Counting cells and following the evolution of the biological layers are important applications in microscopic imagery. In this paper, a microscopic image segmentation method with ...
Abstract. Processing biological data often requires handling of uncertain and sometimes inconsistent information. Particularly when coping with image segmentation tasks against bio...
?This paper presents a computational paradigm called Data-Driven Markov Chain Monte Carlo (DDMCMC) for image segmentation in the Bayesian statistical framework. The paper contribut...
In this paper we derive differential equations for evolving radial basis functions (RBFs) to solve segmentation problems. The differential equations result from applying variation...
In this paper, we propose a general framework for fusing bottom-up segmentation with top-down object behavior classification over an image sequence. This approach is beneficial fo...