Name
Abstract | ||
|---|---|---|
Snakes, or active contours, have been widely used to locate boundaries of image segmentation and computer vision. Problem associated with the existence of the local minima in the active contour energy function makes snakes have poor convergence in segmentation process; therefore, the poor convergence has limited applications. In this work, a fast minimization of snake model is used for an MRI knee image segmentation. This method provides a satisfied result. As a result, it is a good candidate for MRI image segmentation approach. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICARCV.2008.4795795 | ICARCV |
Keywords | Field | DocType |
biomedical MRI,computer vision,image segmentation,medical image processing,minimisation,MRI knee image segmentation,active contour energy function,active contours,computer vision,fast global minimization,image segmentation,snake model,MRI image segmentation,active contours,global minimization,snakes | Active contour model,Convergence (routing),Computer vision,Scale-space segmentation,Segmentation,Computer science,Segmentation-based object categorization,Image segmentation,Maxima and minima,Minimisation (psychology),Artificial intelligence | Conference |
ISBN | Citations | PageRank |
978-1-4244-2287-6 | 1 | 0.36 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thi-Thao Tran | 1 | 32 | 3.50 |
| Po-Lei Lee | 2 | 168 | 17.42 |
| Van-Truong Pham | 3 | 53 | 5.29 |
| Kuo-Kai Shyu | 4 | 394 | 43.06 |