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Technical Program
Paper Detail
| Paper: | TP-P3.11 |
| Session: | Biomedical Image Segmentation and Quantitative Analysis |
| Time: | Tuesday, October 10, 14:20 - 17:00 |
| Presentation: |
Poster
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| Title: |
BIOPHYSICAL ACTIVE CONTOURS FOR CELL TRACKING I: TENSION AND BENDING |
| Authors: |
Jacques Pecreaux; Max Planck Institute of Molecular Cell Biology and Genetics | | | | | Christophe Zimmer; Pasteur Institute | | | | | Jean-Christophe Olivo-Marin; Pasteur Institute | | |
| Abstract: |
Automatic segmentation and tracking of biological objects from dynamic microscopy data is of great interest for quantitative biology. A successful framework for this task are active contours, curves that iteratively minimize a cost function, which contains both dataattachment terms and regularization constraints reflecting prior knowledge on the contour geometry. However the choice of these latter terms and of their weights is largely arbitrary, thus requiring timeconsuming empirical parameter tuning and leading to sub-optimal results. Here, we report on a first attempt to use regularization terms based on known biophysical properties of cellular membranes. The present study is restricted to 2D images and cells with a simple cytoskeletal cortex underlying the membrane. We describe our new active contour model and its implementation, and show a first application to real biological images. The obtained segmentation is slightly better than standard active contours, however the main advantage lies in the self-consistent and automated determination of the weights of regularization terms. This encouraging result will lead us to extend the approach to 3D and more complex cells. |
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