Name
Abstract | ||
|---|---|---|
Cell nuclei detection in fluorescent microscopic images is an important and time consuming task for a wide range of biological applications. Blur, clutter, bleed through and partial occlusion of nuclei make this a challenging task for automated detection of individual nuclei using image analysis. This paper proposes a novel and robust detection method based on the active contour framework. The method exploits prior knowledge of the nucleus shape in order to better detect individual nuclei. The method is formulated as the optimization of a convex energy function. The proposed method shows accurate detection results even for clusters of nuclei where state of the art methods fail. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-33191-6_12 | ADVANCES IN VISUAL COMPUTING, ISVC 2012, PT II |
Keywords | Field | DocType |
microscopy,image analysis,tracking,segmentation | Active contour model,Computer vision,Nucleus,Pattern recognition,Clutter,Segmentation,Computer science,Regular polygon,Software,Artificial intelligence | Conference |
Volume | ISSN | Citations |
7432 | 0302-9743 | 1 |
PageRank | References | Authors |
0.37 | 11 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jonas De Vylder | 1 | 14 | 7.62 |
| Jan Aelterman | 2 | 80 | 11.46 |
| Mado Vandewoestyne | 3 | 1 | 0.37 |
| Trees Lepez | 4 | 1 | 0.37 |
| Dieter Deforce | 5 | 14 | 2.56 |
| Wilfried Philips | 6 | 1476 | 124.85 |