AI Article Synopsis
- Developed an active contour method for segmenting and tracking cells in noisy phase-contrast microscopy images, enhancing fine-grained segmentation.
- Improved the model by selectively identifying and removing low-confidence contour areas for better accuracy.
- Tested on HMEC-1 cells, showing it quantitatively matches manual contours and effectively tracks cell boundaries over many frames.
Article Abstract
Previously we developed an active contour method for segmenting and tracking cells in phase-contrast microscopy images. Our method is capable of fine-grained segmentation on noisy image sequences. In this paper, we improve the active contour segmentation model to provide better accuracy, by selectively identifying areas of the contour with low confidence and removing them. The method is applied to HMEC-1 cells (human microvascular endothelial cells). The segmentation provided by the method is quantitavely compared with manually-drawn contours, showing close fit and capability to 'lock' on to cell boundaries for hundreds of frames.
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| http://dx.doi.org/10.1109/EMBC.2012.6347207 | DOI Listing |
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