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From 3-D Light Microscopic Images to Quantitative Insight

Published online by Cambridge University Press:  02 July 2020

B. Roysam
Affiliation:
Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY12180 Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY12180
A. Can
Affiliation:
Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY12180
H. Shen
Affiliation:
Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY12180
K. Al-Kofahi
Affiliation:
Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY12180
J.N. Turner
Affiliation:
Wadsworth Center, New York State Department of Health, Albany, NY12201
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This presentation will describe a common core set of widely applicable image analysis techniques for automated quantitative analysis of volumetric microscope image data. Volumetric (as distinct from stereoscopic) three-dimensional (3-D) Microscopy is a rapidly maturing field offering the ability to image thick (compared to the depth of field) specimens using a variety of instrumentation techniques, and producing arrays of brightness values in three spatial dimensions. Also well developed are methods to correct the acquired images for a variety of physical effects including blur and attenuation.

Commonly, what is of interest is the best-possible visualization of thick specimens. The next step, increasingly being considered in view of growing computational resources, and progress in image analysis techniques, seeks to quantify many of the processes and effects being studied. In some mainstream fields, such quantitation is essential. For instance, various assays for substance testing in pharmaceutical and chemical industries involve quantitative end points. As an illustration, the Draize assay for ocular irritancy testing of drugs and biochemical products for human use requires counting of live and dead cells that stain differently. Another example is the mouse lymphoma test that requires a 3-D counting of bacterial colonies. Neurobiological assays require morphometry, as well as quantification of changes in neurons as a function of time and various applied stimuli such as drugs, heat, and radiation. Angiogenesis assays require quantification of changes in vascular morphometry. Computerized image analysis is a powerful tool for extracting quantitative data from 3-D images for statistical analysis.

Type
From 3-D Light Microscopic Images to Quantitative Insight
Copyright
Copyright © Microscopy Society of America

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References

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5. Supported by Procter and Gamble Co., Covance Co., and The Wadsworth Center.Google Scholar