Package 'LFApp'

Shiny Apps for Lateral Flow Assays.

Description

Shiny apps for the quantitative analysis of images from lateral flow assays (LFAs). The images are segemented and background corrected and color intensities are extracted. The apps can be used to import and export intensity data and to calibrate LFAs by means of linear, loess, or gam models. The calibration models can further be saved and applied to intensity data from new images for determining concentrations.

Details

library(LFApp)

Author(s)

Filip Paskali, Weronika Schary, Matthias Kohl

Maintainer: Filip Paskali [email protected]

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Run Analysis Shiny Apps

Description

Function start the Analysis Shiny App.

Usage

run_analysis()
run_cal()
run_core()
run_quan()
run_mobile_analysis()
run_mobile_cal()
run_mobile_core()
run_mobile_quan()

Details

The functions start the various shiny apps included in the package.

Value

An object that represents the app. Printing the object will run the app.

Author(s)

Filip Paskali [email protected], Weronika Schary [email protected], Matthias Kohl [email protected]

Examples

if(interactive()){
  ## start full analysis app
  run_analysis()
  ## start mobile version of full analysis app
  run_mobile_analysis()
}

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Li Thresholding Algorithm

Description

The function computes a background theshold of an image by using Li's iterative minimum cross entropy method.

Usage

threshold_li(image, tolerance = NULL, initial_guess = NULL, iter_callback = NULL)

Arguments

image	object of class Image from package EBImage.
tolerance	optional tolerance threshold.
initial_guess	optional initial value for the minimization.
iter_callback	optional function applied to the minimizsation criterion.

Details

For more details about the method see Li and Lee (1993) as well as Li and Tam (1998).

Value

numeric vector with the computed threshold.

Author(s)

Filip Paskali [email protected]

References

C.H. Li and C.K. Lee (1993). Minimum cross entropy thresholding. Pattern Recognition 26 (4): 617-25. https://doi.org/10.1016/0031-3203(93)90115-D.

C.H. Li and P.K.S. Tam (1998). An iterative algorithm for minimum cross entropy thresholding. Pattern Recognition Letters 19 (8): 771-76. https://doi.org/10.1016/S0167-8655(98)00057-9.

Examples

library(EBImage)
x <- readImage(system.file("images", "sample.TIF", package="LFApp"))
threshold_li(x)

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Triangle Thresholding Algorithm

Description

The function computes a background theshold of an image using the triangle algorithm.

Usage

triangle(image, offset = 0.2, breaks = 256)

Arguments

image	object of class Image from package EBImage.
offset	numeric, additional offset added to the computed threshold.
breaks	integer, number of breaks used in the histogram.

Details

The Triangle method is based on the histogram of the intensities. Based on the range of intensities and the maximum peak a threshold is determined. The method was proposed in Zack et al. (1977).

Value

numeric vector with the computed threshold.

Author(s)

Matthias Kohl [email protected]

References

G.W. Zack, W. E. Rogers, and S. A. Latt (1977). Automatic measurement of sister chromatid exchange frequency. The journal of histochemistry and cytochemistry: official journal of the Histochemistry Society 25 (7): 741-53. https://doi.org/10.1177/25.7.70454.

Examples

library(EBImage)
x <- readImage(system.file("images", "sample.TIF", package="LFApp"))
triangle(x)

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