Model-based segmentation of nuclei

Abstract A new approach for the segmentation of nuclei observed with an epi-fluorescence microscope is presented. The proposed technique is model based and uses local feature activities in the form of step-edge segments, roof-edge segments, and concave corners to construct a set of initial hypotheses. These local feature activities are extracted using either local or global operators and corresponding hypotheses are expressed as hyperquadrics. A neighborhood function is defined over these features to initiate the grouping process. The search space is expressed as an assignment matrix with an appropriate cost function to ensure local and neighborhood consistency. Each possible configuration of nucleus defines a path and the path with least overall error is selected for final segmentation. The system is interactive to allow rapid localization of large numbers of nuclei. The operator then eliminates a small number of false alarms and errors in the segmentation process.