Optical microscopy has vastly expanded the frontiers of structural and functional biology, due to the non-invasive probing of dynamic volumes in vivo. However, traditional widefield microscopy illuminating the entire field of view (FOV) is adversely affected by out-of-focus light scatter. Consequently, standard upright or inverted microscopes are inept in sampling diffraction-limited volumes smaller than the optical system’s point spread function (PSF). Over the last few decades, several planar and structured (sinusoidal) illumination modalities have offered unprecedented access to sub-cellular organelles and 4D (3D + time) image acquisition. Furthermore, these optical sectioning systems remain unaffected by the size of biological samples, providing high signal-to-noise (SNR) ratios for objective lenses (OLs) with long working distances (WDs). This review aims to guide biologists regarding planar illumination strategies, capable of harnessing sub-micron spatial resolution with a millimeter depth of penetration.
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Novel Image Processing to Restore Scattered Light-sheet Microscopic Imaging Technique and its Application for Quantifying Biomechanics
Research of cellular and molecular processes by way of histological methods allows for some insight but comes with a fundamental set of constraints that are challenging to overcome. Traditional histological methods are laborious, as well as severely limiting for in-depth study of developmental processes or disease processes in vivo. In traditional histology, fixing and sectioning tissue necessarily eliminates its dynamic function, while tissue section thickness limits the scope of investigation with conventional imaging tools. Noninvasive in vivo study of tissues and biomarkers is therefore paramount in gaining a fuller understanding of the pathophysiology surrounding conditions like congenital heart disorders. Light-sheet fluorescence microscopy (LSFM) is a powerful and noninvasive optical microscopy tool that can image in vivo tissue function in 4D (3D + time). LSFM boasts benefits such as short pixel dwell time (and therefore minimal photobleaching) while maintaining the ability to image a high dynamic range, as well as deep-tissue optical sectioning. Researchers have been seeking to overcome this problem by developing tissue-clearing techniques to attempt to homogenize the refractive index across the tissue via the removal of light-scattering pigments and lipids.
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- Award ID(s):
- 1936519
- PAR ID:
- 10498262
- Publisher / Repository:
- River Publishers
- Date Published:
- ISBN:
- 9788770223799
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Background Structured illumination microscopy (SIM) is a family of methods in optical fluorescence microscopy that can achieve both optical sectioning and super-resolution effects. SIM is a valuable method for high-resolution imaging of fixed cells or tissues labeled with conventional fluorophores, as well as for imaging the dynamics of live cells expressing fluorescent protein constructs. In SIM, one acquires a set of images with shifting illumination patterns. This set of images is subsequently treated with image analysis algorithms to produce an image with reduced out-of-focus light (optical sectioning) and/or with improved resolution (super-resolution). Findings Five complete, freely available SIM datasets are presented including raw and analyzed data. We report methods for image acquisition and analysis using open-source software along with examples of the resulting images when processed with different methods. We processed the data using established optical sectioning SIM and super-resolution SIM methods and with newer Bayesian restoration approaches that we are developing. Conclusions Various methods for SIM data acquisition and processing are actively being developed, but complete raw data from SIM experiments are not typically published. Publically available, high-quality raw data with examples of processed results will aid researchers when developing new methods in SIM. Biologists will also find interest in the high-resolution images of animal tissues and cells we acquired. All of the data were processed with SIMToolbox, an open-source and freely available software solution for SIM.more » « less
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