Voronoi-Based segmentation of cells on image manifolds

Authors:
Thouis R. Jones;Anne Carpenter;Polina Golland
Affiliations:
MIT CSAIL, Cambridge, MA;Whitehead Institute for Biomedical Research, Cambridge, MA;MIT CSAIL, Cambridge, MA
Venue:
CVBIA'05 Proceedings of the First international conference on Computer Vision for Biomedical Image Applications
Year:
2005

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Abstract

We present a method for finding the boundaries between adjacent regions in an image, where “seed” areas have already been identified in the individual regions to be segmented. This method was motivated by the problem of finding the borders of cells in microscopy images, given a labelling of the nuclei in the images. The method finds the Voronoi region of each seed on a manifold with a metric controlled by local image properties. We discuss similarities to other methods based on image-controlled metrics, such as Geodesic Active Contours, and give a fast algorithm for computing the Voronoi regions. We validate our method against hand-traced boundaries for cell images.