Automatic Growth Detection of Cell Cultures through Outlier Techniques using 2D Images

Using conventional statistics, we have developed a new method for cell culture analysis through outlier detection techniques. Statistical methods enable researchers in microbiology to identify experimental parameters that are critical for colony growth and inhibition. This paper reports a method for analysing 2D images of cell cultures in Petri dishs, such as fungi, bacteria or yeast. The aim of this study was to obtain a sensitive and robust method for detection of growth rate, surface coverage and the approximate number of cells in the colony. For testing we have implemented a software application called MoldATRIX. This software generates useful statistics and displays critical information about the cell colony area. Our results were obtained by analyzing a series of digital images of Aspergillus niger cultures at different time intervals. Moreover, our results show the behavior of Aspergillus niger on leather.Â