Improving the Robustness of Cell Nucleus Segmentation

A highly successful active contour implementation, for the automatic segmentation of cervical cell nuclei, is shown to lend itself well to a framework that further increases its success rate. The method is based upon measuring changes in the final contour as the one parameter that governs its behaviour is varied. Only one object of interest is contained in the image, but as artefacts often appear as well, the contour varies with the parameter as it finds different solutions. In contrast, simple images with no artefacts are very stable. Therefore a stability measure is calculated and each image is classified according to its degree of ‘difficulty’. A system can then choose at which level to operate to ensure only high quality examples are processed after segmentation.