Enhancement of tissue sample previsualization for digital microscopy

M. Hegedüs, V. S. Varga, B. Molnár

Research output: Contribution to journalArticle

1 Citation (Scopus)


High-resolution scanning of the slides can be optimized based on tissue localization using low-resolution overview images in digital microscopy. Automatic preview image processing and tissue mapping can fail due to lack of sufficient image contrast in case of samples without visible dyes, e.g. for fluorescent samples or for samples prior to staining. We investigated the use of alternative imaging/illumination solutions (e.g. phase contrast, Schlieren, dark field). After examination of the Mie light scattering properties of tissue samples we developed and tested a method for the dark field preview illumination of glass slides based on our results. This solution proved to be well suited even for hydrated tissue samples prior to coverslipping and staining of any kind. Optimization of the staining procedure is also possible based on these overview images of the sample. Nevertheless, in the case of archived and contaminated slides tissue, dust and fingerprints were imaged with equal intensities. Therefore we proposed an off-axis thin line dark field illumination. This approach makes the separation of the images from different planes along the optical axis possible. Thus light scattered on the bottom of the glass slide, on the sample plane and on the surface of the coverslip is projected onto different pixels of the camera sensor and can be discriminated. We designed a compact light source and control program for testing this design and showed how the image of the tissue sample can be reconstructed from a series of pictures with minimizing the effect of contamination artifacts.

Original languageEnglish
Pages (from-to)629-631
Number of pages3
JournalIFMBE Proceedings
Publication statusPublished - Nov 9 2011


  • dark field illumination
  • digital microscopy
  • slide preview
  • virtual pathology

ASJC Scopus subject areas

  • Bioengineering
  • Biomedical Engineering

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