Name
Abstract | ||
|---|---|---|
The analysis of in vitro cultured stem cells is a challenging task. One particularly important question pertains the relationship between proliferation and differentiation. Here, we introduce an image-based method to combine information about cellular genealogies with an analysis of the protein expression of cells in a culture dish. The method uses a time-series of microscopical images and a immunofluorescence (IF) image. The time-series can be used to obtain the genealogical nexus, while the IF-image displays the expression of a chosen marker-protein within each cell. The task was then to find an algorithm, which automatically maps the last image of the time-series onto the immunofluorescence image. Our solution to this problem is to use a cell detection algorithm in the time-lapse images and a cell nuclei detection in the IF-images to determine the position of the cells. Then, the cell positions are used to match the images with a geometric hashing based method. The robustness of the implemented algorithm is demonstrated using microscopical reference data. In addition, the algorithm was used to estimate the displacement of the cell nuclei (IF image) relatively to the cell shape position, i.e. the centroids in the time-lapse data. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ISBI.2013.6556622 | Biomedical Imaging |
Keywords | Field | DocType |
biomedical optical imaging,cellular biophysics,fluorescence,image matching,medical image processing,object tracking,optical microscopy,proteins,time series,IF-image,automatic mapping,cell detection algorithm,cell differentiation,cell nuclei detection,cell nuclei displacement,cell position determination,cell proliferation,cell protein expression analysis,cell shape position,cellular genealogies,centroid time-lapse data,chosen marker-protein expression,genealogical nexus,geometric hashing based method,image matching,image-based method,immunofluorescence image,in vitro cultured stem cell,microscopical image,microscopical reference data,phase contrast,time-lapse image,time-series,Cell Tracking,Geometric Hashing,Image Segmentation,Time-Lapse Microscopy | Immunofluorescence,Phase contrast microscopy,Reference data (financial markets),Computer vision,Pattern recognition,Computer science,Robustness (computer science),Video tracking,Artificial intelligence,Protein expression,Geometric hashing,Centroid | Conference |
ISSN | ISBN | Citations |
1945-7928 | 978-1-4673-6456-0 | 0 |
PageRank | References | Authors |
0.34 | 1 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Becker, T. | 1 | 0 | 0.34 |
| Sandra Schultz | 2 | 4 | 2.11 |
| Daniel H. Rapoport | 3 | 0 | 1.01 |
| Amir Madany Mamlouk | 4 | 37 | 9.52 |