Automated segmentation of cell structure in microscopy images

Understanding cell movement is important in helping to prevent and cure damage and disease. Increasingly, this study is performed by obtaining video footage of cells in vitro. However, as the number of images obtained for cellular analysis increases, so does the need for automated segmentation of these images, since this is difficult and time consuming to perform manually. We propose to automate the process of segmenting all parts of a cell visible in DIC microscopy video frames by providing an efficient method for correcting the lighting bias and a novel combination of techniques to detect different cell areas and isolate parts of the cell vital to their movement. To the best of our knowledge we contribute the only method able to automatically detect the thin cellular membranes in DIC images. We show that the method can be used to isolate features in order to detect variations vital to motility in differently affected cells.