Name
Abstract | ||
|---|---|---|
The existing Fast Marching methods which are used to solve the Eikonal equation use a locally continuous model to estimate
the accumulated cost, but a discontinuous (discretized) model for the traveling cost around each grid point. Because the accumulated
cost and the traveling (local) cost are treated differently, the estimate of the accumulated cost at any point will vary based
on the direction of the arriving front. Instead we propose to estimate the traveling cost at each grid point based on a locally
continuous model, where we will interpolate the traveling cost along the direction of the propagating front. We further choose
an interpolation scheme that is not biased by the direction of the front. Thus making the fast marching process truly isotropic.
We show the significance of removing the directional bias in the computation of the cost in certain applications of fast marching
method. We also compare the accuracy and computation times of our proposed methods with the existing state of the art fast
marching techniques to demonstrate the superiority of our method.
|
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-15567-3_6 | Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer Vision |
Keywords | Field | DocType |
isotropic fast marching,eikonal equation,existing fast marching method,existing state,grid point,fast marching methods,segmentation,directional bias,minimal cost path,computation time,tracking,continuous model,certain application,minimal cost path.,cartesian grid,fmm,propagating front,biomedical research,fast marching method,bioinformatics,fast marching | Discretization,Computer science,Interpolation,Artificial intelligence,Cartesian coordinate system,Computation,Computer vision,Continuous modelling,Mathematical optimization,Fast marching method,Eikonal equation,Algorithm,Grid | Conference |
Volume | ISSN | ISBN |
6316 | 0302-9743 | 3-642-15548-0 |
Citations | PageRank | References |
2 | 0.40 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vikram Appia | 1 | 24 | 2.73 |
| Anthony J. Yezzi | 2 | 2016 | 151.48 |