biology, microrheology, and nano-object characterization

Severity of current depression and remission status are associated with structural connectome alterations in major depressive disorder

Major depressive disorder (MDD) is associated to affected brain wiring. Little is known whether these changes are stable over time and hence might represent a biological predisposition, or whether these are state markers of current disease severity and recovery after a depressive episode. Human white matter network ("connectome") analysis via network science is a suitable tool to investigate the association between affected brain connectivity and MDD. This study examines structural connectome topology in 464 MDD patients (mean age: 36.6 years) and 432 healthy controls (35.6 years). MDD patients were stratified categorially by current disease status (acute vs. partial remission vs. full remission) based on DSM-IV criteria. Current symptom severity was assessed continuously via the Hamilton Depression Rating Scale (HAMD). Connectome matrices were created via a combination of T1-weighted magnetic resonance imaging (MRI) and tractography methods based on diffusion-weighted imaging. Global tract-based metrics were not found to show significant differences between disease status groups, suggesting conserved global brain connectivity in MDD. In contrast, reduced global fractional anisotropy (FA) was observed specifically in acute depressed patients compared to fully remitted patients and healthy controls. Within the MDD patients, FA in a subnetwork including frontal, temporal, insular, and parietal nodes was negatively associated with HAMD, an effect remaining when correcting for lifetime disease severity. Therefore, our findings provide new evidence of MDD to be associated with structural, yet dynamic, state-dependent connectome alterations, which covary with current disease severity and remission status after a depressive episode