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We construct parametric active contours (snakes) for outlining cells in histology images. These snakes are defined in terms of cubic B-spline basis functions. We use a steerable ridge detector for obtaining a reliable map of the cell boundaries. Using the contour information, we compute a distance map and specify it as one of the snake energies. To ensure smooth contours, we also introduce a regularization term that favors smooth contours. A convex combination of the two cost functions results in smooth contours that lock onto edges efficiently and consistently. Experimental results on real histology images show that the snake algorithm is robust to imperfections in the images such as broken edges.
Volkan Cevher, Grigorios Chrysos, Fanghui Liu, Elias Abad Rocamora