显微镜
数字化病理学
免疫组织化学
计算机科学
体视学
图像分析
病理
人工智能
数字图像
图像处理
医学
图像(数学)
作者
Paul C. Goodwin,Brian Johnson,Charles W. Frevert
出处
期刊:Elsevier eBooks
[Elsevier]
日期:2017-09-16
卷期号:: 53-66
被引量:11
标识
DOI:10.1016/b978-0-12-802900-8.00004-x
摘要
Advances in microscopy including improvements in objectives, light sources, computational power, and digital cameras, with the ability to obtain images of regions of interest or whole slides, have led to the resurgence of the light microscope in biomedical research. Similarly, advances in immunohistochemistry (IHC), such as heat-induced epitope retrieval, have increased the use of this technique to obtain important information about specific molecules in tissues. Finally, advances in digital pathology and software programs that objectively analyze digital images has resulted in the increased use of quantitative microscopy—either stereology or image analysis—to efficiently obtain data from studies using histopathology or IHC. The goal of this chapter is to provide the fundamental information required to successfully use microscopy, IHC, and quantitative microscopy to obtain objective nonbiased data from histology sections.
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