Abstract
With the huge amount of cell images produced in bio-imaging, automatic methods for segmentation are needed in order to evaluate the content of the images with respect to types of cells and their sizes. Traditional PDE-based methods using level-sets can perform automatic segmentation, but do not perform well on images with clustered cells containing sub-structures. We present two modifications for popular methods and show the improved results.
Cite
CITATION STYLE
Kuijper, A., Heise, B., Zhou, Y., He, L., Wolinski, H., & Kohlwein, S. (2015). Segmentation of clustered cells in microscopy images by geometric pdes and level sets. In Handbook of Biomedical Imaging: Methodologies and Clinical Research (pp. 475–487). Springer US. https://doi.org/10.1007/978-0-387-09749-7_26
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