Overview
- Editors:
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Jan SlavĂk
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Institute of Physiology, Czech Academy of Sciences, Prague, Czech Republic
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Table of contents (46 chapters)
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Digital Image Analysis
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- Hanna Tinel, Frank Wehner, Rolf K. H. Kinne
Pages 273-277
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- Denis Demandolx, Jean Davoust
Pages 279-283
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- Lucie KubĂnová, Marie Jirkovská, Petr Hach, Daniel Palouš, Petr Karen, Ivan Krekule
Pages 285-289
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- Werner J. H. Koopman, Bruce G. Jenks, Eric W. Roubos, Wim J. J. M. Scheenen
Pages 291-295
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- B. R. Terry, E. K. Matthews
Pages 297-301
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Back Matter
Pages 303-306
About this book
Fluorescence microscopy images can be easily integrated into current video and computer image processing systems. People like visual observation; they like to watch a television or computer screen, and fluorescence techniques are thus becoming more and more popular. Since true in vivo experiments are simple to perform, samples can be directly seen and there is always the possibility of manipulating the samples during the experiments; it is an ideal technique for biology and medicine. Images are obtained by a classical (now called wide-field) fluorescence microscope, a confocal scanning microscope, upright or inverted, with epifluorescence or transmission. Computerized image processing may improve definition, and remove glare and scattered light signal. It also makes it possible to compute ratio images (ratio imaging both in excitation and in emission) or lifetime imaging. Image analysis programs may supply a great deal of additional data of various types, starting with calculations of the number of fluorescent objects, their shapes, brightness, etc. Fluorescence microscopy data may be complemented by classical measurement in the cuvette yr by flow cytometry.
Editors and Affiliations
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Institute of Physiology, Czech Academy of Sciences, Prague, Czech Republic
Jan SlavĂk