Name
Abstract | ||
|---|---|---|
This paper presents a segmentation framework in a high content screening (HCS) context based on variational snakes. We introduce a modified internal energy function for the snake evolution taking into account the different artifacts appearing in confocal microscopic images during a screening session. This framework is particularly well suited and efficient for nuclei segmentation, providing an accurate base for higher level image analysis. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ISBI.2010.5490166 | Rotterdam |
Keywords | Field | DocType |
biomedical optical imaging,cellular biophysics,image segmentation,medical image processing,optical microscopy,active contour,artifacts,cell segmentation,confocal microscopy,high content screening,modified internal energy function,nuclei segmentation,spatially adaptive relaxation,variational snakes,active contours,image processing,image segmentation,microscopy | Active contour model,Computer vision,Scale-space segmentation,Pattern recognition,Computer science,Segmentation,Signal-to-noise ratio,Image processing,Segmentation-based object categorization,Image segmentation,Artificial intelligence,High-content screening | Conference |
ISSN | ISBN | Citations |
1945-7928 E-ISBN : 978-1-4244-4126-6 | 978-1-4244-4126-6 | 0 |
PageRank | References | Authors |
0.34 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arnaud Ogier | 1 | 20 | 4.09 |
| Thierry Dorval | 2 | 22 | 3.23 |
| Kim, B. | 3 | 0 | 0.34 |
| Auguste Genovesio | 4 | 42 | 7.98 |