Name
Abstract | ||
|---|---|---|
An accurate localization of a cell nucleus boundary is inevitable for any further quantitative analysis of various subnuclear structures within the cell nucleus. In this paper, we present a novel approach to the cell nucleus segmentation in fluorescence microscope images exploiting the level set framework. The proposed method works in two phases. In the first phase, the image foreground is separated from the background using a fast level set-like algorithm by Nilsson and Heyden [1]. A binary mask of isolated cell nuclei as well as their clusters is obtained as a result of the first phase. A fast topology-preserving level set-like algorithm by Maška and Matula [2] is applied in the second phase to delineate individual cell nuclei within the clusters. The potential of the new method is demonstrated on images of DAPI-stained nuclei of a lung cancer cell line A549 and promyelocytic leukemia cell line HL60. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-02230-2_40 | SCIA |
Keywords | Field | DocType |
individual cell nucleus,dapi-stained nucleus,two-phase segmentation,cell nucleus,fast level set-like algorithms,cell nucleus boundary,isolated cell nucleus,fast level set-like algorithm,fast topology-preserving level set-like,promyelocytic leukemia cell line,lung cancer cell line,cell nuclei,cell nucleus segmentation,level set,cell line,quantitative analysis | Cluster (physics),Fluorescence microscope,Computer science,Level set,Cell,Artificial intelligence,Binary number,Active contour model,Computer vision,Pattern recognition,Geodesic active contour,Segmentation,Algorithm | Conference |
Volume | ISSN | Citations |
5575 | 0302-9743 | 3 |
PageRank | References | Authors |
0.39 | 9 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Martin Maška | 1 | 32 | 3.32 |
| Ondřej Daněk | 2 | 19 | 1.89 |
| C. Ortiz-de-Solorzano | 3 | 17 | 1.83 |
| Arrate Muñoz-Barrutia | 4 | 123 | 20.02 |
| Michal Kozubek | 5 | 114 | 17.80 |
| Ignacio Fernández García | 6 | 3 | 0.39 |