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

Jon Sporring; Mahdieh Khanmohammadi; Sune Darkner; Nicoletta Nava; Jens Randel Nyengaard; Eva B. Vedel Jensen

doi:10.1109/ISBI.2014.6867833

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

Jon Sporring, Mahdieh Khanmohammadi, Sune Darkner, Nicoletta Nava, Jens Randel Nyengaard, Eva B. Vedel Jensen

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

5 Citationer (Scopus)

Abstract

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.

Originalsprog	Engelsk
Titel	2014 IEEE International Symposium on Biomedical Imaging
Antal sider	4
Forlag	IEEE
Publikationsdato	2014
Sider	157-160
ISBN (Elektronisk)	978-1-4673-1959-1
DOI	https://doi.org/10.1109/ISBI.2014.6867833
Status	Udgivet - 2014
Begivenhed	International Symposium on Biomedical Imaging - Beijing, Kina Varighed: 28 apr. 2014 → 2 maj 2014

Konference

Konference	International Symposium on Biomedical Imaging
Land/Område	Kina
By	Beijing
Periode	28/04/2014 → 02/05/2014

Adgang til dokumentet

10.1109/ISBI.2014.6867833

Citationsformater

Estimating the thickness of ultra thin sections for electron microscopy by image statistics. / Sporring, Jon; Khanmohammadi, Mahdieh; Darkner, Sune; Nava, Nicoletta; Nyengaard, Jens Randel; Jensen, Eva B. Vedel.

2014 IEEE International Symposium on Biomedical Imaging. IEEE, 2014. s. 157-160.

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

Sporring, J, Khanmohammadi, M, Darkner, S, Nava, N, Nyengaard, JR & Jensen, EBV 2014, Estimating the thickness of ultra thin sections for electron microscopy by image statistics. i 2014 IEEE International Symposium on Biomedical Imaging. IEEE, s. 157-160, International Symposium on Biomedical Imaging, Beijing, Kina, 28/04/2014. https://doi.org/10.1109/ISBI.2014.6867833

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AU - Nyengaard, Jens Randel

AU - Jensen, Eva B. Vedel

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AB - 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.

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