Parametric B-Spline Snakes on Distance Maps—Application to Segmentation of Histology Images
S.C. Sekhar, F. Aguet, S. Romain, P. Thévenaz, M. Unser
Proceedings of the Sixteenth European Signal Processing Conference (EUSIPCO'08), Lausanne VD, Switzerland, August 25-29, 2008, in press.
Please do not bookmark the In Press papers as content and presentation may differ from the published version.
In a few seconds, you should be redirected to the published version. The preprint version is still available here
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.