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This is a matlab function that allows to analyze scratch wound healing assay images. A scratch wound healing assay (http://www.nature.com/nprot/journal/v2/n2/full/nprot.2007.30.html) is a simple in-vitro test that evaluates the invasive capabilities of an eukaryotic cell culture.
It consists in creating a "wound" in a confluent cell culture using a pipette tip and then monitoring over time the cell's growth through bright field microscopy. The area reduction over time is a measure of how invasive is the corresponding cell culture.
Cell-Invasiv-o-Meter is a matlab function that identifies, segments and computes the area of the wound (in pixels). The empty region is recognized by computing the local entropy image, that is then segmented with the Otsu method.
- MATLAB and Image Processing Toolbox, The MathWorks, Inc., Natick, Massachusetts, United States.
- imoverlay (http://www.mathworks.com/matlabcentral/fileexchange/42904-imoverlay)
- [file, path]= CellInvasivOMeter(folderImages)
- [file, path]= CellInvasivOMeter(folderImages, kernelDim)
- [file, path]= CellInvasivOMeter(folderImages, woundPrevalence)
- [file, path]= CellInvasivOMeter(folderImages,kernelDim, woundPrevalence)
Where folderImages is a string representing the path of the folder in which the images are stored (Cell-Invasiv-o-Meter hyposizes a different folder for every time point and experimental condition). kernelDim is the dimension of the kernel used during the computation of the local entropy (size of neighbourhood); the default value is 45 and it needs to be an odd number. woundPrevalence is the percentage of the empty area attributed to the wound and is necessary to exclude small holes outside the wound (it is a number between 0 and 1 and the default value is 0.7). The images are expected to be in .tif format, if you want to use a different format modify accordingly the line number 40 of the function's code.
The workspace containing the results of the elaboration is automatically saved as a .mat file, a dialog window will automatically appear allowing the user to set the file's name and its destination. The mean area of the wound (average of the technical replicates) and the corresponding standard deviation are even printed in the command window.
In this image is summarized the functioning of Cell-Invasiv-o-Meter, in the upper row there are the raw image (on the left) and the corresponding local entropy image (on the right). While in the lower row are reported the histogram of the entropy image and the final result in which the wound area is identified in red.