Name
Abstract | ||
|---|---|---|
Segmentation of image is used from a long time in medical image applications and its study is increased for enhanced the medical diagnosis. This paper concerns a deformable segmentation method for abnormal cells detection by using an improved Level set model which is solved several problems and disadvantages of others segmentation technique. Our approach employed by using real data of carcinoma cells obtained from optical microscopy. Preliminary simulation results showed high performance metrics of the proposed model. Comparative study with manual segmentation demonstrated and confirmed that the level set can be a promise model of abnormal cells detection and in a particularly an irregular shape like carcinoma cells type. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/CoDIT.2014.6996994 | CoDIT |
Keywords | Field | DocType |
cancer,image segmentation,medical image processing,abnormal cell detection,abnormal cell segmentation,carcinoma cancer cells,deformable segmentation method,image segmentation,level set model,medical diagnosis,medical image applications,optical microscopy,carcinoma,level-set,microscopy,segmentation | Computer vision,Scale-space segmentation,Computer science,Segmentation,Level set,Artificial intelligence,Abnormal cells | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haj-Hassan, H. | 1 | 1 | 0.72 |
| Ahmad Chaddad | 2 | 0 | 0.68 |
| Tanougast, C. | 3 | 29 | 4.03 |
| Harkouss, Y. | 4 | 0 | 0.34 |