Automatic Quantification of Filopodia-Based Cell Migration
| Authors | |
|---|---|
| Year of publication | 2013 |
| Type | Article in Proceedings |
| Conference | 10th IEEE International Symposium on Biomedical Imaging |
| MU Faculty or unit | |
| Citation | |
| web | http://dx.doi.org/10.1109/ISBI.2013.6556563 |
| Doi | https://doi.org/10.1109/ISBI.2013.6556563 |
| Field | Informatics |
| Keywords | Filopodium segmentation;fluorescence microscopy;steerable filtering;geodesic distance |
| Description | We present a fully automatic approach to quantitatively analyze filopodia-based migration of fluorescent cells in 3D time-lapse series. The proposed method involves three steps. First, each frame of the time-lapse series is preprocessed using a steerable filter and binarized to obtain a coarse segmentation of the cell shape. Second, a sequence of morphological filters is applied on the coarse binary mask to separate the cell body from individual filopodia. Finally, their length is estimated using a geodesic distance transform. The proposed approach is validated on 3D time-lapse series of lung adenocarcinoma cells. We show that the number of filopodia and their average length can be used as a descriptor to discriminate between different phenotypes of migrating cells. |
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