Name
Abstract | ||
|---|---|---|
Leukocyte migration is an important phenomenon in the inflammatory tissue. The migration process includes the rolling velocity decreasing and the leukocytes adhesion. However, the analysis of in vivo microscopy video is a labor-intensive and time consuming task. Several approaches have been proposed for tracking leukocyte movements. However, these approaches can either only track leukocytes that roll along the centerline of the blood vessel, or can only handle leukocytes with fixed morphologies. In addition, the camera/subject movement is a severe problem which occurs frequently while analyzing in vivo microscopy videos. In this paper, we proposed a new method for automatic recognition of non-adherent and adherent leukocytes. The experimental results demonstrate the effectiveness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/IPC.2007.52 | IPC |
Keywords | Field | DocType |
microscopy,data mining,edge detection,tracking | Computer vision,Computer science,Edge detection,In vivo,Adhesion,Artificial intelligence,Microscopy | Conference |
ISBN | Citations | PageRank |
0-7695-3006-0 | 0 | 0.34 |
References | Authors | |
10 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chengcui Zhang | 1 | 789 | 84.56 |
| Wei-Bang Chen | 2 | 97 | 18.16 |
| Lin Yang | 3 | 13 | 11.70 |
| Xin Chen | 4 | 98 | 9.56 |