Name
Abstract | ||
|---|---|---|
•Augmented feature improves performance for multi-atlas patch-based segmentation.•KNN classifier in multi-atlas segmentation can be replaced by SVM.•SVM outperforms KNN slightly but with higher computation cost.•Validated on MICCAI SATA data set and comparable to state-of-the-art. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.media.2014.09.005 | Medical Image Analysis |
Keywords | Field | DocType |
Multi-atlas segmentation,Patch-based segmentation,Cardiac image segmentation,Augmented features | Computer vision,Feature vector,Scale-space segmentation,Pattern recognition,Segmentation,Support vector machine,Segmentation-based object categorization,Image segmentation,Region growing,Artificial intelligence,Mathematics,Minimum spanning tree-based segmentation | Journal |
Volume | Issue | ISSN |
19 | 1 | 1361-8415 |
Citations | PageRank | References |
17 | 0.70 | 44 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wenjia Bai | 1 | 445 | 35.84 |
| Wenzhe Shi | 2 | 792 | 39.85 |
| Christian Ledig | 3 | 489 | 27.08 |
| Daniel Rueckert | 4 | 9338 | 637.58 |