A comparison of methods for optical sectioning using structured illumination microscopy

2013 ◽  
Author(s):  
Benjamin Thomas ◽  
Michelle Momany ◽  
Peter Kner
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.


2014 ◽  
Vol 20 (S3) ◽  
pp. 388-389
Author(s):  
Zdeněk Švindrych ◽  
Pavel Křížek ◽  
Evgeny Smirnov ◽  
Martin Ovesný ◽  
Josef Borkovec ◽  
...  

2020 ◽  
Vol 28 (8) ◽  
pp. 10919 ◽  
Author(s):  
Wei Zhang ◽  
Bin Yu ◽  
Danying Lin ◽  
Huanhuan Yu ◽  
Siwei Li ◽  
...  

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.


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