Cell Tracking in Video Microscopy Using Bipartite Graph Matching

Automated visual tracking of cells from video microscopy has many important biomedical applications. In this paper, we model the problem of cell tracking over pairs of video microscopy image frames as a minimum weight matching problem in bipartite graphs. The bipartite matching essentially establishes one-to-one correspondences between the cells in different frames. A key advantage of using bipartite matching is the inherent scalability, which arises from its polynomial time-complexity. We propose two different tracking methods based on bipartite graph matching and properties of Gaussian distributions. In both the methods, i) the centers of the cells appearing in two frames are treated as vertices of a bipartite graph and ii) the weight matrix contains information about distance between the cells (in two frames) and cell velocity. In the first method, we identify fast-moving cells based on distance and filter them out using Gaussian distributions before the matching is applied. In the...

• Type: Conference
• Year: 2010
• Where: ICPR
• Authors: Ananda Chowdhury, Rohit Chatterjee, Mayukh Ghosh, Nilanjan Ray
• Keywords: Bipartite Graph, Bipartite Graph Matching, Bipartite Matching, Computer Vision, ICPR 2010