Sammanfattning |
Gradient vector flow (GVF) was introduced by Xu and Prince
in 1998 as an external force for segmentation using active contour
models (snakes). The basic idea behind GVF is to propagate edge
information from strong boundaries into homogeneous regions by
diffusing the gradient vectors of an edge map derived from the
original image. In 3D, a problem is that the convergence rate of the
commonly used numerical scheme to compute GVF does not allow for
practical use. For interactive 3D medical image segmentation with GVF,
computational times in the order of a minute rather than an hour are
needed. In this talk, the aim is to present alternative computation
schemes (stationary iterative methods, conjugate gradients, and
multigrid methods) and give hints on their advantages and
disadvantages. |