Artifact-free whole-slide imaging with structured illumination microscopy and Bayesian image reconstruction
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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.
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Now published in GigaScience doi: 10.1093/gigascience/giaa035
Karl Johnson 1UCCS center for the Biofrontiers Institute, University of Colorado at Colorado Springs 1420 Austin Bluffs Parkway, Colorado Springs, Colorado, 80918, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteGuy M. Hagen 1UCCS center for the Biofrontiers Institute, University of Colorado at Colorado Springs 1420 Austin Bluffs Parkway, Colorado Springs, Colorado, 80918, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for Guy M. HagenFor correspondence: ghagen@uccs.edu
A version of this preprint has been published in the Open Access journal GigaScience (see paper https://doi.org/10.1093/gigascience/giaa035 ), where the paper and peer reviews are published …
Now published in GigaScience doi: 10.1093/gigascience/giaa035
Karl Johnson 1UCCS center for the Biofrontiers Institute, University of Colorado at Colorado Springs 1420 Austin Bluffs Parkway, Colorado Springs, Colorado, 80918, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteGuy M. Hagen 1UCCS center for the Biofrontiers Institute, University of Colorado at Colorado Springs 1420 Austin Bluffs Parkway, Colorado Springs, Colorado, 80918, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for Guy M. HagenFor correspondence: ghagen@uccs.edu
A version of this preprint has been published in the Open Access journal GigaScience (see paper https://doi.org/10.1093/gigascience/giaa035 ), where the paper and peer reviews are published openly under a CC-BY 4.0 license.
These peer reviews were as follows:
Reviewer 1: http://dx.doi.org/10.5524/REVIEW.102185 Reviewer 2: http://dx.doi.org/10.5524/REVIEW.102186 Reviewer 3: http://dx.doi.org/10.5524/REVIEW.102187
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