Name
Abstract | ||
|---|---|---|
In this paper, we propose a parallel algorithm for data classification, and its application for Magnetic Resonance Images (MRI) segmentation. The studied classification method is the well-known c-means method. The use of the parallel architecture in the classification domain is introduced in order to improve the complexities of the corresponding algorithms, so that they will be considered as a pre-processing procedure. The proposed algorithm is assigned to be implemented on a parallel machine, which is the reconfigurable mesh computer (RMC). The image of size (mxn) to be processed must be stored on the RMC of the same size, one pixel per processing element (PE). |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.parco.2011.03.001 | Parallel Computing |
Keywords | Field | DocType |
parallel algorithm,classification method,parallel architecture,proposed algorithm,magnetic resonance images,corresponding algorithm,parallel c-means algorithm,reconfigurable mesh computer,data classification,well-known c-means method,classification domain,parallel machine,image segmentation,magnetic resonance image,classification | Reconfigurable mesh,Computer science,Theoretical computer science,Image segmentation,Processing element,Artificial intelligence,Data classification,Computer vision,Segmentation,Parallel algorithm,Algorithm,Pixel,Parallel architecture | Journal |
Volume | Issue | ISSN |
37 | 4-5 | Parallel Computing |
Citations | PageRank | References |
1 | 0.37 | 20 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Omar Bouattane | 1 | 11 | 10.43 |
| Bouchaib Cherradi | 2 | 3 | 2.80 |
| Mohamed Youssfi | 3 | 6 | 8.68 |
| Mohamed O. Bensalah | 4 | 1 | 0.37 |