Name
Title | ||
|---|---|---|
A novel level set model with automated initialization and controlling parameters for medical image segmentation. |
Abstract | ||
|---|---|---|
•Only one parameter needs to be changed manually for different images in our model.•We propose a novel adaptive mean shift clustering method to guide the evolution of level set.•The results of clustering can automatically generate an initial contour of level set evolution.•The controlling parameters of level set evolution can be automatically estimated.•We use reaction diffusion method in our model to avoid re-initialization. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.compmedimag.2015.12.005 | Computerized Medical Imaging and Graphics |
Keywords | Field | DocType |
Medical image segmentation,Adaptive mean shift clustering,Level set method,Automated initialization,Reaction diffusion method | Computer vision,Scale-space segmentation,Computer science,Segmentation,Level set method,Level set,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Mean-shift,Cluster analysis | Journal |
Volume | ISSN | Citations |
48 | 0895-6111 | 3 |
PageRank | References | Authors |
0.38 | 16 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qingyi Liu | 1 | 3 | 0.38 |
| Mingyan Jiang | 2 | 67 | 11.96 |
| Peirui Bai | 3 | 3 | 0.38 |
| Guang Yang | 4 | 6 | 1.09 |