Improving structured illumination microscopy by blind reconstruction and multifocus detection

Structured Illumination Microscopy (SIM) is a super-resolution microscopy method which enables a two-fold resolution enhancement with respect to classical wide-field (WF) fluorescence microscopy. In SIM, the sample is illuminated by a pattern, typically a sinusoidal grid of light. This pattern is typically the result of interference of either two or three plane waves. The wide dissemination of SIM is limited by the difficulties arising during the necessary numerical reconstruction. Artefacts are observed in the SIM reconstructed images if the illumination pattern is distorted or unknown. Blind-SIM is a deconvolution-based reconstruction approach that enables to reconstruct both the sample and the illumination pattern. Blind-SIM is able to reconstruct partially or fully unknown illumination patterns and is therefore robust to distortions. However, so far blind-SIM was not able to process data from thick samples where the visibility of the fringes is reduced by the presence of out-of-focus light. In this work, we present the thick slice blind-SIM algorithm which reconstructs a 3D stack from a 2D measurement, thus removing the out-of-focus light. The acquisition speed in 3D SIM is limited by the axial scanning and sequential focusing. Using a multifocus detection enables to simultaneously acquire a focal series. Merging SIM excitation with multifocus detection (MF-SIM) permits to enhance the volumetric acquisition speed of 3D SIM as well as removing the need for axial mechanical scanning, a source of sample drift and vibrations. The recorded MF-SIM data does not obey the same theoretical description as the conventional scanning 3D SIM data. Hence, the classical approach for 3D SIM reconstruction cannot be applied. We developed a deconvolution-based algorithm using known 3D illumination pattern that can be applied to the reconstruction of MF-SIM data. The results demonstrate enhanced resolution in all three dimensions.Mikroskopie mit strukturierter Beleuchtung (SIM) zählt zu den hochauflösenden Mikroskopieverfahren und erreicht die doppelte Auflösung im Vergleich zur normalen Weitfeldmikroskopie. Bei SIM wird die Probe mit einem Muster – typischerweise einem Lichtgitter - beleuchtet. Dieses Muster entsteht durch die Interferenz zweier oder dreier ebener Wellen. Die nötige Datenverarbeitung der rohen SIM-Bilder führt zu Artefakten wenn das Beleuchtungsmuster unbekannt oder verzerrt ist. Blind-SIM ist ein Entfaltungsbasierter Ansatz, der sowohl die Rekonstruktion der Probe als auch die des Beleuchtungsmusters ermöglicht. Blind-SIM ist fähig, Daten mit völlig oder teilweise unbekanntem Beleuchtungsmuster zu bearbeiten und ist deswegen robust gegenüber Verzerrungen dieser Muster. Thick slice blind-SIM hingegen erzeugt einen 3D Stapel aus einer 2D-Aufnahme. Dadurch ist es in der Lage, Beiträge von Licht außerhalb der Fokusebene zu entfernen. Durch das Zweistrahl-SIM Verfahren lassen sich entweder optisch Probenschnitte erzeugen oder eine Maximierung der lateralen Auflösung erzielen. Eine Kombination mit thick slice blind-SIM ermöglicht beides gleichzeitig. Thick slice blind-SIM zeigt durch die Bearbeitung einer einzelnen ausgewählten Ebene eine vergleichbare Verbesserung des Auflösungsvermögens und der optische Sectioning Fähigkeit wie die 3D Bearbeitung eines 3D aufgenommenen SIM Stapels. Die Aufnahmegeschwindigkeit für 3D SIM ist durch axiales mechanisches Abtasten in Verbindung mit Nachfokussierung begrenzt, wohingegen eine multifokus Detektion die gleichzeitige Aufnahme einer fokalen Serie ermöglicht. Die Kombination von SIM-Anregung und multifokus Detektion (MF-SIM) ermöglicht es, die Aufnahmegeschwindigkeit von 3D SIM zu verbessern. Das MF-SIM Verfahren macht neue Ansätze der Rekonstruktion nötig, wofür sich ein entfaltungsbasierter Algorithmus, welcher auf bekannten 3D-Beleuchtungsmustern beruht, eignet

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

Landscape homogenization due to agricultural intensification disrupts the relationship between reproductive success and main prey abundance in an avian predator

Selecting high-quality habitat and the optimal time to reproduce can increase individual fitness and is a strong evolutionary factor shaping animal populations. However, few studies have investigated the interplay between land cover heterogeneity, limitation in food resources, individual quality and spatial variation in fitness parameters. Here, we explore how individuals of different quality respond to possible mismatches between a cue for prey availability (land cover heterogeneity) and the actual fluctuating prey abundance.Peer reviewe

Optical Sectioning and High Resolution in Single-Slice Structured Illumination Microscopy by Thick Slice Blind-SIM Reconstruction.

The microscope image of a thick fluorescent sample taken at a given focal plane is plagued by out-of-focus fluorescence and diffraction limited resolution. In this work, we show that a single slice of Structured Illumination Microscopy (two or three beam SIM) data can be processed to provide an image exhibiting tight sectioning and high transverse resolution. Our reconstruction algorithm is adapted from the blind-SIM technique which requires very little knowledge of the illumination patterns. It is thus able to deal with illumination distortions induced by the sample or illumination optics. We named this new algorithm thick slice blind-SIM because it models a three-dimensional sample even though only a single two-dimensional plane of focus was measured

Visualization 2: Motion artefact detection in structured illumination microscopy for live cell imaging

3D stack of motion detection processing steps of a floating chloroplast Originally published in Optics Express on 19 September 2016 (oe-24-19-22121

Results of 3D simulation with <i><b>thick slice</b></i> reconstruction.

<p>a) Resolution test target placed in the focal plane of our simulated sample. 800nm out-of-focus was a <i>π</i>/2-rotated version of the same structure. b) 2D WF deconvolution. c) Focal slice of 3D WF deconvolution of the entire WF image stack. d)One of the 9 simulated SIM images. Here we simulate a two-beam SIM. e) 2D blind reconstruction of (d) containing out-of-focus light. f) <i>Thick slice</i> blind-SIM result, showing optical sectioning and high resolution. g-i) Simulation as in a-f) but with a distorted illumination pattern as depicted in g) (zoom). h)Reconstructed illumination function. i) <i>Thick slice</i> blind-SIM reconstruction of the object described in (a) but illuminated with the distorted pattern(g). Scale bar: 2.5 <i>μ</i>m.</p

Experimental results in an MCF-7 actin-labelled cell.

<p>A 200×200 pixels region of interest was selected to keep the computational time small. a) 2D wide-field (WF) deconvolution. b) 2D blind-SIM reconstruction with higher resolution but no optical sectioning. c) 3D WF deconvolution. d) <i>Thick slice</i> blind-SIM result. The resolution is improved and the out-of-focus contribution removed. The green arrows indicate a pair of filaments that is removed because it originally stems from another plane. The processing time was 25 min with GPU vs. 330 min without GPU. e) and f) are the reconstructions of the original 3D data with the ZEN software (version 2010D). e) Plane that was selected. f) Two slices under slice e), i.e. 182 nm away. The sample was prepared by Michael Reuter and data acquired by Elen Tolstik on a commercial ELYRA-S.1 SIM microscope (Carl Zeiss Microimaging, Jena, Germany). Scale bar: 2 <i>μ</i>m.</p

Comparison of the different existing 2D blind-SIM algorithms on a paxillin sample illuminated with a distorted grating.

<p>a) 2D blind-SIM using simultaneous estimation of the object and illumination functions [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132174#pone.0132174.ref016" target="_blank">16</a>]. b) 2D blind-SIM using the proposed method with sequential estimation. For improved comparability, a conjugate gradient scheme was used here. c) 2D WF deconvolution. The scale bar is 1 <i>μ</i>m.</p

Reconstruction parameters.

<p>For each blind-SIM reconstruction, a number of parameters can be tuned. In this table, we summarize the chosen parameters for the presented results. The number of planes corresponds to the number of planes in a double-sided PSF. Using a half-sided PSF, this value is divided by two as the PSF contains each plane only once.</p><p>Reconstruction parameters.</p

Structured illumination fluorescence microscopy with distorted excitations using a filtered blind-SIM algorithm

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