Variational B-Spline Level-Set Method for Fast Image Segmentation
O. Bernard, D. Friboulet, P. Thévenaz, M. Unser
Proceedings of the Fifth IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI'08), Paris, French Republic, May 14-17, 2008, pp. 177–180.
In the field of image segmentation, most of level-set-based active contour approaches are based on a discrete representation of the associated implicit function. We present in this paper a different formulation where the level-set is modelled as a continuous parametric function expressed on a B-spline basis. Starting from the Mumford-Shah energy functional, we show that this formulation allows computing the solution as a restriction of the variational problem on the space spanned by the B-splines. As a consequence, the minimization of the functional is directly obtained in terms of the B-splines parameters. We also show that each step of this minimization may be expressed through a convolution operation. Because the B-spline functions are separable, this convolution may in turn be performed as a sequence of simple 1D convolutions, which yields a very efficient algorithm. The behaviour of this approach is illustrated on biomedical images from various fields.
@INPROCEEDINGS(http://bigwww.epfl.ch/publications/bernard0801.html,
AUTHOR="Bernard, O. and Friboulet, D. and Th{\'{e}}venaz, P. and Unser,
M.",
TITLE="Variational \mbox{{B}-Spline} Level-Set Method for Fast Image
Segmentation",
BOOKTITLE="Proceedings of the Fifth {IEEE} International Symposium on
Biomedical Imaging: {F}rom Nano to Macro ({ISBI'08})",
YEAR="2008",
editor="",
volume="",
series="",
pages="177--180",
address="Paris, French Republic",
month="May 14-17,",
organization="",
publisher="",
note="")