Name
Title | ||
|---|---|---|
PSO Kernel Fuzzy Clustering Based Cerebrospinal Fluid Evaluation for Multiple Sclerosis Algorithm |
Abstract | ||
|---|---|---|
In order to improve the effectiveness of medical image segmentation algorithm, a PSO nuclear fuzzy clustering algorithm was proposed to evaluate the test of cerebrospinal fluid in multiple sclerosis. The iterative bilateral scale spatial decomposition is used to construct the multi-scale representation of the image, and then the local texture features are extracted by image block and random projection, and the random texture features are generated. A texture primitive dictionary is randomly generated and represents the global texture model. According to this global texture appearance model, the occurrence probability of texture primitives in an image region can be obtained from the texture appearance model of an area. Finally, a random region merging algorithm based on PSO kernel fuzzy clustering algorithm is proposed to realize medical image segmentation based on regional texture appearance model. The experimental results show that the proposed method has better cerebrospinal fluid test results for multiple sclerosis, and has better recognition rate and running time index. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1166/jmihi.2020.2860 | JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS |
Keywords | DocType | Volume |
Particle Swarm,Nuclear Fuzzy Clustering,Multiple Sclerosis,Cerebrospinal Fluid,Test Evaluation | Journal | 10 |
Issue | ISSN | Citations |
1 | 2156-7018 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lin Hua | 1 | 0 | 0.34 |
| Wang Yong | 2 | 0 | 0.34 |
| Chen Yanling | 3 | 0 | 0.34 |
| Zheng Xuxu | 4 | 0 | 0.34 |
| Xu Suxian | 5 | 0 | 0.34 |