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• W2129536519 abstract "The large amount of data produced by biological live cell imaging studies of cell behavior requires accurate automated cell segmentation algorithms for rapid, unbiased and reproducible scientific analysis. This paper presents a new approach to obtain precise boundaries of cells with complex shapes using ridge measures for initial detection and a modified geodesic active contour for curve evolution that exploits the halo effect present in phase-contrast microscopy. The level set contour evolution is controlled by a novel spatially adaptive stopping function based on the intensity profile perpendicular to the evolving front. The proposed approach is tested on human cancer cell images from LSDCAS and achieves high accuracy even in complex environments." @default.
• W2129536519 created "2016-06-24" @default.
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• W2129536519 date "2008-10-01" @default.
• W2129536519 modified "2023-10-14" @default.
• W2129536519 title "Cell segmentation using Hessian-based detection and contour evolution with directional derivatives" @default.
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• W2129536519 doi "https://doi.org/10.1109/icip.2008.4712127" @default.
• W2129536519 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/2743148" @default.
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