Name
Title | ||
|---|---|---|
Hierarchical max-flow segmentation framework for multi-atlas segmentation with Kohonen self-organizing map based Gaussian mixture modeling |
Abstract | ||
|---|---|---|
•Novel probabilistic multi-atlas segmentation framework.•Large scale Gaussian mixture models achieved through Kohonen self-organizing maps.•Deformable registration and label fusion generate spatial priors from the multi-atlas.•Max-flow solver incorporates these priors with hierarchical label information.•Framework validated on 2 open neuro-imaging databases. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.media.2015.05.005 | Medical Image Analysis |
Keywords | Field | DocType |
ASETS,Multi-region segmentation,Convex optimization,Kohonen self-organizing map,GPGPU | Computer vision,Scale-space segmentation,Pattern recognition,Segmentation,Segmentation-based object categorization,Self-organizing map,Image segmentation,General-purpose computing on graphics processing units,Artificial intelligence,Mixture model,Mathematics,Minimum spanning tree-based segmentation | Journal |
Volume | ISSN | Citations |
27 | 1361-8415 | 10 |
PageRank | References | Authors |
0.49 | 44 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Martin Rajchl | 1 | 421 | 34.67 |
| John S. H. Baxter | 2 | 74 | 14.67 |
| A. Jonathan McLeod | 3 | 56 | 10.08 |
| Jing Yuan | 4 | 182 | 12.30 |
| Wu Qiu | 5 | 203 | 18.54 |
| Terry M. Peters | 6 | 1335 | 181.71 |
| Ali R. Khan | 7 | 189 | 17.12 |