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

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Jon Sporring, Mahdieh Khanmohammadi, Sune Darkner, Nicoletta Nava, Jens Randel Nyengaard, Eva B. 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 the 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 we give an extremely simple, linear algorithm. Our algorithm is applied to the challenging domain of electron microscopic sections supposedly $45\text{ nm}$ apart, and we show that these images with high certainty belong to the required statistical class, and that the reconstructions are valid.
OriginalsprogEngelsk
Titel2014 IEEE International Symposium on Biomedical Imaging
Antal sider4
ForlagIEEE
Publikationsdato2014
Sider157-160
ISBN (Elektronisk)978-1-4673-1959-1
DOI
StatusUdgivet - 2014
BegivenhedInternational Symposium on Biomedical Imaging - Beijing, Kina
Varighed: 28 apr. 20142 maj 2014

Konference

KonferenceInternational Symposium on Biomedical Imaging
LandKina
ByBeijing
Periode28/04/201402/05/2014

ID: 161621598