Abstract
Accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression in high-throughput screening applications. We propose a new approach for segmenting cell nuclei which is based on active contours and convex energy functionals. Compared to previous work, our approach determines the global solution. Thus, the approach does not suffer from local minima and the segmentation result does not depend on the initialization. We also suggest a numeric approach for efficiently computing the solution. The performance of our approach has been evaluated using fluorescence microscopy images of different cell types. We have also performed a quantitative comparison with previous segmentation approaches.
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Keywords
- Segmentation Result
- Active Contour
- Fluorescence Microscopy Image
- Energy Functional
- Intensity Inhomogeneity
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Bergeest, JP., Rohr, K. (2011). Fast Globally Optimal Segmentation of Cells in Fluorescence Microscopy Images. In: Fichtinger, G., Martel, A., Peters, T. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011. MICCAI 2011. Lecture Notes in Computer Science, vol 6891. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23623-5_81
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DOI: https://doi.org/10.1007/978-3-642-23623-5_81
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