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Artifact-free whole-slide imaging with structured illumination microscopy and Bayesian image reconstruction.
Johnson, Karl A; Hagen, Guy M.
Afiliação
  • Johnson KA; UCCS BioFrontiers Center, University of Colorado at Colorado Springs, 1420 Austin Bluffs Parkway, Colorado Springs, CO 80918, USA.
  • Hagen GM; UCCS BioFrontiers Center, University of Colorado at Colorado Springs, 1420 Austin Bluffs Parkway, Colorado Springs, CO 80918, USA.
Gigascience ; 9(4)2020 04 01.
Article em En | MEDLINE | ID: mdl-32285910
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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Teorema de Bayes / Imageamento Tridimensional Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Gigascience Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Teorema de Bayes / Imageamento Tridimensional Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Gigascience Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos