Name
Abstract | ||
|---|---|---|
•A spatially constrained generative asymmetric GMM is proposed.•We modify the asymmetric GMM to introduce the spatial information.•We approximate the log-priors with two auxiliaries set.•We construct an asymmetric weight factor.•We incorporate the bias field estimation model. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.cmpb.2017.08.017 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
Gaussian mixture model,Asymmetric distribution,Expectation-maximization algorithm,Brain MR image segmentation,Markov random fields,Intensity inhomogeneity | Computer vision,Scale-space segmentation,Pattern recognition,Computer science,Sørensen–Dice coefficient,Segmentation,Expectation–maximization algorithm,Segmentation-based object categorization,Image segmentation,Statistical model,Artificial intelligence,Mixture model | Journal |
Volume | Issue | ISSN |
151 | C | 0169-2607 |
Citations | PageRank | References |
2 | 0.37 | 37 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zexuan Ji | 1 | 459 | 26.03 |
| Yong Xia | 2 | 32 | 5.58 |
| Yuhui Zheng | 3 | 16 | 3.28 |