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• W2076459392 abstract "Segmentation is a fundamental step in quantifying characteristics, such as volume, shape, and orientation of cells and/or tissue. However, quantification of these characteristics still poses a challenge due to the unique properties of microscopy volumes. This paper proposes a 2D segmentation method that utilizes a combination of adaptive and global thresholding, potentials, z direction refinement, branch pruning, end point matching, and boundary fitting methods to delineate tubular objects in microscopy volumes. Experimental results demonstrate that the proposed method achieves better performance than an active contours based scheme." @default.
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• W2076459392 date "2015-03-06" @default.
• W2076459392 modified "2023-09-23" @default.
• W2076459392 title "Boundary fitting based segmentation of fluorescence microscopy images" @default.
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• W2076459392 doi "https://doi.org/10.1117/12.2085417" @default.
• W2076459392 hasPublicationYear "2015" @default.
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