In this paper the neural progenitor cells in a time-lapse microscopic sequence are analyzed to find position, shape, motility, and ancestor of each cell in the frame. Because of the complex nature of cells, the ability to distinguish a cell from the background of an image for automatic quantification remains a challenging task. By using morphological techniques, the blob-like objects are selected. The cells are detected using h-maxima transform and the cell contours are selected using watershed algorithm. The cells between image sequences are tracked using multiple matching object method based on modified Mahalanobis algorithm. The proposed method has been successfully applied to a large number of images and showed promising results for tracking cells between consecutive images.
Time-lapse Live Imaging of Clonally Related Neural Progenitor Cells in the Developing Zebrafish Forebrain