Jens Randel Nyengaard

Estimating the thickness of ultra thin sections for electron microscopy by image statistics

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperConference articleResearchpeer-review

  • Jon Sporring, University of Copenhagen
  • ,
  • Mahdieh Khanmohammadi, University of Copenhagen
  • ,
  • Sune Darkner, University of Copenhagen
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  • Nicoletta Nava, Stereology & Electron Microscopy Laboratory, Centre for Stochastic Geometry and Advanced Bioimaging, Aarhus University Hospital, Aarhus, Denmark.
  • ,
  • Jens Randel Nyengaard
  • Eva Bjørn Vedel Jensen

We propose a method for estimating the thickness of ultra thin histological sections by image statistics alone. Our method works for images, that are realisations of a stationary and isotropic stochastic process, and it relies on the existence of statistical image-measures that are strictly monotonic with distance. We propose to use the standard deviation of the difference between pixel values as a function of distance, and give an extremely simple, linear algorithm. Our algorithm is applied to the challenging domain of electron microscopic sections supposedly 45 nm apart, and we show that these images with high certainty belong to the required statistical class, and that the reconstructions are valid.

Original languageEnglish
Journal2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Pages (from-to)157-160
Number of pages4
Publication statusPublished - 29 Jul 2014
Event2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 - Beijing, China
Duration: 29 Apr 20142 May 2014


Conference2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
SponsorIEEE Engineering in Medicine and Biology Society (EMBS), IEEE Signal Processing Society (SPS)

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ID: 156880396