Simultaneous optical sectioning and super resolution in 2D-SIM using tunable structured illumination

Author(s):  
Hasti Shabani ◽  
Ana Doblas ◽  
Chrysanthe Preza
GigaScience ◽  
2020 ◽  
Vol 9 (4) ◽  
Author(s):  
Karl A Johnson ◽  
Guy M Hagen

Abstract Background Structured illumination microscopy (SIM) is a method that can be used to image biological samples and can achieve both optical sectioning and super-resolution effects. Optimization of the imaging set-up and data-processing methods results in high-quality images without artifacts due to mosaicking or due to the use of SIM methods. Reconstruction methods based on Bayesian estimation can be used to produce images with a resolution beyond that dictated by the optical system. Findings Five complete datasets are presented including large panoramic SIM images of human tissues in pathophysiological conditions. Cancers of the prostate, skin, ovary, and breast, as well as tuberculosis of the lung, were imaged using SIM. The samples are available commercially and are standard histological preparations stained with hematoxylin-eosin. Conclusion The use of fluorescence microscopy is increasing in histopathology. There is a need for methods that reduce artifacts caused by the use of image-stitching methods or optical sectioning methods such as SIM. Stitched SIM images produce results that may be useful for intraoperative histology. Releasing high-quality, full-slide images and related data will aid researchers in furthering the field of fluorescent histopathology.


2018 ◽  
Author(s):  
Jakub Pospíšil ◽  
Tomáš Lukeš ◽  
Justin Bendesky ◽  
Karel Fliegel ◽  
Kathrin Spendier ◽  
...  

AbstractBackgroundStructured 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).FindingsFive complete and 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 which we are developing.ConclusionVarious methods for SIM data acquisition and processing are actively being developed, but complete raw data from SIM experiments is not typically published. Publicly 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 was processed with SIMToolbox, an open source and freely available software solution for SIM.


2019 ◽  
Author(s):  
Karl Johnson ◽  
Guy M. Hagen

AbstractBackgroundStructured illumination microscopy (SIM) is a method which can be used to image biological samples and can achieve both optical sectioning and super-resolution effects. Optimization of the imaging setup and data processing methods results in high quality images without artifacts due to mosaicking or due to the use of SIM methods. Reconstruction methods based on Bayesian estimation can be used to produce images with a resolution beyond that dictated by the optical system.FindingsFive complete datasets are presented including large panoramic SIM images of human tissues in pathophysiological conditions. Cancers of the prostate, skin, ovary, and breast, as well as tuberculosis of the lung, were imaged using SIM. The samples are available commercially and are standard histological preparations stained with hematoxylin and eosin.ConclusionThe use of fluorescence microscopy is increasing in histopathology. There is a need for methods which reduce artifacts when employing image stitching methods or optical sectioning methods such as SIM. Stitched SIM images produce results which may be useful for intraoperative histology. Releasing high quality, full slide images and related data will aid researchers in furthering the field of fluorescent histopathology.


2020 ◽  
Vol 54 (7) ◽  
pp. 074004
Author(s):  
Dan Dan ◽  
Peng Gao ◽  
Tianyu Zhao ◽  
Shipei Dang ◽  
Jia Qian ◽  
...  

2015 ◽  
Vol 23 (4) ◽  
pp. 5327 ◽  
Author(s):  
Peter W. Winter ◽  
Panagiotis Chandris ◽  
Robert S Fischer ◽  
Yicong Wu ◽  
Clare M Waterman ◽  
...  

2021 ◽  
Author(s):  
Haoran Wang ◽  
Réne Lachmann ◽  
Barbora Marsikova ◽  
Rainer Heinzmann ◽  
Benedict Diederich

State-of-the-art microscopy techniques enable the imaging of sub-diffraction barrier biological structures at the price of high-costs or lacking transparency. We try to reduce some of these barriers by presenting a super-resolution upgrade to our recently presented open-source optical toolbox UC2. Our new injection moulded parts allow larger builds with higher precision. The 4x lower manufacturing tolerance compared to 3D printing makes assemblies more reproducible. By adding consumer-grade available open-source hardware such as digital mirror devices (DMD) and laser projectors we demonstrate a compact 3D multimodal setup that combines image scanning microscopy (ISM) and structured illumination microscopy (SIM). We demonstrate a gain in resolution and optical sectioning using the two different modes compared to the widefield limit by imaging Alexa Fluor 647- and SiR-stained HeLa cells. We compare different objective lenses and by sharing the designs and manuals of our setup, we make super-resolution imaging available to everyone.


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