## Abstract Modern microscopic techniques like high‐content screening (HCS), high‐throughput screening, 4D imaging, and multispectral imaging may involve collection of thousands of images per experiment. Efficient image‐compression techniques are indispensable to manage these vast amounts of data.
Signal to noise analysis of multiple color fluorescence imaging microscopy
✍ Scribed by Y. Garini; A. Gil; I. Bar-Am; D. Cabib; N. Katzir
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 656 KB
- Volume
- 35
- Category
- Article
- ISSN
- 0196-4763
No coin nor oath required. For personal study only.
✦ Synopsis
Background: Various approaches that were recently developed demonstrate the ability to simultaneously detect all human (or other species) chromosomes by using combinatorial labeling and fluorescence in situ hybridization (FISH). With the growing interest in this field, it is important to develop tools for optimizing and estimating the accuracy of different experimental methods. Methods: We have analyzed the principles of multiple color fluorescence imaging microscopy. First, formalism based on the physical principles of fluorescence microscopy and noise analysis is introduced. Next, a signal to noise (S/N) analysis is performed and summarized in a simple accuracy criterion. The analysis assumes shot noise to be the dominant source of noise.
Results:
The accuracy criterion was used to calculate the S/N of multicolor FISH (M-FISH), spectral karyotyping, ratio imaging, and a method based on using a set of broad band filters. Spectral karyotyping is tested on various types of samples and shows accurate classifications. We have also tested classification accuracy as a function of total measurement time.
Conclusions:
The accuracy criterion that we have developed can be used for optimizing and analyzing different multiple color fluorescence microscopy methods. The assumption that shot noise is dominant in these measurements is supported by our measurements. Cytometry
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