Name
Abstract | ||
|---|---|---|
Statistical shape models have been widely used to guide the segmentation in an image, thus overcoming noise and occlusions. In this study, the authors present a graph cut-based segmentation framework, in which multiple objects can be segmented. They design a specific multilabel shape prior, which is integrated into the graph cost function. They also want to enforce spatial constraint between the o... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1049/iet-ipr.2015.0408 | IET Image Processing |
Keywords | Field | DocType |
biomedical MRI,graph theory,image segmentation,medical image processing,statistical analysis | Cut,Computer vision,Scale-space segmentation,Graph energy,Pattern recognition,Segmentation,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Connected-component labeling,Minimum spanning tree-based segmentation,Mathematics | Journal |
Volume | Issue | ISSN |
10 | 10 | 1751-9659 |
Citations | PageRank | References |
3 | 0.40 | 26 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Damien Grosgeorge | 1 | 68 | 3.59 |
| Caroline Petitjean | 2 | 390 | 28.57 |
| Ruan Su | 3 | 559 | 53.00 |