Abstract
This paper deals with the segmentation of cell nuclei in tissue. We present a region-based segmentation method where seeds representing object- and background-pixels are created by morphological filtering. The seeds are then used as a starting-point for watershed segmentation of the gradient magnitude of the original image. Over-segmented objects are thereafter merged based on the gradient magnitude between the adjacent objects. The method was tested on a total of 726 cell nuclei in 7 images, and 95% correct segmentation was achieved.
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Wählby, C., Bengtsson, E. (2003). Segmentation of Cell Nuclei in Tissue by Combining Seeded Watersheds with Gradient Information. In: Bigun, J., Gustavsson, T. (eds) Image Analysis. SCIA 2003. Lecture Notes in Computer Science, vol 2749. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45103-X_55
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DOI: https://doi.org/10.1007/3-540-45103-X_55
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