Name
Title | ||
|---|---|---|
3D brain tumor segmentation scheme using K-mean clustering and connected component labeling algorithms |
Abstract | ||
|---|---|---|
In the recent years human brain segmentation in three-dimensional magnetic resonance imaging (MRI) has gained a lot of importance in the field of biomedical image processing since it is the main stage for the automatic brain disease diagnosis. In this paper, we propose an image segmentation scheme to segment 3D brain tumor from MRI images through the clustering process. The clustering is achieved using K-mean algorithm in conjunction with the connected component labeling algorithm to link the similar clustered objects in all 2D slices and then obtain 3D segmented tissue using the patch object rendering process. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ISDA.2010.5687244 | Intelligent Systems Design and Applications |
Keywords | Field | DocType |
biomedical MRI,image segmentation,medical image processing,patient diagnosis,pattern clustering,rendering (computer graphics),tumours,3D brain tumor segmentation,3D magnetic resonance imaging,3D segmented tissue,K-mean clustering,biomedical image processing,brain disease diagnosis,connected component labeling algorithm,patch object rendering process | Scale-space segmentation,Computer science,Segmentation-based object categorization,Image processing,Image segmentation,Artificial intelligence,Cluster analysis,k-means clustering,Computer vision,Pattern recognition,Segmentation,Algorithm,Connected-component labeling,Machine learning | Conference |
ISBN | Citations | PageRank |
978-1-4244-8134-7 | 8 | 0.59 |
References | Authors | |
4 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hossam M. Moftah | 1 | 36 | 3.54 |
| Aboul Ella Hassanien | 2 | 1610 | 192.72 |
| Mohamoud Shoman | 3 | 8 | 0.59 |
| Moftah, H.M. | 4 | 10 | 0.98 |
| ella Hassanien, A. | 5 | 36 | 4.57 |