Name
Title | ||
|---|---|---|
PARAMETRIC B-SPLINE SNAKES ON DISTANCE MAPS—APPLICATION TO SEGMENTATION OF HISTOLOGY IMAGES |
Abstract | ||
|---|---|---|
We construct parametric active contours (snakes) for outlining cells in histology images. These snakes are de- fined 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 thus obtained, we compute a distance map and specify it as one of the snake energies. To ensure smooth con- tours, we also introduce a regularization term that fa- vors smooth contours. A convex combination of the two cost functions results in smooth contours that lock onto edges eciently and consistently. Experimental results on real histology images show that the snake algorithm is robust to imperfections in the images such as broken edges. |
Year | Venue | Field |
|---|---|---|
2008 | EUSIPCO | Active contour model,B-spline,Computer vision,Segmentation,Convex combination,Parametric statistics,Regularization (mathematics),Distance transform,Basis function,Artificial intelligence,Mathematics |
DocType | Citations | PageRank |
Conference | 2 | 0.41 |
References | Authors | |
9 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| S. Chandra Sekhar | 1 | 42 | 6.12 |
| Francois Aguet | 2 | 5 | 1.21 |
| Sebastien Romain | 3 | 2 | 0.41 |
| Philippe Thevenaz | 4 | 35 | 3.26 |
| M Unser | 5 | 4335 | 499.89 |