Image Division Technique in Automated Fluorescence Microscopy with Complex Content

BRÁZDILOVÁ, Silvie Luisa and Michal KOZUBEK. Image Division Technique in Automated Fluorescence Microscopy with Complex Content. In PROCEEDINGS OF THE IADIS INTERNATIONAL CONFERENCE COMPUTER GRAPHICS, VISUALIZATION, COMPUTER VISION AND IMAGE PROCESSING 2010. 2010th ed. Freiburg, Germany: International Association for Development of the Information Society, 2010, p. 176-183. ISBN 978-972-8939-22-9.

Basic information

• Original name: Image Division Technique in Automated Fluorescence Microscopy with Complex Content
• Name in Czech: Použití metody dělení obrazu v automatické fluorescenční mikroskopii s bohatou obsahovou funkcí
• Authors: BRÁZDILOVÁ, Silvie Luisa (203 Czech Republic, belonging to the institution) and Michal KOZUBEK (203 Czech Republic, guarantor, belonging to the institution).
• Edition: 2010. vyd. Freiburg, Germany, PROCEEDINGS OF THE IADIS INTERNATIONAL CONFERENCE COMPUTER GRAPHICS, VISUALIZATION, COMPUTER VISION AND IMAGE PROCESSING 2010, p. 176-183, 8 pp. 2010.
• Publisher: International Association for Development of the Information Society

Other information

• Original language: English
• Type of outcome: Proceedings paper
• Field of Study: 10201 Computer sciences, information science, bioinformatics
• Country of publisher: Germany
• Confidentiality degree: is not subject to a state or trade secret
• Publication form: printed version "print"
• RIV identification code: RIV/00216224:14330/10:00067194
• Organization unit: Faculty of Informatics
• ISBN: 978-972-8939-22-9
• Keywords (in Czech): Automatická mikroskopie; fluorescenční mikroskopie; obsahová funkce s více extrémy; pořizování obrazu
• Keywords in English: Automated microscopy; fluorescence microscopy; multimodal content function; image acquisition
• Tags: automated microscopy, biomedical image, fluorescence microscopy, information content analysis
• Tags: International impact, Reviewed

Abstract

This paper presents a method that allows for reliable automated acquisition of images in fluorescence microscopy. Specifically, if an image contains more objects that do not lie precisely in one z-plane, traditional methods necessarily fail due to their principle of operation. We take a different approach by reducing the original problem to a set of tasks which can already be easily solved. Namely, we divide the original image into a few subparts and process each of them individually. The results obtained in such a way enable discovering hidden z-planes with rich information content. Our approach therefore outperforms other acquisition methods including manual one. A large part of the paper is devoted to practical examples and suggestions.

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