Name
Abstract | ||
|---|---|---|
Volume segmentation is of great significances for feature visualization and feature extraction, essentially volume segmentation can be viewed as generalized cluster. This paper proposes a hybrid approach via symmetric region growing (SRG) and information diffusion estimation (IDE) for volume segmentation, the volume dataset is over-segmented to series of subsets by SRG and then subsets are clustered by K-Means basing on distance-metric derived from IDE, experiments illustrate superiority of the hybrid approach with better segmentation performance. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1587/transinf.2017EDL8085 | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS |
Keywords | Field | DocType |
volume segmentation, hybrid approach, SRG, over-segment, IDE, cluster | Computer vision,Pattern recognition,Segmentation,Computer science,Artificial intelligence | Journal |
Volume | Issue | ISSN |
E100D | 9 | 1745-1361 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Li Wang | 1 | 0 | 1.69 |
| Xiaoan Tang | 2 | 36 | 8.24 |
| Junda Zhang | 3 | 0 | 2.03 |
| Dongdong Guan | 4 | 4 | 4.79 |