Book chapter
[11] - Image Analytic Techniques for Quantification of Immunohistochemical Staining in the Nervous System
Methods in Neurosciences, pp 208-229
1990
Abstract
Image analysis is a set of techniques that permit the investigator to obtain quantitative information from morphological preparations. When used properly, quantitative image analysis of histological sections is a powerful tool that is capable of providing meaningful data and is sensitive to subtle alterations in tissue staining characteristics. However, when used improperly, image analysis can produce erroneous results. As the techniques used in image analysis are highly dependent on computer processing, many of these errors can be introduced inadvertently, with profound results. This chapter provides an investigator with the baseline knowledge regarding image analytic techniques that can be used to maximize the amount of information resulting from the analysis and to minimize the magnitude of error. The chapter further assists a scientist who has little or no previous experience with image analytic methodologies to understand the essential steps that should be carried out in the quantitative analysis of immunohistochemically stained material and provides the rudiments of the theoretical basis for each of these steps. A number of different hardware configurations have been employed for image analysis, including scanning densitometry, drum densitometry, and video-based densitometry. The latter configuration is now the most widely used for a number of reasons, including flexibility and cost. The chapter discusses only video-based image analysis systems.
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166 citations in Scopus
Details
- Title
- [11] - Image Analytic Techniques for Quantification of Immunohistochemical Staining in the Nervous System
- Creators
- Arnold J. Smolen
- Publication Details
- Methods in Neurosciences, pp 208-229
- Publisher
- Elsevier
- Number of pages
- 22
- Resource Type
- Book chapter
- Language
- English
- Academic Unit
- MD (Doctor of Medicine) Program
- Scopus ID
- 2-s2.0-85012748571
- Other Identifier
- 991021961108304721