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Harmonic Cut and Regularized Centroid Transform for Localization of Subcellular Structures
Quebec City, QC, Canada August 11-August 15
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.104487716th International Conference on Patt ...
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Qing Yang, Lawrence Berkeley National Laboratory
Bahram Parvin, Lawrence Berkeley National Laboratory
Two novel computational techniques, harmonic cut and regularized centroid transform, are developed for segmentation of cells and their corresponding substructures observed with an epi-fluorescence microscope. Harmonic cut detects small regions that correspond to subcellular structures. These regions also affect the accuracy of the overall segmentation. They are detected, removed, and interpolated to ensure continuity within each region. We show that interpolation within each region (subcellular compartment) is equivalent to solving the Laplace equation on a multi-connected domain with irregular boundaries. The second technique, referred to as the regularized centroid transform, aims to separate touching compartments. This is achieved by adopting a quadratic model for the shape of the object and relaxing it for final segmentation.
Index Terms:
segmentation, scale-space, regularization, vector field
Citation:
Qing Yang, Bahram Parvin, "Harmonic Cut and Regularized Centroid Transform for Localization of Subcellular Structures," icpr, vol. 1, pp.10788, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 1, 2002
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