2019
DOI: 10.1016/j.mimet.2019.105717
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Development and validation of an alternative parameter for quantification of signals emitted by fluorescently labelled bacteria in microscopic images

Abstract: In this study, an alternative parameter for quantifying the signals of fluorescently labelled bacteria (e.g. propidium iodide, Cyanine 3, etc.) in microscopic images was investigated. Three common parameters (mean grey value (MGV), mean grey value which is corrected for the background (MGVcwB) and the signal to background ratio (SBR) per bacterial cell) are used as reference parameters. As an alternative, the coefficient of variation (CV) is defined as the ratio of the logarithm of the standard deviation and t… Show more

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Cited by 5 publications
(4 citation statements)
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“…The CV is the ratio of the standard deviation to the average value, and its magnitude is related to the repeatability of the experiment. Lower CV values indicate less variation in the mean and better repeatability of the experiment [38]. When the CV was less than 10%, the model accuracy was high [39].…”
Section: Discussionmentioning
confidence: 99%
“…The CV is the ratio of the standard deviation to the average value, and its magnitude is related to the repeatability of the experiment. Lower CV values indicate less variation in the mean and better repeatability of the experiment [38]. When the CV was less than 10%, the model accuracy was high [39].…”
Section: Discussionmentioning
confidence: 99%
“…The results of ANOVA demonstrated that the extraction time and extraction power (BD) had a significant (p < 0.05) negative effect on the comprehensive evaluation value ( Table 1). The coefficient of variation (CV) is defined as the quotient of standard deviation and mean value [36,37]. CV was used for analyzing the statistical data.…”
Section: Discussionmentioning
confidence: 99%
“…This application produced approximately 150 microscopic fluorescence images (in Z-direction) at a magnification of 200x from which visual recognizable objects were isolated by a computer vision algorithm. Morphometric parameters (n = 20, including shape, area, roundness, brightness and number of spots) are calculated per object [ 22 ]. The morphometric parameter scores were subsequently entered in the neural network of the SARS-CoV-2 application, resulting in an autonomous generated test result for SARS-CoV-2 (positive or negative).…”
Section: Methodsmentioning
confidence: 99%