Image Division Technique in Pre-acquisition Analysis of Information Content for Automated Microscopy

BRÁZDILOVÁ, Silvie Luisa and Michal KOZUBEK. Image Division Technique in Pre-acquisition Analysis of Information Content for Automated Microscopy. Journal of Microscopy. Oxford: Blackwell Science, 2011, vol. 242, No 3, p. 279-289. ISSN 0022-2720. Available from: https://dx.doi.org/10.1111/j.1365-2818.2010.03465.x.

Basic information

• Original name: Image Division Technique in Pre-acquisition Analysis of Information Content for Automated Microscopy
• Authors: BRÁZDILOVÁ, Silvie Luisa (203 Czech Republic, belonging to the institution) and Michal KOZUBEK (203 Czech Republic, guarantor, belonging to the institution).
• Edition: Journal of Microscopy, Oxford, Blackwell Science, 2011, 0022-2720.

Other information

• Original language: English
• Type of outcome: Article in a journal
• Field of Study: 20200 2.2 Electrical engineering, Electronic engineering, Information engineering
• Country of publisher: United Kingdom of Great Britain and Northern Ireland
• Confidentiality degree: is not subject to a state or trade secret
• Impact factor: Impact factor: 1.631
• RIV identification code: RIV/00216224:14330/11:00051479
• Organization unit: Faculty of Informatics
• Doi: http://dx.doi.org/10.1111/j.1365-2818.2010.03465.x
• UT WoS: 000290627600006
• Keywords in English: Automated microscopy; fluorescence microscopy; autofocusing; multimodal content function; image acquisition; information content analysis
• Tags: cbia-web
• Tags: International impact, Reviewed

Abstract

This article presents a method that allows for reliable automated image acquisition of specimens with high information content in light microscopy with emphasis on fluorescence microscopy applications. Automated microscopy typically relies on autofocusing used for the analysis of information content behaviour along z-axis within each field of view. However, in the case of a field of view containing more objects that do not lie precisely in one z-plane, traditional autofocusing methods fail due to their principle of operation. We avoid this issue by reducing the original problem to a set of simple and performable tasks: we divide the field of view into a small number of tiles and process each of them individually. The obtained results enable discovering z-planes with rich information content that remain hidden during global analysis of the whole field of view. Our approach therefore outperforms other acquisition methods including the manual one. A large part of the contribution is oriented toward practical application.

Links

• LC535, research and development project: Name: Dynamika a organizace chromosomů během buněčného cyklu v normě a patologii

Investor: Ministry of Education, Youth and Sports of the CR, Dynamika a organizace chromosomů během buněčného cyklu v normě a patologii

• MSM0021622419, plan (intention): Name: Vysoce paralelní a distribuované výpočetní systémy

Investor: Ministry of Education, Youth and Sports of the CR, Highly Parallel and Distributed Computing Systems

• MUNI/A/0914/2009, interní kód MU: Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace (Acronym: SV-FI MAV)

Investor: Masaryk University, Category A

• 2B06052, research and development project: Name: Vytipování markerů, screening a časná diagnostika nádorových onemocnění pomocí vysoce automatizovaného zpracování multidimenzionálních biomedicínských obrazů (Acronym: Biomarker)

Investor: Ministry of Education, Youth and Sports of the CR, Determination of markers, screening and early diagnostics of cancer diseases using highly automated processing of multidimensional biomedical images