Image analysis
Dotaz
Zobrazit nápovědu
sv.
- MeSH
- histologické techniky MeSH
- počítačové zpracování obrazu MeSH
- Publikační typ
- periodika MeSH
- Konspekt
- Buněčná biologie. Cytologie
- NLK Obory
- cytologie, klinická cytologie
- histologie
elektronický časopis
Image analysis & stereology, ISSN 1580-3139 vol. 21, suppl. 1, December 2002
SIX, S97 s. : il., tab., grafy ; 30 cm
- MeSH
- algoritmy MeSH
- automatizované zpracování dat MeSH
- mikroskopie metody trendy MeSH
- počítačové zpracování obrazu normy MeSH
- software MeSH
- Publikační typ
- přehledy MeSH
This chapter gives examples of basic procedures of quantification of plant structures with the use of image analysis, which are commonly employed to describe differences among experimental treatments or phenotypes of plant material. Tasks are demonstrated with the use of ImageJ, a widely used public domain Java image processing program. Principles of sampling design based on systematic uniform random sampling for quantitative studies of anatomical parameters are given to obtain their unbiased estimations and simplified "rules of thumb" are presented. The basic procedures mentioned in the text are (1) sampling, (2) calibration, (3) manual length measurement, (4) leaf surface area measurement, (5) estimation of particle density demonstrated on an example of stomatal density, and (6) analysis of epidermal cell shape.
Článek se zabývá úlohou obrazového materiálu v dokumeniaci lékařského nálezu. Popisuje funkci programu GastroBase, litery je primárně určen pro dokumentaci gasíroenterologické ambulance a endoskopických pracovišť. Nejnovější verze programu GastroBase již práci s obrazovou dokumentací umožňuje.
The paper deals with images in medical documentation. The program GastroBase is described that primary serves for documentation in gastroenterology ambulance and endoscopic workplaces. The last version of the program GastroBase makes possible to include also image documentation.
Biosignal, ISSN 1211-412X vol. 19
1 CD ROM ; 13 cm
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 the 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 towards practical application.
